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read_repositories

Read-onlyIdempotent

Where this project's code lives on GitHub. Returns whether the sponsor connected a GitHub account, the repositories linked to the project with your current access (write, read or none, and when it ends), pending repository requests and how to proceed. Decide with the owner how many repositories the project needs before asking for any. Reveals no token.

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": {
      "project_id": "<project_id>"
    },
    "name": "read_repositories"
  }
}

Input Schema

NameRequiredDescriptionDefault
project_idYes
result_offsetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover the safe-read profile (readOnly, idempotent, non-destructive), so the bar is lower, and the description still adds real context: per-repository access levels with expiry dates, pending request visibility, and the security note 'Reveals no token'. What it omits is pagination behavior and result size, which matters for a list-returning tool.

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?

Five short sentences, front-loaded with what the tool surfaces and ending with the 'Reveals no token' reassurance. No filler, though the opening fragment is less scannable than a verb-first phrasing would be.

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 no output schema, the description does useful work by sketching the return payload (account status, repos, access, pending requests). But for a returning-list tool with a paging parameter, omitting pagination behavior and not pointing at request_repository as the next step leaves a real gap.

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% across two parameters, so the description carries the full burden — and it names neither. 'project_id' is guessable from context, but 'result_offset' is a pagination parameter that goes completely unmentioned, leaving the agent no explanation of how to page through results.

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?

The description states a specific resource (the GitHub repositories linked to a project) and enumerates what it returns: sponsor account connection, repositories plus your access level and expiry, and pending requests. That distinguishes it from siblings like request_repository or github_token. It stops short of a crisp verb-first statement, opening instead with a sentence fragment.

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?

It gives concrete workflow guidance — 'Decide with the owner how many repositories the project needs before asking for any' — which implies reading this view before making a request. It does not explicitly name request_repository as the follow-up tool or state exclusions, so the routing is inferable rather than spelled out.

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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