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jbouder

agent-docs-mcp

by jbouder

read_agent_docs

Retrieve coding guidelines and docs from configured Git repositories to understand codebase conventions, architecture decisions, and implementation patterns before making changes.

Instructions

Read agent documentation and coding guidelines from configured repositories. Use this when you need context about how to work with a codebase, understand coding patterns, architecture decisions, or get implementation guidelines. The documentation provides best practices, conventions, and important context for making code changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repositoryNoOptional: specific repository URL or name to get docs from. If not provided, returns all configured docs.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. The verb 'Read' implies a non-mutating operation, and the description clarifies the source ('configured repositories') and the kind of content returned. It does not disclose output format, potential size limits, or failure modes, but for a simple read tool this is acceptable.

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 reasonably concise, with the core purpose front-loaded in the first sentence. The third sentence is somewhat redundant with the first, but it does reinforce the practical value of the documentation without excessive bloat.

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?

For a tool with one optional parameter and no output schema, the description covers when and why to use it, what it reads, and the source scope. It does not explain return format, but the tool's purpose is simple and the schema fully specifies the only input.

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%, and the single optional parameter is already well documented ('specific repository URL or name' and default behavior). The description adds no additional parameter detail, but none is needed.

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 ('Read') and resource ('agent documentation and coding guidelines from configured repositories'). It is clear what the tool does, though it does not explicitly contrast with the sibling search_agent_docs, so differentiation is left mostly to the name.

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

Usage Guidelines4/5

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

Provides explicit 'Use this when' guidance covering codebase context, coding patterns, architecture decisions, and implementation guidelines. It does not mention when to prefer search_agent_docs instead, but the usage context is clear enough for an agent.

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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