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MCP Tool Reference

The MCP server provides 243 tools organized by category (218 static + 25 dynamic per-recipe-script tools).

Cross-Harness Discovery (RFC #113)

Four small tools let any MCP client — Claude Code, Cursor, Codex, vanilla Agents SDK — ground itself and reach the routing layer without depending on the initialize instructions block. Call them at session start or when the agent needs to check what Pretorin can do.

check_context

Cheap, unauthenticated probe of session grounding. Reads local CLI config only — no platform calls. Returns:

{
  "connected": true,
  "platform_api_base_url": "http://localhost:8000/api/v1/public",
  "active_system": {"id": "sys-1", "name": "Primary"},
  "active_framework_id": "nist-800-53-r5",
  "suggested_next": "Ready. Call `start_task` with an `intent_verb` to route the user's request to a workflow.",
  "pending_attention": {}
}

platform_api_base_url is the non-secret REST endpoint the MCP client will use, so a local or customer-managed rehearsal can prove it is not pointed at the hosted production platform. suggested_next is deterministic and tells the agent exactly what to do given current state — call pretorin login, call list_systems, set a framework, or proceed with start_task.

Parameters: None.

When to call: Once at session start. Always safe; never makes a platform call.


list_tools

Compact catalog of every available tool. Returns one short record per tool:

{
  "total": 243,
  "tier_counts": {"default": 9, "reference": 148, "workflow": 61, "recipe": 25},
  "tools": [
    {"name": "check_context", "purpose": "Cheap, unauthenticated probe of session grounding", "tier": "default", "requires_workflow": false},
    ...
  ]
}

The full payload fits in roughly 100 lines — far smaller than fetching every tool’s inputSchema. Tier classification:

TierMeaning
defaultAlways advertised. Minimum surface to ground a session and route a task.
referenceRead-only browsing of frameworks, controls, systems, recipes. Safe without prior routing.
workflowRequires prior start_task context. Calling without it raises WorkflowRoutingError.
recipeDynamic per-recipe-script tools (recipe_<id>__<script>).

Parameters: None.

When to call: Once at session start (or anytime “what’s available?” comes up).


search_platform_capabilities

Search the product-facing Pretorin Platform Capability Index for features that can satisfy a compliance requirement. This is a searchable product source, not a catalog dump. Agents should call it before creating local tracking documents, spreadsheets, registers, placeholder evidence, or shadow systems of record.

{
  "query": "vendor management system for third-party risk and vendor documents",
  "framework_id": "soc2",
  "control_id": "CC9.2",
  "limit": 3
}

Returns compact matches, best-scoring first. The satisfies, mcp_tools, and search_terms lists below are abridged for readability — the real response carries every entry the matched capability declares:

{
  "source_kind": "pretorin_platform_capabilities",
  "query": "vendor management system for third-party risk and vendor documents",
  "framework_id": "soc2",
  "control_id": "CC9.2",
  "total_matches": 3,
  "matches": [
    {
      "capability_id": "vendor_management",
      "name": "Vendor Management",
      "surface": "Vendors",
      "availability": "platform_ui_and_mcp",
      "satisfies": ["track third-party providers and service providers"],
      "mcp_tools": [
        "list_vendors",
        "create_vendor",
        "upload_vendor_document",
        "sign_vendor_residual_acceptance",
        "link_evidence_to_vendor"
      ],
      "search_terms": ["vendor", "third-party", "supplier"],
      "agent_guidance": "Use Pretorin Vendor Management as the system of record before creating local vendor inventories, assessment trackers, or document folders.",
      "source_kind": "pretorin_platform_capabilities",
      "system_of_record": true,
      "confidence": "high"
    }
  ],
  "note": "Search this product capability index before creating local tracking documents, spreadsheets, registers, or placeholder artifacts. A zero-match response means the local catalog did not find a product surface; it is not proof that Pretorin lacks one."
}

Capabilities are curated per product surface, so a vendor query also returns neighboring surfaces — here vendor_assessment_workflows (assessment templates, launches, scoring, and reviewer finalization) ranks second. Read the capability_id and surface of each match rather than assuming the first one owns every tool in the domain. A zero-match response is not proof that Pretorin lacks the surface; ask the user or check the platform.

Availability values:

AvailabilityMeaning
platform_ui_and_mcpPretorin has a product surface and MCP tools the agent can use.
platform_ui_with_mcp_readPretorin has a product surface plus read-oriented MCP context, but the full workflow may stay in the platform UI.
platform_ui_onlyPretorin has a product surface, but the current MCP/CLI does not expose the workflow.

Parameters:

  • query (required) — Plain-English requirement or proposed local artifact.
  • framework_id (optional) — Framework context.
  • control_id (optional) — Control context.
  • limit (optional, 1–10, default 5) — Maximum matches to return.

When to call: Before creating local artifacts to satisfy a requirement that sounds like vendor management, risk tracking, POA&M/weakness tracking, vendor assessments, formal assessments, policy management, system scope/profile management, approval workflow, compliance report generation, eMASS synchronization, SPRS scoring, OSCAL packages, STIG/CCI tracking, or another GRC platform feature.


get_instructions

Returns the server’s routing instructions as a regular tool response. Mirrors the text the MCP initialize handshake advertises in the instructions field, for harnesses (Cursor, Codex, vanilla Agents SDK) that don’t render that text to the agent.

Parameters: None.

When to call: If the agent didn’t receive routing rules via the initialize handshake, or wants to re-read them mid-session.


Routing Errors (errors-as-instructions)

Workflow-tier tools require an active routing context — either an active system/framework set via pretorin context set, or the context that start_task resolves. Calling a workflow write without context returns a structured error payload, not just plain text:

{
  "error": "workflow_required",
  "message": "No active system/framework context. Call start_task with an intent_verb to route the request to the right workflow, or run `pretorin context set --system <id> --framework <id>` in the terminal.",
  "routing_hint": {
    "reason": "no_active_context",
    "next_action": "call_start_task",
    "missing": ["system_id", "framework_id"],
    "suggested_intent_verb": "collect_evidence"
  }
}

The response carries isError=true so agents that only check the error flag still surface the failure, but the parseable body tells them exactly which start_task call to make. This means routing rules live in the protocol, not the preamble — harnesses that ignore instructions still see the rules in the error payload they have to read anyway.

Evidence and narrative producer writes add one more guardrail: create_evidence, create_evidence_batch, and update_narrative require recipe_context_id from start_recipe. Missing recipe context returns recipe_required with a recipe_gap before scope resolution, so agents converge on start_task → source preflight → start_recipe → write.

suggested_intent_verb is set when the called tool has a registered mapping (see _TOOL_TO_INTENT_VERB in src/pretorin/mcp/server.py). Every tool in WORKFLOW_TIER has one; tools added to that set without a mapping will fail the sync test in CI.


Workflow Schema Bundling

When the agent calls get_workflow, the response includes required_tool_schemas — the full MCP Tool definitions for every tool the workflow body references:

{
  "id": "single-control",
  "manifest": { "..." },
  "body": "## Single Control Update\n\n...",
  "required_tool_schemas": [
    {"name": "create_evidence", "description": "...", "inputSchema": {...}},
    {"name": "update_narrative", "description": "...", "inputSchema": {...}},
    ...
  ]
}

Single round trip equips the agent. Schemas are response data — agents can read them as reference regardless of whether their harness supports dynamic tool registration.

Large playbooks can be read without host-side clipping. Pass mode="compact" to keep the complete Markdown body and every validation keyword while omitting non-validating schema and tool-description annotations. Pass section="<heading-id>" to retrieve one complete heading and its nested content; the response lists valid heading IDs in response_metadata.available_sections. Selection is explicit and response_metadata.truncated remains false for a complete requested slice.


Telemetry

The server emits structured telemetry events to stderr so MCP hosts can capture them through their existing log pipeline. Each event is one line:

PRETORIN_TELEMETRY_EVENT {"ts": 1747249200.12, "event_type": "workflow_routing_required", "tool": "create_evidence", "reason": "no_active_context", "missing": ["system_id", "framework_id"], "suggested_intent_verb": "collect_evidence"}
PRETORIN_TELEMETRY_EVENT {"ts": 1747249200.99, "event_type": "recipe_required", "tool": "create_evidence", "reason": "agent write attempted without recipe_context_id", "requested_evidence_type": "code_snippet", "suggested_next": "call_start_task_then_start_recipe"}

Events emitted:

event_typeWhen
start_task_succeededA start_task call completed successfully (the canonical-path signal).
workflow_routing_requiredA write tool raised WorkflowRoutingError (the bypass signal).
recipe_requiredAn evidence or narrative producer write returned the structured recipe-context guardrail before scope resolution.

For the post-recipe producer path, compute the combined bypass rate as:

(workflow_routing_required + recipe_required) / start_task_succeeded

When your log pipeline can group by MCP session, count only bypass events that did not have the expected preceding canonical calls in that same session: start_task for workflow_routing_required, and start_task → source preflight → start_recipe for recipe_required. The recipe_required event carries only non-content shape data such as evidence type, item count, narrative length, and suggested_next; it must not include artifact content, narrative text, evidence ids, control ids, or source excerpts.

Per RFC #113 and issue #121, this combined bypass data gates any phase-4 default-surface cull or capability-negotiation work.

Opt-out: set PRETORIN_MCP_TELEMETRY_DISABLED=1 in the environment before starting the MCP server. Local-only — no PII or content leaves the user’s machine.


Common Write-Side Parameters

Most write-side tools (evidence, narratives, issues, control status, monitoring events) share one audit-trail flag and one plan-attribution pair.

  • allow_unverified_sources (optional, default false) — Permit a write when source attestation shows a mismatch. Listed below as “(audit-trail flag)”. Set it only when the calling agent has a deliberate reason to bypass that guardrail.
  • plan_id (optional) — Id of the agent-authored Plan this write belongs to. When supplied, the platform write is tagged with the Plan and the Plan’s local produced_artifacts[] audit chain gets an entry.
  • step_index (optional) — Zero-based index of the Plan step that triggered the write. Only meaningful alongside plan_id.

There is no scope-override parameter. An MCP agent can never write outside the active system/framework context by passing a flag: only a human switching context with pretorin context set moves that boundary. A cross-scope write is refused regardless of the arguments sent.

MCP agent evidence and narrative writes require recipe_context_id returned by start_recipe; writes without one return a structured recipe_required error.

Task Routing

start_task

Route a user prompt to the right workflow. Call this after check_context whenever the user references compliance work (a control, system, framework, questionnaire, source preflight, or campaign). The calling agent extracts entities from the user prompt and supplies them as structured args; pretorin applies deterministic rules to pick a workflow and bundles the platform read-state (workflow_state, compliance_status, pending items) into the response. The agent then reads the selected workflow’s body via get_workflow and follows it.

The one exception is pure reference questions (“show me AC-2”, “list frameworks”) — those go directly to the read-side tools without start_task.

Argument shape: all prompt-derived fields (intent_verb, raw_prompt, system_id, framework_id, control_ids, scope_question_ids, policy_question_ids) must be nested inside the entities object. Only active_system_id, active_framework_id, skip_inspect, and create_new_plan live at the top level — those come from the CLI runtime, not the user prompt. Flattening prompt entities to the top level is a common caller bug: such top-level copies are ignored by the handler (not read, not rejected), so the route is decided from entities alone and the misplaced fields silently have no effect.

