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complete_activation_retrieval_proof

Read-onlyIdempotent

Complete a pending guided-activation retrieval challenge with exact task, topic, project, repo path, and challenge ID; the server verifies the published decision, not user-authored recall JSON.

Instructions

Complete a pending guided-activation retrieval challenge from this exact managed MCP surface. The server reads and attests the published decision; user-authored recall/read JSON is never accepted.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "complete_activation_retrieval_proof"
  }
}

Input Schema

Name	Required	Description
`query`	No	Exact activation task text
`topic`	No	Exact activation topic
`project`	No	Exact activation project
`callerCwd`	No	Absolute repository path from the activation request
`challengeId`	No	Opaque challenge ID emitted by threadnote activate

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 5, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive). The description adds real context beyond them: the server 'reads and attests the published decision' and rejects user-authored input, which tells the agent the proof is server-verified. It still omits what a completed vs rejected challenge returns.

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

Conciseness4/5

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

Two tightly written sentences with the action front-loaded and the constraint following. No filler, though the phrasing is dense and slightly jargon-heavy.

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?

No output schema exists, but the description explains the server-side attestation mechanism, which is the key behavioral fact for calling a proof tool. Combined with full schema coverage and annotations, most of what an agent needs is present, though return behavior on failure is unstated.

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?

Schema description coverage is 100%, so the schema already documents all five parameters and the baseline is 3. The description's emphasis on 'this exact managed MCP surface' reinforces the exact-match expectation but adds no field-level syntax beyond the schema.

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

Purpose4/5

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

States a specific verb ('Complete') and resource ('pending guided-activation retrieval challenge'), making it distinguishable from recall/read siblings. It does not name an alternative tool directly, but the object of the action is concrete enough for an agent to identify the operation.

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?

Usage is implied ('pending' challenge) rather than explicitly conditional, and there is no explicit when-not or named alternative. The line 'user-authored recall/read JSON is never accepted' weakly separates it from recall_context, but routing guidance is left to inference.

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