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mind_recall

Recall error-to-fix playbooks for an error signature or task context, ranking by relevance and trust so verified fixes rank higher and failing fixes are demoted.

Instructions

Recall error->fix playbooks for an error and/or a task context. Ranking blends relevance with trust: a verified or proven fix gets a boost, a repeatedly-failing one is demoted, but a strongly-matching unverified fix still surfaces.

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": "mind_recall"
  }
}

Input Schema

NameRequiredDescriptionDefault
errorNoError signature to match (lexical)
limitNoMax playbooks
contextNoTask description to match (semantic)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does disclose the non-obvious ranking logic: verified/proven fixes are boosted, repeatedly-failing ones demoted, and strongly-matching unverified ones still surface. That materially helps an agent interpret and trust ordering. It still omits read-only status and the shape of a returned 'playbook'.

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 sentences, purpose front-loaded before the ranking detail, with no filler. The second sentence is slightly dense but every clause describes a distinct ranking behavior that earns its place.

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

Completeness3/5

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

For a 3-parameter recall tool with no output schema and no annotations, the description explains purpose and ranking but never describes what a returned playbook contains or the response shape. Adequate but with a clear gap given structured data cannot fill it.

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 error (lexical), context (semantic), and limit (default 3) are already fully documented. The description adds the 'and/or' combinatorics — that either or both matching inputs may be supplied — but little else beyond what the schema provides, so the baseline 3 holds.

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 and resource ('Recall error->fix playbooks') with additional scope ('for an error and/or a task context'). An agent can tell what the tool returns without opening the schema. It does not, however, explicitly distinguish itself from the sibling mind_recall_all, which is the natural alternative an agent would weigh.

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 phrase 'for an error and/or a task context' implies the situation in which to reach for it, but there is no explicit when-to-use, when-not-to-use, or named alternative (e.g. mind_recall_all, mind_search). Usage is inferable rather than stated.

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