Parameters:

  • entities (required) — Structured entities extracted from the user prompt. Required sub-fields: intent_verb (one of work_on, collect_evidence, draft_narrative, answer, policy_definition, scope_artifacts, preflight, stig_scan, risk_assessment, formal_assessment, campaign, inspect_status) and raw_prompt (original verbatim text). Optional sub-fields: system_id, framework_id, control_ids, scope_question_ids, policy_question_ids. All prompt-derived entities live here — do not flatten them to the top level. preflight routes source discovery, binding, verification, and recipe provisioning to the preflight workflow. The three lifecycle intents route to stig-scan-remediation, risk-assessment, and formal-assessment, respectively.
  • active_system_id (optional) — The user’s active CLI context system_id, if any. Used to detect cross-system writes.
  • active_framework_id (optional) — The user’s active CLI context framework_id, if any. Used by inspect_status when the user asks for current status without naming a framework.
  • skip_inspect (optional) — Skip the server-side platform reads when the calling agent already has fresh state. Default: false
  • include_source_hints (optional) — Return full source_hints in suggested_capture_plan instead of compact hint summaries. Only honored for single-control tasks; multi-control summaries never inline hints. Default: false
  • create_new_plan (optional) — Force a separate Plan even when an exact-context non-terminal Plan already exists. Default: false

Returns: Selected workflow id, resolved scope (system/framework/items), platform-state bundle, and suggested_capture_plan for source/recipe preflight when the workflow produces evidence or narratives. For a single control, the local draft Plan already contains the required evidence-expectation-mapping step; activate_plan preserves it before narrative composition. The capture plan carries compact per-expectation items: verbose source_hints are replaced with source_hint_count and preferred_source_hint; pass include_source_hints=true for full hints. For multiple controls (e.g. a control family routed to the campaign workflow), the plan is a bounded per-control summary with no items or recipe_gaps keys — counts, statuses, and a top_capture_hint per control — sized for agent context budgets. Call check_sources for the full per-expectation detail of any one control.

Plan reuse: before creating a Plan, start_task looks for non-terminal Plans in the identical execution context — same workflow, same scope (system, framework, control, and any workflow-specific targets such as questionnaire question ids or a campaign’s control filter), same intent verb, and the same prompt text ignoring case and whitespace. Matching Plans come back in resume_candidates, using the same summary shape as list_recent_plans. A single candidate is adopted automatically and its id is returned as plan_id, so repeated calls don’t accumulate duplicate Plans. With two or more candidates the response carries no plan_id and the caller picks one. Pass create_new_plan=true to start a separate Plan regardless. Candidates never cross a system or framework boundary; when a route has no system/framework context at all, only Plans with equally unresolved scope can match.


Framework & Control Reference

These tools are read-only and available to all authenticated users.

list_frameworks

List all available compliance frameworks.

Parameters: None

Returns: List of frameworks with ID, title, version, tier, and control counts.


get_framework

Get detailed metadata about a specific framework including AI context (purpose, target audience, regulatory context).

Parameters:

  • framework_id (required) — e.g., nist-800-53-r5, fedramp-moderate

Returns: Framework details including description, version, OSCAL version, and dates.


list_control_families

List control families for a framework with AI context (domain summary, risk context, implementation priority).

Parameters:

  • framework_id (required)

Returns: List of control families with ID, title, class, and control count.


list_controls

List controls for a framework, optionally filtered by family.

Parameters:

  • framework_id (required)
  • family_id (optional) — Family IDs are slugs like access-control, not short codes. CMMC families include a level suffix (e.g., access-control-level-2).

Returns: List of controls with ID, title, and family.


get_control

Get detailed control information including AI guidance (summary, control intent, evidence expectations, implementation considerations, common failures, complexity).

Parameters:

  • framework_id (required)
  • control_id (required) — NIST/FedRAMP: zero-padded (ac-01). CMMC: dotted (AC.L2-3.1.1).

Returns: Control details including parameters, parts, and enhancement count.


get_controls_batch

Get detailed control data for many controls in one framework-scoped request.

Parameters:

  • framework_id (required)
  • control_ids (optional) — List of canonical control IDs; omit to retrieve all controls in the framework

Returns: Full control detail records for the requested controls.


get_control_references

Get reference information including statement, guidance, objectives, and related controls.

Parameters:

  • framework_id (required)
  • control_id (required)

Returns: Statement, guidance, objectives, parameters, and related controls.


OSCAL Artifacts

Read-only access to validated OSCAL export artifacts (SSP/SAR/SAP/POA&M/ component-definition). Generation stays on the platform; these tools list and inspect what exists. Both are read-only and not active-context-enforced.

list_oscal_artifacts

List validated OSCAL artifacts for a system. Server-filtered to generation_state = succeeded AND validation_status = valid.

Parameters:

  • system_id (required)
  • artifact_type (optional) — ssp, sap, sar, poam, component_definition, bundle
  • framework_id (optional)
  • assessment_id (optional)
  • limit (optional, 1–100, default 50)
  • offset (optional, default 0)

Returns: artifacts (list of summaries with type, version, oscal_version, validation status) and total.

get_oscal_artifact

Get artifact metadata including the two-tier validation report and a presigned download URL.

Parameters:

  • system_id (required)
  • artifact_id (required)

Returns: Full metadata — oscal_version, generator_version, validation_report, checksum_sha256, file_size, and download_url.


Systems

list_systems

List systems in the current organization.

Parameters: None

Returns: System IDs, names, and summary metadata.


get_cli_status

Return the local Pretorin CLI version status, including update availability and upgrade guidance for MCP hosts and agents.

Parameters:

  • force (optional) — Bypass the local cache and re-resolve the latest version from the channel this install actually upgrades through (PyPI for Python-package installs; the public tap’s releases for raw binaries; the published tap formula for Homebrew installs). Default: false

Returns: Current version, latest version, update available flag, passive-notification and check state, plus four upgrade_* fields:

  • upgrade_command — the command (or, where no self-update exists, the openable release URL) for this install. Never a pip/uv hint for a frozen binary.
  • upgrade_requires_human_approvaltrue whenever upgrade_command is a command that mutates this machine’s Pretorin install. Present it to the human operator; do not execute it. false only for installs with no self-update path, where the value is a download page and nothing changes until a person acts on it.
  • upgrade_restart_requiredtrue on the same routes: an already-running MCP server keeps serving the previous version until the host restarts it.
  • upgrade_note — prose explaining, for this specific install, what the command changes and why a restart is needed. Route-specific, so it can never disagree with the command beside it.

get_source_manifest

Get the resolved source manifest for a system and evaluate it against currently detected sources. Shows which external sources (git, cloud, HRIS, etc.) are required, recommended, or optional, and whether each is currently satisfied.

Parameters:

  • system_id (optional) — System ID or name
  • framework_id (optional) — Defaults to active context

Returns: Source manifest with per-source satisfaction status. Returns null manifest if none is configured.


get_system

Get system metadata including attached frameworks and security impact level.

Parameters:

  • system_id (required) — System ID or name

Returns: System metadata.


get_preflight

Read the local preflight verdict for the active (or given) scope: which recommended source kinds are mapped to host-local resolvers and their per-kind rollup (ready/degraded/missing/unverified/unmapped). This is the CLI-local source of truth for source availability — the platform cannot verify connections. When authenticated it also seeds the platform’s in-scope recommended source kinds into the artifact (persisted only when the profile changed something; offline it is a pure local read).

Parameters:

  • system_id (optional) — System ID or name; defaults to the active scope
  • framework_id (optional) — Framework ID; defaults to the active scope

Returns: Preflight artifact with per-kind resolver bindings and rollup. Returns exists=false with a hint when no artifact has been built yet and the platform recommends nothing.


verify_preflight

Probe every resolver bound in the preflight artifact for this scope, persist the results, and return the refreshed verdict. Probes run locally on the CLI host (e.g. gh auth status, az account show, workspace path checks).

Parameters:

  • system_id (optional) — System ID or name; defaults to the active scope
  • framework_id (optional) — Framework ID; defaults to the active scope

Returns: Refreshed preflight verdict with per-resolver probe results.


update_preflight

Bind resolver collections to recommended source kinds and persist the preflight artifact. Each kind maps to a collection of resolvers (each tells a distinct piece of the evidence story); a kind’s collection is replaced wholesale. Resolver types are open: workspace_path, cli_tool, command, manual/attested, mcp, connected_api, pretorin_feature, or any custom type with a probe.

Parameters:

  • bindings (required) — Array of per-kind resolver bindings to upsert. Each entry has kind (canonical source kind), optional recommended flag, and a resolvers array (each resolver has type, optional name, constraints, scope, params, and capabilities).
  • system_id (optional) — System ID or name; defaults to the active scope
  • framework_id (optional) — Framework ID; defaults to the active scope

Returns: The persisted preflight artifact with the updated bindings.


get_compliance_status

Get framework progress and implementation posture for a system.

Parameters:

  • system_id (required) — System ID or friendly system name

Returns: Framework status summaries and progress metrics.


set_target_scale_tier

Declare or clear the engagement’s target scale tier for a system/framework scope. The declared tier overrides the platform-derived tier used for guidance and expectation coverage.

Parameters:

  • system_id (optional) — Defaults to the active scope
  • framework_id (optional) — Defaults to the active scope
  • target_scale_tier (required) — baseline, moderate, or comprehensive; pass null to clear the override

Returns: target_scale_tier, derived_scale_tier, effective_scale_tier, and the platform’s reasoning.


Evidence Management

search_evidence

Search evidence within exactly one active system/framework scope. With query, performs RAG semantic search over attached evidence and scoped unattached evidence (including org policy documents) so agents can reuse existing evidence before creating new artifacts. Without query, lists evidence linked to control_id or the current framework scope.

Parameters:

  • system_id (optional) — System ID or friendly system name. When omitted, the active CLI scope is used if available.
  • control_id (optional) — Filter by control
  • framework_id (optional) — Filter by framework
  • query (optional) — Natural-language RAG query. Provide this before creating evidence to find currently attached evidence and reusable unattached evidence.
  • include_attached (optional) — When query is set, include evidence already attached to control_id. Default: true
  • include_unattached (optional) — When query is set, include scoped evidence not attached to control_id, including org policy evidence. Default: true
  • min_similarity (optional) — When query is set, minimum semantic similarity threshold. Default: 0.6
  • limit (optional) — Maximum number of results (default 20 for listing; RAG queries default to 5 and are capped at 50)
  • include_metadata / include_full_detail (optional) — When query is set, request full per-result metadata and control mappings. Default: false, which returns compact count markers such as metadata_key_count and control_mapping_count.
  • snippet_only (optional) — When query is set, replace large body fields such as artifact_content and matched_text with short snippets. Default: true
  • max_body_chars (optional) — When query is set and snippet_only=false, maximum characters to keep per body field. Use a positive value to opt into capped body content. Default: 0
  • snippet_chars (optional) — When query is set, maximum characters returned for each body-field snippet. Default: 500

Returns: Matching evidence items. RAG query responses are compact by default: full metadata and control mappings are replaced with counts, and full body fields are replaced with snippets and omitted-character counts so hot-path agent calls stay below tool-result limits. Pass include_metadata=true only when full per-result detail is needed; pass snippet_only=false with a positive max_body_chars only when body content is explicitly needed.


create_evidence

Upsert evidence on the platform (find-or-create by default). If dedupe is true, exact matching evidence in the active system/framework scope is reused; otherwise a new record is created.

Parameters:

  • name (required)
  • description (required) — Short human summary of what the evidence demonstrates
  • artifact_content (required) — Markdown body containing the actual evidence artifact. Start directly with factual content; omit section headers and standalone bold labels because the SSP supplies headings. Do not include gap lists, missing-information placeholders, unresolved caveats, or remediation backlog.
  • evidence_type (required) — Must be one of the canonical evidence types
  • system_id (optional) — Defaults to active scope
  • control_id (optional)
  • framework_id (optional)
  • dedupe (optional) — Default: true
  • code_file_path (optional) — Path to source file (relative to workspace root)
  • code_line_numbers (optional) — Line range (e.g., 10-25)
  • code_snippet (optional) — Relevant code excerpt
  • code_repository (optional) — Git repository URL
  • code_commit_hash (optional) — Git commit hash
  • source_uri, source_label, source_locator, source_excerpt, capture_method (optional at the MCP layer) — Structured provenance inputs. If omitted, the handler derives safe defaults from code context or active scope. Note: the platform’s audit-metadata contract (issue #701) requires source_locator for agent-produced evidence — the handler auto-derives lines N-M from code_line_numbers when present, but for non-code sources (policy excerpts, docs, vendor reports, dashboards) you must pass an explicit locator such as section 3.7 or page 4 paragraph 2, otherwise the platform rejects the write with Missing: source_locator.
  • recipe_context_id (required) — Active recipe execution context from start_recipe; evidence is stamped producer_kind='recipe' automatically.
  • allow_unverified_sources (optional, audit-trail flag)
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns:

  • evidence_id
  • created — true if new, false if reused
  • linked — whether control/system link succeeded
  • match_basisexact_name_desc_type_control_framework or none

create_evidence_batch

Create and link multiple evidence items within one system/framework scope in a single request.

