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ai-dememory

ai-dememory

by GonzaloTorreras
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Capture Git Lesson Candidates

memory.git_lessons

Generate review-first lesson candidates by inspecting local git history. Preview candidates in dry-run mode, or write them to inbox/git-lessons/ when dry-run is disabled.

Instructions

Inspect local git history and preview review-first lesson candidates; dry_run=false writes into inbox/git-lessons/.

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": "memory.git_lessons"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNo
repoNo
limitNo
reposNo
dry_runNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations indicate readOnlyHint=false, and the description adds critical context: dry_run defaults to true (preview only), and setting dry_run=false writes to inbox/git-lessons/. This clarifies the write behavior beyond annotations. However, no details on performance or side effects.

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?

The description is a single sentence that efficiently conveys the core purpose and key behavior (dry_run). It is front-loaded and concise, though it could add more parameter info without becoming verbose.

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?

With 5 parameters, an output schema, and annotations, the description covers the main objective and critical behavior but omits explanations for most parameters. For a tool of moderate complexity, it is somewhat incomplete.

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

Parameters2/5

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

Schema description coverage is 0%, yet the description only explains the dry_run parameter. Parameters like days, repo, limit, and repos are not described, leaving the agent to infer from names. The description does not compensate for the lack of schema documentation.

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 inspects local git history and previews/reviews lesson candidates, with a verb ('inspect') and resource ('git history' and 'lesson candidates'). It distinguishes from siblings like review tools by specifically focusing on git lessons capture.

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 usage for capturing git lesson candidates but does not provide explicit guidance on when to use this tool versus alternatives like memory.recall_miss_candidate or memory.review_recommendation. No context on prerequisites or when not to use it.

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

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