world-model-mcp

pin_annotation

Attach signed human annotations—notes, override justifications, or intervention records—to event spans, persisting them into the audit-logged annotations table.

Instructions

Attach a signed human annotation (note, override rationale, or intervention record) to a span of agent events. Persists into the annotations table and chains into the same Merkle audit log as agent writes (v0.15.0, ADR-0001). Rationale limited to 8 KB.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "session_id": "<session_id>",
      "event_range_start": "<event_range_start>",
      "event_range_end": "<event_range_end>",
      "author": "<author>",
      "rationale": "<rationale>",
      "annotation_type": "<annotation_type>"
    },
    "name": "pin_annotation"
  }
}

Input Schema

Name	Required	Description
`author`	Yes	Author identity. Self-asserted in OSS; KMS-verified in Etch hosted.
`rationale`	Yes	Human rationale text (UTF-8). Max 8192 bytes.
`session_id`	Yes	Session containing the annotated events.
`annotation_type`	Yes
`event_range_end`	Yes	Last event_id in the annotated span. Equals event_range_start for a single-event annotation.
`event_range_start`	Yes	First event_id in the annotated span.

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.15.5Jul 25, 2026

TDQS

A4.2/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and exceeds expectations by disclosing persistence ('Persists into the annotations table'), audit integration ('chains into the same Merkle audit log as agent writes'), version/ADR references, and the rationale size limit. This gives the agent a clear behavioral model.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core action, and includes only essential extra context (persistence, audit log, limit). Every sentence earns its place with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 required parameters, no output schema, and no annotations, the description provides solid context for a write operation: it explains persistence and audit chaining. It lacks explicit error handling or return behavior, but that is not critical for a basic mutation tool. The description is largely complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 83% coverage (5 of 6 parameters have descriptions), so the baseline is 3. The description adds little beyond the schema; it mentions the 8 KB rationale limit (already in schema) and does not elaborate on parameter meanings or relationships. The schema itself is well-documented, so a baseline score is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action ('Attach') and object ('a signed human annotation to a span of agent events'). It distinguishes from siblings like record_event by emphasizing human annotation vs agent events and mentions specific annotation types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the use case of attaching human notes or overrides to event spans, but provides no explicit guidance on when to choose this tool over alternatives such as record_correction or record_decision. The context is clear but lacks exclusions or alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.