Parameters:

  • items (required) — Array of evidence payloads. Each item: name, description, artifact_content, control_id, evidence_type (required); optional relevance_notes, code_file_path, code_line_numbers, code_snippet, code_repository, code_commit_hash, source_uri, source_label, source_locator, source_excerpt, capture_method. Artifact content uses the same no-heading, no-gap-discussion rule as create_evidence. The platform’s audit-metadata contract (issue #701) requires source_locator for agent writes — pass an explicit locator (e.g., section 3.7, lines 84-88, page 4 paragraph 2) on each item from a non-code source, or the platform will reject the corresponding item with Missing: source_locator.
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • recipe_context_id (required) — Active recipe execution context from start_recipe; every item in the batch is stamped producer_kind='recipe'. All items share the same context — per-item context variation is not supported in v1.
  • allow_unverified_sources (optional, audit-trail flag)
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: Batch creation summary with per-item results and created evidence IDs.


Link an existing evidence item to a control and classify its relationship to the control’s declared evidence expectations. Narrative citations ground claims but do not satisfy expectation coverage.

Parameters:

  • evidence_id (required)
  • control_id (required)
  • system_id (optional) — Defaults to active scope
  • framework_id (optional)
  • expectation_key (preferred) — Stable key from get_control_context.expectation_coverage
  • expectation_item (optional) — Raw expectation text; the platform hashes it to the stable key. Use this or expectation_key.
  • unbound_reason (conditional) — Required instead of an expectation binding when the artifact supports no declared expectation. The platform preserves the control link, clears any expectation binding the artifact currently has, and records the reason in its audit chain; the call fails closed unless the platform confirms the unbind. Never use it on an artifact that is correctly bound — it removes real expectation coverage. Mutually exclusive with the expectation fields.
  • allow_unverified_sources (optional, audit-trail flag)
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Pass an expectation binding or unbound_reason; an unclassified MCP agent link is refused. When the write carries plan_id and the mapping step’s step_index, the Plan records the evidence id and expectation key (or unbound reason) under produced_artifacts.

Returns: Link confirmation plus expectation_mapping.status (bound or intentionally_unbound).


Link an existing evidence item to a per-system CCI implementation row. Use when you already have the CCI implementation UUID (from get_cci_implementation or get_cci_status).

Parameters:

  • evidence_id (required)
  • cci_implementation_id (required)
  • system_id (optional) — Defaults to active scope
  • override_system_mismatch (optional, default false) — Permit cross-system attachment
  • override_reason (optional) — Required when override_system_mismatch is true
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: Link confirmation with link_summary.cci_implementation_id.


Link an existing evidence item to a STIG rule workflow. Lazy-creates the workflow row if none exists yet for (system, stig_rule). Use to attach remediation proof, mitigating-control documentation, or waiver-justification artifacts to a failing rule.

Parameters:

  • evidence_id (required)
  • stig_rule_id (required) — STIG catalog rule UUID
  • system_id (optional) — Defaults to active scope
  • override_system_mismatch (optional, default false)
  • override_reason (optional) — Required when override_system_mismatch is true
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: Link confirmation with link_summary.stig_rule_workflow_id.


upload_evidence

Upload a file as evidence to the platform (system-scoped, requires WRITE access).

Parameters:

  • file_path (required) — Absolute path to the file to upload
  • name (required) — Evidence name
  • system_id (optional) — Defaults to active scope
  • evidence_type (optional) — Default: other
  • description (optional) — Evidence description
  • control_id (optional)
  • framework_id (optional)
  • allow_unverified_sources (optional, audit-trail flag)
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: Uploaded evidence record.


delete_evidence

Delete an evidence item from the platform (system-scoped, requires WRITE access).

Parameters:

  • evidence_id (required) — The evidence item ID to delete
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: Deletion confirmation.


get_evidence_attestation

Fetch the DSSE attestation envelope (ADR 0003) for an evidence record. Returns the in-toto Statement, signing key fingerprint, and provenance metadata. Read-only; no recipe context required.

Parameters:

  • evidence_id (required) — The evidence item ID to fetch the attestation for
  • include_lineage (optional, default false) — Also return the full lineage of attestations for this evidence (newest first)
  • include_archived (optional, default false) — When include_lineage is set, include archived attestations

Returns: DSSE envelope plus statement, signer fingerprint, and provenance fields. With include_lineage=true, also includes prior envelopes. Returns a structured attestation_unavailable error when the platform attestation surface is disabled or no envelope exists for the row.


get_narrative

Get the current narrative record for a control.

Parameters:

  • control_id (required)
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • allow_unverified_sources (optional, audit-trail flag)

Returns: Narrative text, status, AI confidence metadata, and citations[]. Each citation includes grounding (claim_grounded, document_grounded, or ungrounded) plus any locator_chunk_index and matched_excerpt.


Implementation Context

get_control_context

Get rich context for a control including AI guidance, statement, objectives, scope status, current implementation details, and the full per-expectation coverage map.

This is the read that gives an author both halves of the grading contract in one call: ai_guidance is the rubric the platform’s AI review scores against, and ai_analysis is its last verdict against that rubric.

Parameters:

  • control_id (required)
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope

Returns: Combined control metadata and implementation details. expectation_coverage maps each expectation to its expectation_key, item, tier, covered state, bound evidence, and unconfirmed suggestions. evidence_expectations carries one tier per expectation (top-level, and mirrored under ai_guidance), and scale_tier.tier is the confirmed target tier to compare them against. ai_analysis is the read-only projection of the platform’s last AI review — see Reading the AI review. Null on platforms that predate the field.


get_scope

Get system scope and policy information including excluded controls and Q&A responses.

Parameters:

  • system_id (required)
  • framework_id (required)

Returns: Scope narrative, excluded controls, Q&A responses, and scope status.


patch_scope_qa

Apply partial scope questionnaire updates for a system/framework.

Parameters:

  • system_id (required)
  • framework_id (required)
  • updates (required) — Non-empty list of {question_id, answer} objects
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: Updated scope questionnaire state, including the saved responses.


list_org_policies

List organization policies available for questionnaire work.

Parameters: None

Returns: Policy summaries including id, name, template linkage, and questionnaire status.


get_org_policy_questionnaire

Get the canonical questionnaire state for one organization policy. For a large questionnaire, set include_guidance=false to omit static template and question guidance from the MCP projection.

Parameters:

  • policy_id (required)
  • include_guidance (optional, default true)

Returns: Policy metadata, saved answers, and the merged template/question set when available.


patch_org_policy_qa

Apply partial questionnaire updates for one organization policy.

Parameters:

  • policy_id (required)
  • updates (required) — Non-empty list of {question_id, answer} objects
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: Updated organization policy questionnaire state.


get_control_implementation

Get implementation details for a control in a system.

Parameters:

  • control_id (required)
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • allow_unverified_sources (optional, audit-trail flag)

Returns: Current status, narrative, evidence count, operating_evidence_count (excluding the automatic scope document), compact expectation_coverage, and issue metadata.


get_control_issues

Get issues for a control implementation.

Parameters:

  • control_id (required)
  • system_id (optional) — Defaults to active scope
  • framework_id (optional)
  • status (optional) — all (default), open, or resolved
  • limit (optional) — 1–1000, default 50
  • offset (optional) — Default 0
  • snippet_only (optional) — Replace body-sized fields such as content with bounded snippets; default true
  • max_body_chars (optional) — With snippet_only=false, retain at most this many characters per body field; use a positive value to request body content

Returns: A bounded Issue page. total, open_total, blocking_total, and non_blocking_total describe the returned page; matched_total, matched_open_total, matched_blocking_total, and matched_non_blocking_total describe the complete filtered set before pagination. returned, limit, offset, and has_more make pagination explicit. An unreadable_total appears only if the platform returned a record that is not an issue object, so nothing vanishes silently.

Open Issues are serialized before resolved history (with stable relative order inside each group), including when status=all. This ensures a bounded page or final response-guard compaction retains approval-gating work first. For full content, request a small page with snippet_only=false and a positive max_body_chars.

Demonstrated control deficiencies gate approval. Calibrated evidence-gap Issues carry is_blocking: false and are tracked without gating approval; non_blocking_total reports them. Above-target “areas to strengthen” are still reported in ai_analysis.gaps_detail, where is_blocking can be false, and are never filed as Issues.

Issues filed by the AI review also carry ai_review_finding_key, which matches a finding_key in ai_analysis.gaps_detail or .unsupported_claims — that is how you trace an issue back to the reasoning behind it. Treat ai_analysis as explanatory read-only output: the platform reconciler owns AI finding Issues, so agents must not copy those findings into add_control_issue. Agent-authored Issues are only for gaps independently observed in the workspace or another connected source. This avoids duplicate Issues even when an analysis is stale or superseded.

Each row also carries control_implementation_id and issue_id — the pair the Issue treatment tools are addressed by — plus lifecycle_status and gate_status.


get_system_issues

List issues across a whole system/framework instead of one control at a time. Use this to find open remediation work without walking every control.

Parameters:

  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • status (optional) — open (default), resolved, or all
  • source (optional) — manual, rfi, monitoring, cli, mapping, finding, ai_review, or all
  • control_id (optional) — Narrow to a single control
  • limit (optional) — 1–1000, default 500
  • offset (optional) — Default 0

Returns: The same normalized shape and counts as get_control_issues (total, open_total, blocking_total, non_blocking_total, and unreadable_total when applicable), scoped to the returned page. Adds matched_total — every row the filter matched server-side, which exceeds the page counts when paginating — plus limit, offset, and the resolved system_id and framework_id. Rows add control_id, control_title, and control_status.


get_control_notes

Deprecated alias for get_control_issues.

Parameters:

  • control_id (required)
  • system_id (optional) — Defaults to active scope
  • framework_id (optional)
  • status, limit, offset, snippet_only, max_body_chars (optional) — Same bounded-read controls as get_control_issues

Returns: The same bounded Issue page as get_control_issues. Compatibility responses also include notes.


Reading the AI review

The platform reviews a control narrative against ai_guidance.evidence_expectations and persists the verdict. get_control_context and get_control_implementation return it as ai_analysis:

  • gaps_detail[] — each {text, tier, tier_label, exceeds_target, is_blocking, finding_key}. is_blocking: false means the gap sits above your target scale tier: worth doing, not required.
  • unsupported_claims[] — each {claim, reason, finding_key}: a narrative claim no cited evidence backs.
  • strengths[], recommendations[], confidence_score.

confidence_score is null until a review has scored the narrative, so it — not the presence of ai_analysis — tells you whether a review has run.

issues[].is_blocking remains the authority on what gates approval. ai_analysis explains the review’s reasoning; the issue list records what the platform actually enforced, including any human judgement layered on top.


update_narrative

Push a narrative text update produced by a narrative recipe.

Parameters:

  • control_id (required)
  • narrative (required) — Agent-authored control narrative: no section headers, standalone bold labels, or images; target 150–300 words, require at least 800 characters, and never exceed 400 words; start directly with a short implementation overview, include an Expectation | Implemented behavior | Evidence table, and add supported operating detail. A few bullets alone are insufficient. Do not pad, restate the control, or include gap lists, missing-information placeholders, unresolved caveats, or remediation backlog; use add_control_issue.
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • is_ai_generated (optional) — Default: false
  • recipe_context_id (required) — Active narrative-producing recipe context from start_recipe
  • evidence_ids (required) — Evidence ids cited by the narrative
  • evidence_citations (optional) — Full citation objects with evidence_id, optional citation_role, locator_chunk_index, and matched_excerpt. Map search_evidence’s chunk_index and matched_text to the locator fields for claim-level grounding.
  • trigger_review (optional) — Default: false. Explicit exception that asks the platform to review this final narrative generation.
  • review_requested_by_user (conditional) — Must be true with trigger_review=true, confirming the user explicitly requested review. Without it, the tool refuses before saving or enqueueing review.
  • allow_unverified_sources (optional, audit-trail flag)
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: Update confirmation. A normal Plan-attributed single-control save also returns its verified mapping_gate and the structured expectation_coverage read-back used to gate composition.

