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github_list_prs

List pull requests from a GitHub repository, with optional state filter (open, closed, all) and count limit.

Instructions

List pull requests in a repository.

Args: repo: Repository name (defaults to configured default repo) state: PR state filter ('open', 'closed', 'all') limit: Maximum number of PRs to return

Returns: Dictionary with list of pull requests

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": "github_list_prs"
  }
}

Input Schema

Name	Required	Default
`repo`	No
`limit`	No
`state`	No	open

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 13, 2026

TDQS

A3.9/5.0

Behavior3/5

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

No annotations provided, so the description is the sole source. It explains the return type (dictionary with list of PRs) but lacks details on pagination, sorting, or authentication requirements. Adequate but with gaps.

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

Conciseness5/5

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

The description is concise, with a clear Args/Returns structure. Every sentence is useful, no redundancy, and it is front-loaded with the core purpose.

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?

Given no output schema and 0% parameter schema coverage, the description does not fully cover return format details (e.g., PR structure) or behavior like pagination. While functional, it leaves some gaps for an AI agent.

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

Parameters4/5

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

With 0% schema description coverage, the description compensates by explaining each parameter: repo (defaults to configured), state (filter values), limit (max count). Adds meaningful context beyond the schema's property names.

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 'List pull requests in a repository', using a specific verb and resource. It distinguishes from sibling tools like github_get_pr (single PR) and github_create_pr.

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 mentions default repo, state filter, and limit, but does not explicitly state when to use this tool versus alternatives like github_get_pr. Usage context is implied by the parameters.

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