For a Plan-attributed single-control write, complete the required evidence-expectation-mapping step first: bind or explicitly classify every artifact, re-read get_control_context, and complete the step with its typed evidence_mapping result. The canonical loop is: search/reuse evidence → create evidence as needed → bind expectation keys → re-read coverage → save the mapped, cited narrative with review disabled. The normal result includes mapping_gate and expectation_coverage (covered, uncovered, and unbound_evidence_count) for the handoff. Only an explicit user request may set both review flags; that review result additionally includes an optional coverage_warning and analysis only after the reviewed generation matches the requested target generation. The single-control workflow also seeds narrative_min_chars: 800; call complete_plan after the attributed steps and revise with supported detail if that bounded completion gate fails.


add_control_issue

Admit one independently supported control gap as a canonical Issue. This is not a general task writer: optional advice, missing context, source/recipe gaps, evidence suggestions, subtasks, and findings already represented by an Issue do not qualify. Open issue-create with one stable expectation key, the exact unmet expectation, observed gap and independent observation basis, risk basis and ratings, clearance condition, and non-empty minimum-evidence list. Read current Issues before writing. One expectation gets one Issue.

Parameters:

  • control_id (required)
  • content (required) — Exactly the admitted observed_gap, as one plain sentence of at most 20 words
  • title (required) — Stable title beginning with the admitted expectation_key
  • inherent_likelihood, inherent_impact (required) — NIST 800-30 ratings from very_low through very_high
  • risk_basis (required) — Rationale for the initial provisional risk evaluation
  • detected_at, idempotency_key (optional) — Detection timestamp and organization-scoped retry key
  • issue_kind (optional) — control_gap (default) or evidence_gap. Use evidence_gap only for a completed search that did not observe required active-tier evidence
  • is_blocking (optional) — Default true. Evidence-gap Issues must set false; demonstrated control deficiencies stay true
  • search_context (conditional) — Search scope, query, and result provenance for an evidence_gap Issue
  • recipe_context_id (required) — Active candidate-specific issue-create context from start_recipe
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • allow_unverified_sources (optional, audit-trail flag)
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: The created Issue record. The recipe then creates one minimal draft treatment plan on that same Issue, preserving the clearance condition and minimum evidence. One issue-create context can create at most one Issue.


Canonical Issue Treatment Tools

All treatment tools take control_implementation_id and issue_id, returned by add_control_issue or get_control_issues. Plan/action tools additionally take the relevant plan_id and action_id.

ToolPurpose
get_issue_risk_historyRead immutable risk-evaluation versions
add_issue_risk_evaluationAppend a provisional evaluation; confirm it with confirm_issue_risk_evaluation
set_issue_poam_metadataReplace Issue-owned POA&M projection facts
get_issue_acceptance_historyRead formal risk-acceptance decisions
get_issue_plansRead versioned treatment plans
get_issue_planRead one plan version with its full approval lifecycle
create_issue_plan, update_issue_plan, submit_issue_planBuild a draft and submit it for approval review
confirm_issue_risk_evaluationConfirm the risk determination (supersedes active acceptances)
accept_issue_risk, revoke_issue_risk_acceptanceRecord or withdraw a formal risk acceptance
approve_issue_plan, reject_issue_planDecide a submitted plan
review_issue_opaReview an approved CMMC Operational Plan of Action
complete_issue_planComplete an approved plan — Issue becomes verification_pending, not closed
verify_issueVerify treatment and close the Issue (the only closure path)
void_issueRetire an invalid finding — terminal and irreversible; requires explicit force=true confirmation
get_issue_actionsRead ordered plan actions and milestones
get_issue_actionRead one action or milestone
create_issue_action, update_issue_action, delete_issue_actionManage work while a plan remains draft
transition_issue_actionExecute work in an approved plan (blocked/cancelled require a note)

create_issue_plan / update_issue_plan take kind of remediation or cmmc_opa. The CMMC OPA fields (opa_eligibility_basis, review_frequency_days, next_review_at) are valid only on a cmmc_opa plan, and the two review fields must be supplied together.

set_issue_poam_metadata is a full replacement: every field the platform accepts is written on each call, so an omitted field is cleared.

A WRITE or ADMIN API token is a first-class governed actor for the whole lifecycle, including risk confirmation, acceptance and revocation, plan approval/rejection/review/completion, verification, and voiding. The platform enforces every precondition and returns an explanatory conflict when one is unmet. Two determinations remain interactive-only: poam-set --false-positive and --operational-requirement are rejected for API tokens.


add_control_note

Deprecated alias for add_control_issue.


resolve_control_issue

Reopen or update metadata on one existing Issue while evaluating it through issue-evaluate. Generic update cannot close an Issue. Governed closure is verify_issue after treatment reaches verification_pending; a duplicate or finding that was never valid uses the explicit, irreversible void_issue decision.

Parameters:

  • control_id (required)
  • issue_id (required)
  • recipe_context_id (required) — Active issue-evaluate context for this one Issue
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • is_resolved (optional) — false reopens; true is rejected because closure is governed
  • resolution_note (optional) — Closure-justification metadata only; it does not close the Issue
  • content (optional) — Updated issue content
  • is_pinned (optional)
  • allow_unverified_sources (optional, audit-trail flag)
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: The updated Issue record. issue-evaluate itself finishes with one bounded disposition: verified, one next action, time-bounded risk acceptance, an explicit void candidate, or already terminal. It recognizes an active acceptance before requiring a plan. Every nonterminal source-owned RFI/finding/AI-review Issue stays on its exact source workflow; after source reconciliation moves it to verification_pending, it is verified against the current source result and supporting evidence without a retroactive plan. A planless non-source Issue must be reopened before treatment can be added. It never creates child Issues.


resolve_control_note

Deprecated alias for resolve_control_issue. Accepts note_id instead of issue_id; otherwise the parameter set matches.


Compliance Updates

update_control_status

Start or reopen authoring for a control.

Parameters:

  • control_id (required)
  • status (required) — in_progress
  • system_id (optional) — Defaults to active scope
  • framework_id (optional)
  • allow_unverified_sources (optional, audit-trail flag)
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

CLI/MCP callers cannot set ready_to_approve, implemented, or not_applicable; those decisions happen in the Pretorin UI by a human.

Returns: Status update confirmation.


push_monitoring_event

Create a monitoring event for a system.

Parameters:

  • title (required)
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • severity (optional) — critical, high, medium, low, info. Default: medium
  • event_type (optional) — security_scan, configuration_change, access_review, compliance_check. Default: security_scan
  • control_id (optional)
  • description (optional)
  • allow_unverified_sources (optional, audit-trail flag)
  • plan_id, step_index (optional) — Plan attribution; see Common Write-Side Parameters

Returns: The created monitoring event.


generate_control_artifacts

Generate read-only AI drafts for a control narrative, evidence recommendations, and recommended issues.

Parameters:

  • system_id (required)
  • control_id (required)
  • framework_id (required)
  • working_directory (optional) — Local workspace path for code-aware drafting
  • model (optional) — Model override

Returns: Draft narrative text, evidence recommendations, recommended issues, and prompt_version (which drafting instructions produced this output). Does not write to the platform.

The drafting agent is instructed to read the control’s rubric first — the evidence_expectations list from get_control_context (top-level, falling back to ai_guidance.evidence_expectations), compared against the target tier from scale_tier.tier or, on older platforms, get_scope’s target_scale_tier — and to account for every expectation at or below that tier. An independent observation that proves an expectation unmet becomes a complete Issue candidate; an expectation that is merely unverified goes to needs_input with one concrete next action rather than being silently omitted or mislabeled as an Issue.

Recommended issues come back in two forms:

  • recommended_issues[] — the canonical gap sentence, one short line each. This is the text to file as issue content. It is deliberately terse: the platform reconciler links a CLI-filed issue to its own later AI-review finding by comparing substance words, and a verbose issue scores too low to match, so the two end up filed twice.
  • recommended_issues_detail[] — the admission contract for the same entries: expectation_key, unmet_expectation, observed_gap, observation_basis, risk_basis, inherent_likelihood, inherent_impact, clearance_condition, minimum_evidence, expectation_tier, optional target_completion_date, plus admitted and any admission_errors.
  • needs_input[] — unverified expectations that lack an independent observation, each with expectation_key, reason, and exactly one next_action. These never become Issues during campaign apply.

Campaign proposals submitted through submit_campaign_proposal are normalized to the same forms on the way in. Incomplete legacy candidates remain visible with admitted=false but cannot be written. Apply deduplicates admitted candidates, gives the canonical Issue its short matcher-safe text, and preserves the expectation, observation, clearance condition, and minimum evidence in a minimal draft treatment plan.

To persist approved evidence or narrative changes, first open the matching recipe context; create_evidence and update_narrative require recipe_context_id.


Workflow State & Analytics

get_workflow_state

Get the lifecycle state for a system+framework, showing which stage needs work next (scope, policies, controls, evidence).

Parameters:

  • system_id (required)
  • framework_id (required)

Returns: Current workflow stage, completion percentages, and next recommended action.


get_analytics_summary

Get a lightweight system progress snapshot.

Parameters:

  • system_id (required)
  • framework_id (required)

Returns: Scope completion, policy completion, control coverage, and evidence gaps.


get_family_analytics

Get per-family breakdown with narrative coverage, evidence coverage, and status distribution.

Parameters:

  • system_id (required)
  • framework_id (required)

Returns: Per-family metrics.


get_policy_analytics

Get per-policy breakdown with answer completion and review status.

Parameters:

  • policy_id (required)

Returns: Per-policy completion metrics.


Family Operations

get_pending_families

Identify which control families need work.

Parameters:

  • system_id (required)
  • framework_id (required)

Returns: Families with counts of pending vs total controls.


get_family_bundle

Get all controls in one family with status, narrative presence, evidence presence, and note counts.

Parameters:

  • system_id (required)
  • family_id (required)
  • framework_id (required)

Returns: Complete family bundle with per-control details.


trigger_family_review

Trigger AI review of all controls in a family. Takes 2-4 minutes for large families.

Parameters:

  • system_id (required)
  • family_id (required)
  • framework_id (required)

Returns: Review job ID for polling.


get_family_review_results

Poll family review results.

Parameters:

  • system_id (required)
  • job_id (required)

Returns: Aggregated findings with severity, affected control IDs, and recommended fixes.


Scope Workflow

get_pending_scope_questions

Get only unanswered scope questions (lightweight).

Parameters:

  • system_id (required)
  • framework_id (required)

Returns: List of unanswered questions with IDs.


get_scope_question_detail

Get guidance, tips, and example responses for a specific scope question.

Parameters:

  • system_id (required)
  • question_id (required)
  • framework_id (required)

Returns: Question text, guidance, tips, and example answers.


answer_scope_question

Answer one scope question.

Parameters:

  • system_id (required)
  • question_id (required)
  • answer (required)
  • framework_id (required)

Returns: Updated question state.


trigger_scope_generation

Trigger AI generation of scope document from answered questions. By default the same durable job also runs an AI review after generation.

Parameters:

  • system_id (required)
  • framework_id (required)
  • include_review (optional) — Run AI review after generation in the same job. Default: true

Returns: Generation job ID for polling.


trigger_scope_review

Trigger AI review of scope answers.

Parameters:

  • system_id (required)
  • framework_id (required)

Returns: Review job ID for polling.


get_scope_review_results

Poll for structured scope review findings.

Parameters:

  • system_id (required)
  • job_id (required)

Returns: Findings with severity levels and recommended fixes.


update_scope_narrative

Replace the scope narrative sections for a system+framework. A completed scope is locked — call reopen_scope first (this returns a 422 scope_locked error otherwise). Pass the full ordered list of sections; each is an object with at least title and content.

Parameters:

  • system_id (required)
  • framework_id (required)
  • sections (required) — Full ordered list of narrative sections; each object has title, content, and optional key/order/parent_key.

Returns: Updated scope narrative.


reopen_scope

Reopen a completed scope for editing (regress it to in_progress). Records a monitoring regression event plus audit. Use before update_scope_narrative, answering questions, or regenerating when the scope is completed.

Parameters:

  • system_id (required)
  • framework_id (required)

Returns: Updated scope state.


Policy Workflow

Custom policies are platform-native definitions, never promoted Evidence Locker items. Agents may author and submit them but cannot approve them.

create_custom_policy

Create from an explicit definition (title, purpose, version, ordered stable-ID sections/questions) and optional is_required. Returns the created draft.

get_policy_definition

Read definition state and revision. Use offset/limit for bounded section and question pages; needs_configuration policies cannot enter Q&A or generation.

update_policy_definition

Replace a definition with policy_id, definition, and expected_revision. Set reset_authoring=true only after confirming the platform’s destructive reset.

suggest_policy_definition

Wait for an advisory definition suggestion from human-authored title, purpose, and optional version. It never saves, submits, or approves the result.

get_policy_mappings

Read mappings for policy_id, optionally scoped by framework_id, using offset/limit pagination.

replace_policy_mappings

Atomically replace family_mappings and control_mappings for exactly one framework_id; mappings in other frameworks remain unchanged.

submit_policy_for_review

Submit a ready policy_id for first-party human review. This tool cannot approve.

get_pending_policy_questions

Get only unanswered policy questions.

Parameters:

  • policy_id (required)

Returns: List of unanswered questions.


get_policy_question_detail

Get guidance, tips, and examples for a specific policy question.

Parameters:

  • policy_id (required)
  • question_id (required)

Returns: Question text, guidance, and example answers.


answer_policy_question

Answer one policy question.

Parameters:

  • policy_id (required)
  • question_id (required)
  • answer (required)

Returns: Updated question state.


get_policy_workflow_state

Get per-policy workflow state including completion, generation, and review status.

Parameters:

  • policy_id (required)

Returns: Policy workflow state.


trigger_policy_generation

Trigger AI generation of policy document from answered questions. By default the same durable job also runs an AI review after generation.

Parameters:

  • policy_id (required)
  • system_id (optional) — System ID for scope context
  • include_review (optional) — Run AI review after generation in the same job. Default: true

Returns: Generation job status.


trigger_policy_review

Trigger AI review of policy answers/document.

Parameters:

  • policy_id (required)

Returns: Review job ID for polling.


get_policy_review_results

Poll for structured policy review findings.

Parameters:

  • policy_id (required)
  • job_id (required)

Returns: Findings with severity levels and recommended fixes.


get_policy_narrative

Read an org policy’s generated narrative sections in order — the read counterpart to update_policy_narrative. Use this before a surgical edit: read the current sections, modify or append one, then pass the full list back so no existing section is dropped. Large reads are paginated by default and never return guard-generated content snippets. Use offset/limit to continue, set include_content=false for a compact section index, or pass section_id to fetch one complete section. This returns generated narrative sections, not the Q&A template returned by get_org_policy_questionnaire.

Parameters:

  • policy_id (required)
  • offset (optional, default 0)
  • limit (optional, 1–100, default 10)
  • include_content (optional, default true)
  • section_id (optional; fetch one complete section)

Returns: {policy_id, sections[], pagination}. The pagination object contains offset, limit, returned, total, has_more, and next_offset. When include_content=false, each section contains only section_id, order, and title.


update_policy_narrative

Replace an org policy’s generated narrative sections. An approved policy is locked — call reopen_policy first (this returns a 422 policy_locked error otherwise). Pass the full ordered list of sections; each is an object with section_id, title, and content.

Parameters:

  • policy_id (required)
  • sections (required) — Full ordered list of policy sections; each object has section_id, title, content, and optional order.

Returns: Updated policy narrative.


reopen_policy

Reopen an approved policy for editing (regress it to draft, clearing approval and bumping the version). Records a monitoring regression event plus audit. Use before update_policy_narrative, answering questions, or regenerating when the policy is approved.

Parameters:

  • policy_id (required)

Returns: Updated policy state.


Campaign Operations

Campaigns enable bulk compliance operations with checkpoint persistence and lease-based concurrency.

prepare_campaign

Prepare a workflow-aligned campaign run with a platform state snapshot.

Parameters:

  • domain (required) — controls, policy, or scope
  • mode (required) — Campaign mode for the selected domain
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • family_id (optional) — Target family for control campaigns
  • control_ids (optional) — Explicit control IDs to include
  • all_controls (optional) — Include all controls. Default: false
  • artifacts (optional) — Artifact type: narratives, evidence, or both. Default: both
  • review_job (optional) — Family review job ID for review-fix mode
  • policy_ids (optional) — Explicit policy IDs to include
  • all_incomplete (optional) — Include all incomplete items. Default: false
  • apply (optional) — Apply proposals immediately. Default: false
  • output (optional) — Output format: auto, live, compact, json. Default: json
  • checkpoint_path (optional) — Local checkpoint file path
  • working_directory (optional) — Working directory for executors
  • concurrency (optional) — Parallel execution limit. Default: 4
  • max_retries (optional) — Retry limit per item. Default: 2

Returns: Campaign checkpoint with item list and metadata.


claim_campaign_items

Claim items for drafting with TTL-based leases. Safe for fan-out to multiple agents.

Parameters:

  • checkpoint_path (required) — Local campaign checkpoint path
  • lease_owner (optional) — Stable identifier for the claiming agent
  • max_items (optional) — Number of items to claim. Default: 1
  • lease_ttl_seconds (optional) — Lease time-to-live. Default: 300

Returns: Claimed items with lease metadata.


get_campaign_item_context

Get full item context plus drafting instructions for a claimed item.

Parameters:

  • checkpoint_path (required)
  • item_id (required)

Returns: Control/policy/scope context, current state, and drafting guidance.


submit_campaign_proposal

Submit an external agent’s proposal without applying it to the platform.

Parameters:

  • checkpoint_path (required)
  • item_id (required)
  • proposal (required) — Campaign proposal payload object

Returns: Proposal acceptance confirmation.


apply_campaign

Push stored proposals to the platform.

Parameters:

  • checkpoint_path (required)
  • item_ids (optional) — Subset of item IDs to apply; omit to apply all

Returns: Apply results with per-item status.


get_campaign_status

Get structured campaign status with a stable transcript snapshot.

Parameters:

  • checkpoint_path (required)

Returns: Campaign progress, item states, and transcript.


Risk Management

Risks are system-scoped (except list_risk_library, which is org-level). Mitigation is recorded via update_risk — there is no separate /mitigate endpoint. Control auto-link on create/seed is opt-in: it requires framework_id plus matching ControlImplementation rows on the system.

list_risks

List risks for a system with optional filters.

Parameters:

  • system_id (required)
  • category (optional) — Filter by risk category (confidentiality, integrity, availability, etc.)
  • risk_level (optional) — Filter by overall risk level (critical, high, medium, low)
  • status (optional) — Filter by lifecycle status

Returns: Risk list with summary metadata.


get_risk

Get the full risk detail including eager-loaded artifact_links (controls, evidence, findings, vendors, monitoring events).

Parameters:

  • system_id (required)
  • risk_id (required)

Returns: Full risk record with artifact_links.


create_risk

Create a custom risk for a system. Control auto-link is opt-in: pass framework_id plus suggested_control_families and the platform will only auto-link controls that already have ControlImplementation rows for that framework.

Parameters:

  • system_id (required)
  • title (required)
  • category (required) — confidentiality, integrity, availability, etc.
  • description (optional)
  • cia_category (optional)
  • likelihood (optional)
  • impact (optional)
  • owner_id (optional)
  • treatment (optional) — mitigate, accept, transfer, avoid
  • treatment_plan (optional)
  • treatment_due_date (optional) — ISO date string
  • review_frequency_days (optional) — How often the risk should be re-reviewed
  • framework_id (optional) — Required for control auto-link
  • suggested_control_families (optional) — List of family short codes (e.g., ["AC", "IA"])

Returns: The created risk including artifact_links.


seed_risks

Bulk-instantiate library templates against a system + framework. Each template is scored against the system, and controls are auto-linked per the template’s suggested_control_families when matching ControlImplementation rows exist.

Parameters:

  • system_id (required)
  • framework_id (required)
  • template_ids (required) — Non-empty list of risk template IDs

Returns: Seed summary with the created risks.


update_risk

Update risk fields. This is the mitigation surface — set treatment, treatment_plan, and treatment_due_date here rather than via a separate endpoint. Set status to a terminal value (e.g., closed) to retire a risk; there is no public hard-delete because risks are part of the audit chain.

Parameters:

  • system_id (required)
  • risk_id (required)
  • title (optional)
  • description (optional)
  • category (optional)
  • cia_category (optional)
  • likelihood (optional)
  • impact (optional)
  • owner_id (optional)
  • status (optional)
  • review_frequency_days (optional)
  • treatment (optional) — mitigate, accept, transfer, avoid
  • treatment_plan (optional)
  • treatment_due_date (optional)

Returns: Updated risk record.


Attach an artifact (control, evidence, finding, vendor, or monitoring event) to a risk. Pass exactly one artifact reference.

Parameters:

  • system_id (required)
  • risk_id (required)
  • link_type (required) — contributes_to_risk, mitigates_risk, evidence_of_risk
  • control_id (optional) — Pair with framework_id
  • framework_id (optional) — Required when linking a control
  • evidence_id (optional)
  • finding_id (optional)
  • vendor_id (optional)
  • monitoring_event_id (optional)

Returns: The created artifact link record.


Remove a previously attached artifact link.

Parameters:

  • system_id (required)
  • risk_id (required)
  • link_id (required)

Returns: Removal confirmation.


refresh_risk_summary

Re-score the risk using the latest analytics and trigger a best-effort AI summary regeneration. The endpoint always returns 200 with the updated entry. The score commits regardless of AI availability; the AI summary updates only if the AI service is reachable and the org has quota — check whether ai_summary_generated_at advanced to confirm AI ran.

Parameters:

  • system_id (required)
  • risk_id (required)

Returns: Updated risk entry.


list_risk_library

Browse the org-level risk template library. Templates expose a scenario, category, cia_category, and suggested_control_families.

Parameters:

  • category (optional) — Filter templates by category

Returns: Library template list.


generate_risk_assessment_report

Synchronously generate or idempotently reuse the current Risk Assessment Report (RAR) for the active system/framework. This is a governed write and must follow the risk-assessment workflow selected with start_task(intent_verb="risk_assessment", ...).

Parameters:

  • system_id (required)
  • framework_id (required) — Must match the active framework
  • force_regenerate (optional) — Default false; set only when a new document version is explicitly required

Returns: Current RAR document id, status, generation timestamp, and already_generated replay indicator.


get_risk_assessment_report

Read metadata for the current RAR in the active system/framework scope. This is a proof-only call: it never creates, repairs, or regenerates a document, and it returns not found when no current RAR exists.

Parameters:

  • system_id (required)
  • framework_id (required) — Must match the active framework

Returns: Current RAR id, name, version, status, generation timestamp, completeness, warnings, section count, AI-generated flag, and timestamps.


Formal Assessments and Auditor Portal

Use start_task(intent_verb="formal_assessment", ...) and load the formal-assessment workflow before scheduling or starting an assessment.

list_assessments

List formal assessments for one system with optional type/status filters.

get_assessment

Read one formal assessment, including status and immutable snapshot state.

schedule_assessment

Schedule a formal assessment in the active system/framework scope. This accepts planning facts only; assessment outcomes and final report links cannot be predeclared. Identical engagement requests are atomically deduplicated by the public integration; replay the same call and require the same assessment ID before starting it.

start_assessment

Start a scheduled assessment and initiate its immutable snapshot. Poll get_assessment until the assessment is in_progress and its snapshot is frozen before claiming the read-only Auditor Portal is ready.


System Spec Artifacts

Auditor-required artifacts (asset inventory plus four snapshot kinds) that anchor a system’s audit chain. See System Spec Artifacts for the full schema.

list_artifact_requirements

List the 5 auditor-required system_spec artifact kinds for a system (asset inventory + 4 snapshot kinds). Returns each kind’s effective_required, optional/toggled-off state, attestation timestamp, and rationale.

Parameters:

  • system_id (required)

Returns: Artifact-requirement rows with required/optional state and attestation metadata.


get_asset_inventory

Return the system’s asset inventory. Active rows by default; pass as_of (ISO-8601 timestamp) to replay historical state.

Parameters:

  • system_id (required)
  • as_of (optional) — ISO-8601 timestamp for historical replay

Returns: Asset inventory rows with provenance and snapshot timestamp.


submit_asset_inventory_diff

Submit an asset-inventory diff produced by a recipe-driven scan. At least one of added / modified / decommissioned must be non-empty. recipe_id is a free-form CLI string the platform records as cli:<recipe_id> provenance per row. idempotency_key defaults to sha256(system_id, recipe_id, scan_timestamp); pass your own when replaying a scan. recipe_context_id (from start_recipe) is optional — the diff endpoint accepts it cleanly but does not require it.

Parameters:

  • system_id (required)
  • recipe_id (required) — Free-form CLI recipe id (e.g., asset-inventory-aws-baseline); stored as provenance per row
  • idempotency_key (optional) — Defaults to sha256(system_id, recipe_id, scan_timestamp)[:32]
  • recipe_context_id (optional) — UUID returned by start_recipe when the diff is produced inside an active recipe context
  • added (optional) — Array of new asset rows. Required per row: external_id. Recommended: name, asset_type, environment, data_classification, criticality
  • modified (optional) — Array of changed asset rows keyed by external_id; same shape as added
  • decommissioned (optional) — Array of {external_id, rationale} for assets to mark decommissioned

Returns: Diff acceptance summary with per-row outcomes.


Link an uploaded evidence item as the current snapshot for a system_spec kind, so it surfaces on the scope page. Use after upload_evidence returns an evidence id. kind is one of the snapshot kinds (boundary_diagram, network_dfd, ppsm, interconnection) — call list_artifact_requirements for the authoritative set. The asset inventory is not a snapshot kind (attest it with attest_spec_inventory). Requires an active workflow (call start_task first).

Parameters:

  • system_id (required)
  • kind (required) — Snapshot kind to link the evidence to
  • evidence_id (required) — ID of the uploaded evidence item to link as this kind’s snapshot
  • plan_id (optional) / step_index (optional) — B3 plan attribution

Returns: The updated snapshot-kind state.


attest_spec_snapshot

Attest a system_spec snapshot kind (boundary_diagram, network_dfd, ppsm, interconnection), setting its last_attested_at on the scope page. Typically called right after link_spec_snapshot. Requires an active workflow.

Parameters:

  • system_id (required)
  • kind (required) — Snapshot kind to attest
  • evidence_id (optional) — The linked evidence item being attested
  • sufficiency (optional) — Auditor sufficiency envelope (canonical source, coverage window, producer, verification state)
  • plan_id (optional) / step_index (optional) — B3 plan attribution

Returns: The updated snapshot-kind attestation state.


attest_spec_inventory

Attest the current asset inventory state, setting its last_attested_at on the scope page. Use after submit_asset_inventory_diff has the inventory in the desired state. The inventory is a living kind (rows + attestation), not a file upload — there is no evidence_id. Requires an active workflow.

Parameters:

  • system_id (required)
  • sufficiency (optional) — Auditor sufficiency envelope
  • attestation_name (optional) — Human-readable label for this inventory attestation
  • plan_id (optional) / step_index (optional) — B3 plan attribution

Returns: The inventory attestation result.


Vendor Management

list_vendors

List all vendor entities in the organization. The client fetches every matching page from the paginated public API.

Parameters:

  • search (optional) — Case-insensitive match on name/description
  • provider_type (optional) — csp, saas, managed_service, internal
  • risk_tier (optional) — low, moderate, high, critical
  • owner_user_id (optional)
  • assessment_status (optional) — draft, in_progress, submitted, reviewed
  • lifecycle_status (optional) — onboarding, active, inactive
  • include_inactive (optional) — Include inactive vendors, which are hidden by default. Default: false
  • sort_by (optional) — name, provider_type, inherent_risk, risk_tier, residual_risk_score, next_review_at, last_assessed_at, created_at, document_count. Default: name
  • sort_dir (optional) — asc, desc. Default: asc

Returns: Vendor list with IDs, names, types, authorization levels, inherent risk, residual tier, lifecycle status, reassessment dates, assessment status, document-expiry flags, and document counts when provided by the platform. Inactive vendors are omitted unless include_inactive is set.


create_vendor

Create a new vendor entity.

Parameters:

  • name (required)
  • provider_type (required) — csp, saas, managed_service, internal
  • description (optional)
  • authorization_level (optional)
  • owner_user_id (optional)
  • inherent_risk (optional) — low, moderate, high, critical; medium is a deprecated alias for moderate

Returns: Created vendor record.


get_vendor

Get vendor details.

Parameters:

  • vendor_id (required)

Returns: Vendor metadata and linked documents.


get_vendor_history

Get vendor audit and evidence history.

Parameters:

  • vendor_id (required)
  • limit (optional) — 1..500. Default: 100

Returns: Vendor history events.


get_vendor_dashboard

Get the organization-wide third-party-risk (TPRM) reporting dashboard: posture counts, by_tier / by_provider_type breakdowns, the 5×5 residual likelihood×impact heatmap, and bounded document/contract expiry lists. Organization-wide — requires an org-scoped token with the vendor.pii or admin scope; system-scoped tokens are rejected.

Parameters:

  • horizon_days (optional) — 1..365. Default: 90. Look-ahead window for the expiring-soon KPIs and lists.

Returns: A VendorTprmSummary. Note: per-cell heatmap vendor rosters are omitted to stay within the MCP response-size budget (heatmap_vendors_omitted is set to true); each cell still carries its vendor count. Call list_vendors with a risk_tier filter to enumerate the vendors in a tier.


update_vendor

Update vendor fields.

Parameters:

  • vendor_id (required)
  • name (optional)
  • description (optional)
  • provider_type (optional) — csp, saas, managed_service, internal
  • authorization_level (optional)
  • owner_user_id (optional)
  • inherent_risk (optional) — low, moderate, high, critical; medium is a deprecated alias for moderate

Returns: Updated vendor record.


set_vendor_lifecycle

Transition a vendor to a new lifecycle status. Requires the server-side vendor.pii scope (or an admin token); the platform returns 403 if the token is not authorized.

Parameters:

  • vendor_id (required)
  • target_status (required) — onboarding, active, inactive
  • reason (required) — Non-empty audit reason, max 500 characters

Returns: Updated vendor record with its new lifecycle status.


delete_vendor

Delete a vendor entity.

Parameters:

  • vendor_id (required)

Returns: Deletion confirmation.


upload_vendor_document

Upload vendor evidence documents (SOC 2 reports, CRMs, FedRAMP packages).

Parameters:

  • vendor_id (required)
  • file_path (required)
  • name (optional)
  • description (optional)
  • attestation_type (optional) — self_attested, third_party_attestation, vendor_provided. Default: vendor_provided
  • expires_at (optional) — Document expiry date (ISO-8601, e.g. 2027-01-31)
  • refresh_cadence_days (optional) — Refresh reminder cadence in days (1–365)

Returns: Uploaded document record.


list_vendor_documents

List documents linked to a vendor.

Parameters:

  • vendor_id (required)

Returns: Document list with metadata.


list_vendor_contacts

List a vendor’s contacts. Requires the server-side vendor.pii scope (or an admin token); the platform returns 403 if the token is not authorized.

Parameters:

  • vendor_id (required)

Returns: Contact list.


create_vendor_contact

Add a contact to a vendor. Requires the vendor.pii scope. Setting is_primary auto-demotes the prior primary contact.

Parameters:

  • vendor_id (required)
  • name (required)
  • email (optional)
  • title (optional)
  • phone (optional)
  • is_primary (optional, boolean)
  • notes (optional)

Returns: The created contact.


update_vendor_contact

Update a vendor contact. Requires the vendor.pii scope. Only provided fields are updated.

Parameters:

  • vendor_id (required)
  • contact_id (required)
  • name, email, title, phone, is_primary, notes (all optional)

Returns: The updated contact.


delete_vendor_contact

Delete a vendor contact. Requires the vendor.pii scope.

Parameters:

  • vendor_id (required)
  • contact_id (required)

Returns: Deletion confirmation.


list_vendor_contracts

List a vendor’s contracts, SLAs, and DPAs. Requires the vendor.pii scope. status and is_expired are server-derived, read-only fields.

Parameters:

  • vendor_id (required)

Returns: Contract list including derived status and is_expired.


create_vendor_contract

Add a contract to a vendor. Requires the vendor.pii scope. status and is_expired are server-derived and cannot be set.

Parameters:

  • vendor_id (required)
  • name (required)
  • contract_type (required) — contract, sla, dpa, order_form
  • start_date, end_date, renewal_date (optional, ISO-8601)
  • auto_renew (optional, boolean)
  • notice_period_days (optional, integer)
  • terminated_at (optional, ISO-8601)
  • document_evidence_item_id (optional)
  • notes (optional)

Returns: The created contract.


update_vendor_contract

Update a vendor contract. Requires the vendor.pii scope. Only provided fields are updated. status and is_expired are server-derived and cannot be set.

Parameters:

  • vendor_id (required)
  • contract_id (required)
  • name, contract_type, start_date, end_date, renewal_date, auto_renew, notice_period_days, terminated_at, document_evidence_item_id, notes (all optional)

Returns: The updated contract.


delete_vendor_contract

Delete a vendor contract. Requires the vendor.pii scope.

Parameters:

  • vendor_id (required)
  • contract_id (required)

Returns: Deletion confirmation.


list_vendor_systems

List the systems a vendor serves.

Parameters:

  • vendor_id (required)

Returns: List of attached systems with total.


attach_vendor_systems

Attach one or more systems to a vendor (SR-5 / SA-9 system-of-record mapping).

Parameters:

  • vendor_id (required)
  • system_ids (required) — array of system IDs (at least one)

Returns: Attachment result.


detach_vendor_system

Detach a system from a vendor.

Parameters:

  • vendor_id (required)
  • system_id (required)

Returns: Detachment confirmation.


sign_vendor_residual_acceptance

Sign authorizing-official acceptance of a vendor’s residual risk for one attached system. Idempotent per (vendor, system). Requires the org’s evidence attestation-envelope capability and attestation process mode; when signing is disabled the tool returns a clear, actionable error.

Parameters:

  • vendor_id (required)
  • system_id (required) — attached system ID to accept residual risk for
  • note (optional) — justification/note for the acceptance

Returns: The signed residual-acceptance result.


Link an evidence item to a vendor with attestation type. Set vendor_id to null to unlink.

Parameters:

  • evidence_id (required)
  • vendor_id (optional) — Vendor ID; null to unlink
  • attestation_type (optional) — self_attested, third_party_attestation, vendor_provided

Returns: Link confirmation.


list_vendor_assessment_templates

List vendor assessment templates available to the organization.

Parameters: None.

Returns: Template summaries including kind, source format, section count, and question count.


get_vendor_assessment_template

Get a vendor assessment template with its full section and question specs.

Parameters:

  • template_id (required)

Returns: Template detail, including sections, questions, and in_flight_assessment_count.


import_vendor_assessment_template

Import a SIG-Lite or CAIQ-Lite xlsx workbook as an org-scoped vendor assessment template. The default dry-run returns a preview. To persist the template, pass dry_run=false and acknowledge_license_rights=true.

Parameters:

  • file_path (required) — Local .xlsx workbook path
  • source_format (required) — sig_lite, caiq_lite
  • dry_run (optional) — Default: true
  • acknowledge_license_rights (optional) — Required when dry_run=false

Returns: Import preview on dry-run, or created template summary when persisted.


delete_vendor_assessment_template

Delete an org-scoped custom or imported vendor assessment template. Global seed templates cannot be deleted.

Parameters:

  • template_id (required)

Returns: Deletion confirmation.


launch_vendor_assessment

Launch an assessment against a vendor, freezing the selected template snapshot.

Parameters:

  • vendor_id (required)
  • template_id (required)

Returns: Assessment summary.


list_vendor_assessments

List assessments run against a vendor.

Parameters:

  • vendor_id (required)

Returns: Assessment summaries.


get_vendor_assessment

Get an assessment with its frozen template snapshot, responses, and any advisory AI summary.

Parameters:

  • vendor_id (required)
  • assessment_id (required)

Returns: Assessment detail.


save_vendor_assessment_responses

Upsert assessment answers. The first answer moves a draft assessment to in_progress.

Parameters:

  • vendor_id (required)
  • assessment_id (required)
  • answers (required) — List of answer objects with question_ref; optional fields are answer, comment, and evidence_item_id

Returns: Updated assessment detail.


submit_vendor_assessment

Move an in-progress vendor assessment to submitted.

Parameters:

  • vendor_id (required)
  • assessment_id (required)

Returns: Assessment summary.


score_vendor_assessment

Run advisory AI scoring over a submitted assessment. If scoring is unavailable, the platform records that state and review can still proceed through the acknowledgement gate.

Parameters:

  • vendor_id (required)
  • assessment_id (required)

Returns: Assessment detail.


review_vendor_assessment

Finalize an assessment by setting residual likelihood and impact. Values use the five-point NIST 800-30 scale: very_low, low, moderate, high, very_high.

Parameters:

  • vendor_id (required)
  • assessment_id (required)
  • residual_likelihood (required) — very_low, low, moderate, high, very_high
  • residual_impact (required) — very_low, low, moderate, high, very_high
  • acknowledge_no_ai_review (optional) — Required to finalize when no successful AI advisory summary exists

Returns: Reviewed assessment summary.


Inheritance & Responsibility

set_control_responsibility

Create or update an inheritance edge for a control.

Parameters:

  • system_id (required)
  • control_id (required)
  • framework_id (required)
  • responsibility_mode (required) — inherited or shared
  • source_type (optional) — provider for a vendor entry on the Pretorin vendor portal, or org_system for an org-internal system
  • vendor_id (conditional) — Vendor provider id from the vendor portal. Required when source_type is provider
  • source_system_id (conditional) — Source org-internal system id. Required when source_type is org_system
  • source_control_id (optional) — Control id on the source side. Defaults to the target control_id, which fits the common vendor-inheritance case where the source covers the same control concept

Returns: Created responsibility edge.


get_control_responsibility

Check if a control is inherited and from where.

Parameters:

  • system_id (required)
  • control_id (required)
  • framework_id (required)

Returns: Responsibility edge details or null.


remove_control_responsibility

Convert an inherited control back to system-specific.

Parameters:

  • system_id (required)
  • control_id (required)
  • framework_id (required)

Returns: Removal confirmation.


generate_inheritance_narrative

AI-generate an inheritance narrative grounded in vendor documentation.

Parameters:

  • system_id (required)
  • control_id (required)
  • framework_id (required)

Returns: Draft inheritance narrative text.


get_stale_edges

Identify controls where the source narrative changed but the inherited control hasn’t been updated.

Parameters:

  • system_id (required)

Returns: List of stale inheritance edges with source change timestamps.


sync_stale_edges

Bulk update inherited controls by regenerating narratives from latest source.

Parameters:

  • system_id (required)

Returns: Sync results with per-control status.


STIG & CCI

list_stigs

List STIG benchmarks with optional filters.

Parameters:

  • technology_area (optional) — Filter by technology area
  • product (optional) — Filter by product name
  • limit (optional) — Default: 100
  • offset (optional) — Pagination offset. Default: 0

Returns: STIG benchmark list with IDs, titles, and rule counts.


get_stig

Get STIG benchmark detail.

Parameters:

  • stig_id (required)

Returns: Benchmark metadata including title, version, release info, and severity breakdown.


list_stig_rules

List rules for a STIG benchmark.

Parameters:

  • stig_id (required)
  • severity (optional) — Filter by severity (high, medium, low)
  • cci_id (optional) — Filter by CCI identifier
  • limit (optional) — Default: 100
  • offset (optional) — Pagination offset. Default: 0

Returns: Rule list with IDs, titles, severities, and linked CCIs.


get_stig_rule

Get full STIG rule detail.

Parameters:

  • stig_id (required)
  • rule_id (required)

Returns: Check text, fix text, discussion, and linked CCIs.


list_ccis

List CCIs with optional filters.

Parameters:

  • nist_control_id (optional) — Filter by NIST 800-53 control ID (e.g., AC-2)
  • status (optional)
  • limit (optional) — Default: 100
  • offset (optional) — Pagination offset. Default: 0

Returns: CCI list with definitions and linked controls.


get_cci

Get CCI detail with linked SRGs and STIG rules.

Parameters:

  • cci_id (required) — e.g., CCI-000015

Returns: CCI definition, linked SRGs, and linked STIG rules.


get_cci_chain

Get the full traceability chain: Control -> CCIs -> SRGs -> STIG rules.

Parameters:

  • nist_control_id (required) — NIST 800-53 control ID (e.g., AC-2)

Returns: Complete traceability from control requirements to technical checks.


get_cci_status

Get CCI-level compliance rollup for a system.

Parameters:

  • system_id (required)
  • nist_control_id (optional) — Filter by NIST control ID (e.g., AC-2)

Returns: Per-CCI pass/fail status.


get_cci_implementation_summary

Get the bounded CCI implementation authoring and approval posture for one active system/framework. This is distinct from get_cci_status, which reports STIG scan results.

Parameters:

  • system_id (required)
  • framework_id (optional) — Defaults to the active MCP framework and must match the active context when supplied.

Returns: In-scope initialized CCI implementation total, approved, unapproved, and effective status_counts, excluding deprecated catalog CCIs and archived implementations.


get_cci_implementation

Read a single per-system CCI implementation row by (system_id, cci_uuid). Returns the live impl detail (status, status_source, narrative, ai_generated_narrative, evidence_ids, eMASS fields, has_status_conflict). 404 means the row hasn’t been initialized for this system yet.

Parameters:

  • system_id (required)
  • cci_uuid (required) — The CCI catalog UUID (the unique catalog row id, not the CCI-000XXX label)

Returns: Full CCI implementation detail.


get_stig_applicability

Get which STIGs apply to a system based on its profile.

Parameters:

  • system_id (required)

Returns: List of applicable STIG benchmarks.


infer_stigs

AI-infer applicable STIGs from the system’s profile.

Parameters:

  • system_id (required)

Returns: Recommended STIG benchmarks with reasoning.


get_test_manifest

Fetch the test manifest (applicable STIGs + rules) for a system.

Parameters:

  • system_id (required)
  • stig_id (optional) — Scope manifest to a specific STIG benchmark
  • rule_id (optional) — Exact DISA rule ID or internal rule UUID
  • mode (optional) — full (default) or summary
  • limit / offset (optional) — Bounded rule pagination; summary defaults to 25 rules

Returns: Test manifest with applicable rules and scanner assignments plus response_metadata containing filters, page counts, has_more, next_offset, and an explicit truncated flag. Use stig_id + rule_id in full mode for one complete scanner definition; use summary mode to omit check/fix bodies while browsing.


submit_test_results

Upload STIG scan results to the platform.

Parameters:

  • system_id (required)
  • cli_run_id (required) — CLI scan run identifier
  • results (required) — Array of test result objects
  • cli_version (optional) — CLI version string

Returns: Submission confirmation with per-result status.


list_stig_checklists

List STIG checklists for a system (per-asset: benchmark, asset identity, title). Use to discover an existing checklist_id before export/import, or to confirm one exists for a (benchmark, asset) pair before creating a new one.

Parameters:

  • system_id (required)
  • inventory_item_id (optional) — Filter to one asset’s checklists by inventory item ID
  • limit (optional) — Max results per page (1–500). Default: 100
  • offset (optional) — Pagination offset. Default: 0

Returns: Checklist summaries (benchmark, asset identity, title, id).


create_stig_checklist

Create an asset-scoped STIG checklist bound to a benchmark + asset. Returns the new checklist summary (including its id). Fails if one already exists for that (benchmark, asset), or if the benchmark/asset is unknown. Create-or-resolve a checklist this way before importing scanner output.

Parameters:

  • system_id (required)
  • stig_benchmark_id (required) — STIG benchmark ID to bind (e.g. RHEL_9_STIG)
  • inventory_item_id (required) — Asset inventory item ID to bind the checklist to
  • title (optional) — Checklist title

Returns: The new checklist summary including its id.


export_stig_checklist

Export a checklist to a local file as DISA .ckl (XML) or .cklb (JSON). Regenerated on demand (air-gap/FIPS-safe; no eMASS connector needed). Writes to output_path and returns {path, format, size_bytes, sha256} — the raw file is written to disk, not inlined in the response. Refuses an existing output_path unless overwrite=true, and never writes through a symlink.

Parameters:

  • system_id (required)
  • checklist_id (required) — Checklist ID to export
  • output_path (required) — Local path to write the exported checklist file
  • format (optional) — ckl (XML) or cklb (JSON). Default: ckl
  • overwrite (optional) — Replace output_path if it already exists. Default: false

Returns: {path, format, size_bytes, sha256} for the written file.


import_stig_checklist

Import a .ckl/.cklb file into a checklist’s per-rule reviews (review axis). Full-fidelity complement to submit_test_results: ingests asset metadata, the four DISA statuses, finding details/comments, and severity override, reconciled against the benchmark. A non-reconciling import (rules dropped) returns an error result — never treat it as complete. Writes are refused outside the active context system.

Parameters:

  • system_id (required)
  • checklist_id (required) — Target checklist ID (must already exist)
  • file_path (required) — Local path to the .ckl (XML) or .cklb (JSON) file
  • format (optional) — auto, ckl, or cklb. Default: auto

Returns: Match/import counters, a reconciles flag, and capped rule-id buckets (full per-rule detail via the CLI).


import_stig_checklist_xccdf

Import an XCCDF scan document (SCAP/OpenSCAP results) into the system test axis. Separate from import_stig_checklist (the .ckl/.cklb review axis). The test axis is system-scoped, so the response reports how many checklists on the system the scan affects. Use this to push a scanner recipe’s XCCDF results so they derive DISA statuses across all checklists bound to the same benchmark.

Parameters:

  • system_id (required)
  • checklist_id (required) — A checklist ID on the target system
  • file_path (required) — Local path to the XCCDF results document

Returns: Import summary reporting how many checklists on the system the scan affects.


Recipes & Workflows

Recipes are markdown playbooks the calling agent reads and executes; workflows describe how to iterate items in a domain and which recipes to pick per item. See RFC 0001 for the contract spec and docs/src/recipes/ for authoring guides.

list_recipes

List loaded recipes with their summary metadata (id, name, tier, description, use_when, produces). Deprecated compatibility recipes are hidden by default. When system_id is supplied, recipes missing required connected sources are hidden by default. Use this to discover which recipes are available, then call get_recipe(id) to read the full body.

Parameters:

  • tier (optional) — Filter to one tier: official, partner, or community
  • produces (optional) — Filter by what the recipe produces: evidence, narrative, both, answers, or issues (notes is a legacy compatibility value)
  • system_id (optional) — Filter to recipes runnable against the system’s connected sources; also annotates each recipe with an active flag (membership in the scope’s active set)
  • include_unavailable (optional) — Include recipes missing required sources with unavailable reasons. Default: false
  • include_deprecated (optional) — Include deprecated compatibility recipes and their replacements. Default: false
  • active_only (optional) — When system_id is supplied, return only the scope’s active recipe set. On an unprovisioned or missing scope this returns an empty recipe list, not the whole cookbook. Default: false

Returns: Recipe summaries with manifest metadata, required sources, per-recipe source availability, and an active flag when a system scope is supplied.


get_recipe

Return one recipe’s full manifest and body. The body is the markdown playbook the calling agent reads to understand the procedure.

Parameters:

  • recipe_id (required) — Recipe id to fetch

Returns: Recipe manifest plus the markdown body.


check_sources

Preflight source reachability and candidate recipes for one workflow/control. Use after start_task and before opening recipe contexts when the agent needs fresh source/recipe detail.

Parameters:

  • workflow_id (required) — Workflow id returned by start_task
  • control_id (required)
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • include_source_hints (optional) — Return full per-expectation source_hints instead of compact hint summaries. Default: false

Returns: Compact capture-plan items with source kind, connected state, candidate recipes, selected recipe, and structured recipe_gap entries. On a provisioned scope, candidates are drawn from the active recipe set and each recipe_gap carries ready_source_kinds and ready_alternative_recipe_ids so an unmatched hint points at substitutes instead of a dead-end. Full source_hints are opt-in via include_source_hints=true.


get_active_recipes

Read the scope’s active recipe set — the curated subset of the cookbook provisioned for this (system, framework) compliance effort — plus a provisioning proposal. Call this during preflight (workflow Step 7) to seed the set, and whenever deciding what to run.

Parameters:

  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope

Returns: active (the provisioned recipes), candidates (recipes runnable on this host, each with serves_kinds), coverage_gaps (ready source kinds no recipe consumes), and drift (active recipes whose pinned version/content/source has moved or left the cookbook). Returns provisioned: false / exists: false when the scope has no preflight artifact yet.


set_active_recipes

Edit the scope’s active recipe set and persist it on the preflight artifact. Seed it from get_active_recipes candidates during preflight, then adjust as the effort evolves. Establishing an active set makes it the confirmed menu: start_recipe then refuses recipes outside it (unless force=true), and the capture plan draws candidates from it.

Parameters:

  • recipe_ids (required) — Recipe ids to set/add/remove (may be empty only for mode='replace')
  • mode (optional) — replace (default, set the active set to exactly recipe_ids), add, or remove
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope

With mode='add', an already-active recipe whose version and loader source are unchanged but whose reviewed content digest moved is re-pinned. Version and loader-source drift require an explicit remove followed by add after review.

Returns: The activated/deactivated/unchanged ids, repinned records with old and new content hashes, any unknown_recipe_ids skipped (not in the cookbook), and the resulting active set.


start_recipe

Open a recipe execution context. Returns a context_id the caller passes as recipe_context_id on subsequent platform-API write tool calls and to end_recipe so audit metadata is stamped with producer_kind='recipe' automatically. One recipe per session at a time (nesting forbidden in v1). Contexts auto-expire after 1 hour of inactivity. On a provisioned scope, start_recipe refuses recipes outside the active set and active recipes whose pinned version/content/source has drifted; pass force=true only for an audited ad-hoc run.

Parameters:

  • recipe_id (required) — Recipe id (must be loadable from the registry)
  • recipe_version (required) — Recipe version the caller intends to run. Read this from get_recipe(recipe_id).manifest.version (or the version field returned by list_recipes) before calling — hard-coded values will break when the recipe registry advances. Cross-checked against the loaded recipe; mismatch is an error.
  • params (optional) — Inputs the calling agent supplies, validated against the recipe’s params schema
  • selection (optional) — Structured RecipeSelection record from the engagement layer, stored on the context for the eventual RecipeResult
  • evidence_ids (optional) — Evidence ids supplied as inputs for narrative-producing recipes
  • system_id (optional) — Defaults to active scope
  • framework_id (optional) — Defaults to active scope
  • control_id (optional) — Control context for the recipe run
  • force (optional) — Open the context ad hoc when preflight source availability, active-set membership, or active recipe drift would otherwise refuse the run. Forced runs are recorded on the execution record.

Returns: Context id and the resolved recipe manifest snapshot.


end_recipe

Close a recipe execution context and return the RecipeResult summary (status, evidence and narrative counts, errors, elapsed time). Must be called once the recipe’s work is complete; failure to call leaves the context in place until the 1-hour expiry sweep.

Parameters:

  • recipe_context_id (required unless using the deprecated alias) — Context id returned by start_recipe; use this canonical name to match update_narrative, add_control_issue, and resolve_control_issue
  • context_id (optional, deprecated) — Legacy alias accepted for backwards compatibility. Prefer recipe_context_id.
  • status (optional) — Caller-supplied disposition: pass, fail, or needs_input. Default: pass

Returns: RecipeResult summary.


list_workflows

List loaded workflow playbooks (single-control, scope-question, scope-artifacts, policy-question, campaign, preflight, stig-scan-remediation, risk-assessment, formal-assessment). Each workflow describes how to iterate items in its domain and which recipes to pick per item. Use this before picking a recipe so the agent works at the right granularity.

Parameters:

  • iterates_over (optional) — Filter to one item-iteration shape: single_control, scope_questions, policy_questions, campaign_items, system_spec_kinds, source_kinds, stig_rules, system_risks, or assessments

Returns: Workflow summaries with manifest metadata.


get_workflow

Return one workflow’s manifest, Markdown instructions, and referenced tool schemas.

Parameters:

  • workflow_id (required) — Workflow id to fetch
  • mode (optional) — full (default) or validation-equivalent compact
  • section (optional) — Heading title/id from response_metadata.available_sections

Returns: Workflow manifest, the complete requested body/slice, referenced tool schemas, and explicit response-selection/truncation metadata.


Work Plans

Agent-authored work plans are the local execution contract for one exact (system_id, framework_id) context. Implemented fields include scope, intent, typed steps, acceptance criteria, produced artifacts, structural version, and append-only structural snapshots. expected_outputs, deviations, and evaluator_results are proposals in the draft RFC; they are not persisted by the current schema. Plans live under ~/.pretorin/plans/<id>.json.

create_plan

Persist an agent-authored work plan locally. Returns the full plan record including the generated plan id.

A plan must declare what it intends to do before it can carry writes. Omitting steps creates the plan in the draft state, and writes attributed to a draft plan are refused — call activate_plan with an ordered step list first. Supplying steps up front creates the plan active directly.

Parameters:

  • workflow_id (required) — Workflow id this plan executes (e.g. single-control)
  • intent_summary (required) — One-paragraph statement of what the agent intends to do and why; used by future sessions to decide whether to resume or replace
  • scope (optional) — Object with system_id, framework_id, and control_id this plan operates on
  • intent_inputs_snapshot (optional) — Free-form snapshot of the inputs that shaped the plan (user prompt, active scope, etc.) so the audit trail captures the why
  • steps (optional) — Ordered list of intended steps; each has index (contiguous from 0), summary, kind (recipe, policy_link, issue, note, or other), and optional ref_id. Every step is created pending — a step supplied in any other status is rejected, since creation declares intent and cannot back-date progress. Omit to create a draft that must be activated before use
  • created_by_agent (optional) — Identifier for the agent creating the plan (e.g. claude-code-1.2.3)
  • acceptance_criteria (optional) — Typed conditions the platform must verify before complete_plan succeeds (max 32). Empty/omitted leaves the gate open. Each criterion has a kind (narrative_min_chars, every_claim_cites_evidence, ai_narrative_reviewed, min_evidence_count_per_control, or all_required_spec_kinds_attested) and kind-specific params

Returns: The full plan record, including the generated plan id and its state (draft or active).


activate_plan

Declare the ordered execution steps for a draft plan and transition it to active.

start_task creates a scope-pinned draft for routed work — it knows the scope before the agent knows the implementation steps. Activation is where the agent states what it will actually do. Until it succeeds, the plan refuses step updates, completion, and any platform write carrying its plan_id.

For single-control, the draft already contains the workflow-required evidence-expectation-mapping step. Activation preserves it and, when the agent declares a narrative step with ref_id: evidence-narrative-compose, places mapping after evidence work and immediately before narrative work. Read the returned plan before sending attributed writes because those are the final step indices.

Parameters:

  • plan_id (required) — UUID-shaped id of the draft plan (from start_task or create_plan)
  • steps (required) — Ordered list, at least one entry. Each has index (contiguous from 0), summary, kind (recipe, policy_link, issue, note, or other), and optional ref_id, recipe_version, params. Every step must be pending — activation declares intent, it cannot back-date progress
  • acceptance_criteria (optional) — Additional completion-gate criteria, added on top of any the workflow seeded into the draft. The workflow owns its Definition of Done, so seeded criteria always survive activation and cannot be removed; an entry whose kind is already seeded is ignored rather than overriding it. Omit (or send []) to keep only the seeded criteria. The 32-criteria cap applies to the merged total
  • expected_version (optional) — Optimistic-locking guard: the draft’s version as the caller last read it. Activation increments version, so a second caller holding the pre-activation number is told its view is stale
  • actor (optional) — Agent identifier recorded on the initial structural snapshot
  • reason (optional) — Why this execution contract is being activated

Returns: The activated plan record, with state: "active" and activated_at set.

Errors: Refused if the plan is neither a draft nor an adoptable legacy record (see below), if steps is empty, if step indices aren’t contiguous from zero, or if any step is not pending.

Legacy records: Also accepts a plan that is already active but declares no steps and was never activated — the shape start_task produced before the draft state existed. Completion requires at least one declared step, so supplying the steps here is the only route to completed for such a record; without it the plan could only be cancelled, stamping delivered work as “stopped early”. The same step rules apply, so the plan rejoins the normal contract rather than bypassing it.


mutate_plan_structure

Add, remove, or replace pending steps, or replace acceptance criteria. Every call requires expected_version, actor, and reason; success increments Plan.version and appends an immutable post-change snapshot. Runtime progress and artifact recording do not increment the structural version. Workflow-owned steps retain their required ordering, and acceptance-criteria replacement only replaces caller-added criteria: workflow-required Definition-of-Done criteria cannot be removed or weakened (an empty replacement clears only optional criteria).

Parameters:

  • plan_id (required)
  • operation (required) — One of add_step, remove_step, replace_step, replace_acceptance_criteria
  • expected_version (required) — Current Plan.version; a mismatch is rejected rather than applied
  • actor (required) — Who is making the structural change (1–200 chars)
  • reason (required) — Why (1–2000 chars); recorded in the immutable snapshot
  • step_index (required for remove_step and replace_step) — Zero-based index
  • step (required for add_step and replace_step) — Object with index, summary, and kind (recipe, policy_link, issue, note, other) required, plus optional ref_id, recipe_version, params
  • acceptance_criteria (required for replace_acceptance_criteria) — Up to 32 objects with a required kind (narrative_min_chars, every_claim_cites_evidence, ai_narrative_reviewed, min_evidence_count_per_control, all_required_spec_kinds_attested) and optional params

Returns: The updated plan with an incremented version.


get_plan

Return the full record of a previously-created plan. Use when resuming work from a prior session or auditing what was intended.

Parameters:

  • plan_id (required) — UUID-shaped plan id returned by create_plan

Returns: The full plan record.


list_recent_plans

List recent plans (newest first), with optional filtering by state, workflow, and scope. Returns compact summaries — call get_plan for the full record once a plan is selected. Use this at session start to find an existing plan to resume instead of creating a duplicate.

Parameters:

  • limit (optional) — Maximum number of plans to return (0–200, default 20)
  • state (optional) — Restrict results to draft, active, completed, or cancelled
  • workflow_id (optional) — Filter by workflow id
  • system_id (optional) — Filter by system id
  • framework_id (optional) — Filter by framework id (e.g. fedramp-moderate)
  • control_id (optional) — Filter by control id

Returns: Compact plan summaries, newest first.


update_plan_step

Update one step’s status and/or outcome summary. Status transitions are guarded: pendingin_progress | skipped; in_progresscompleted | skipped; terminal states are sticky. Skipping requires an explicit outcome_summary.

Workflow-required steps cannot be skipped. The single-control mapping step also cannot be completed without evidence_mapping, a typed read-back record from get_control_context after all links are written.

Parameters:

  • plan_id (required)
  • step_index (required) — Index of the step to update
  • status (optional) — New status: pending, in_progress, completed, or skipped
  • outcome_summary (optional) — Short note about what the step actually produced. Required and non-empty when status is skipped. May also be supplied alone to fill in a missing reason on an already-skipped step whose reason is blank; an existing reason cannot be overwritten
  • evidence_mapping (conditional) — Required when completing evidence-expectation-mapping. Contains active_tier, all declared expectation_keys, bindings (expectation key → evidence-id list), intentionally_unbound (evidence_id + reason), post-link covered and uncovered key lists, and unbound_evidence_count. Every declared key must be classified; bound and intentionally unbound evidence cannot overlap.
  • expected_version (optional) — Optimistic-locking guard. If supplied, the call returns a structured version_conflict error when the plan’s on-disk version no longer matches

Returns: The updated plan record.


complete_plan

Mark a plan as completed. The Plan must be active, contain at least one step, and have every step completed or explicitly skipped with a reason. Structural gaps return plan_incomplete before acceptance evaluation. Failing typed criteria return acceptance_failed; the Plan stays active in both cases.

Parameters:

  • plan_id (required)
  • outcome_summary (optional) — One-paragraph summary of what the plan ultimately produced
  • expected_version (optional) — Optimistic-locking guard. If supplied, the call returns a structured version_conflict error when the plan’s on-disk version no longer matches

Returns: The updated plan record.


cancel_plan

Mark a plan as cancelled. Allowed only from active. Idempotent: cancelling an already-cancelled plan is a no-op. Cannot cancel a completed plan.

Parameters:

  • plan_id (required)
  • outcome_summary (optional) — Reason for cancellation
  • expected_version (optional) — Optimistic-locking guard. If supplied, the call returns a structured version_conflict error when the plan’s on-disk version no longer matches

Returns: The updated plan record.