scout-mcp

github_search

Search GitHub repositories by keyword, topic, or description. Filter by language, sort by stars, forks, or updated. Returns stars, forks, language, topics, and license info.

Instructions

Search GitHub repositories by keyword, topic, or description. Returns stars, forks, language, topics, and license info.

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": {
      "query": "<query>"
    },
    "name": "github_search"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	Search query (supports GitHub search qualifiers like 'topic:mcp')
`sort`	No	Sort order	best-match
`per_page`	No	Results per page
`language`	No	Filter by programming language (e.g. 'typescript')

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 23, 2026

TDQS

A4.2/5.0

Behavior4/5

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

No annotations are provided, so the description must carry full burden. It explains what the tool returns (stars, forks, language, topics, license) and hints at typical search behavior. It does not mention rate limits, authentication needs, or destructive actions, but for a read-only search tool, the description is reasonably transparent.

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 a single, concise sentence that front-loads the purpose and key outputs. No wasted words.

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?

Given the tool's complexity (4 parameters, no output schema, no nested objects), the description covers the main functionality and outputs. It does not detail the return format or pagination behavior, but the schema covers parameters. For a search tool, this is mostly complete.

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 the schema already documents each parameter. The description adds no additional semantics beyond what the schema provides, such as clarifying the 'query' supports GitHub qualifiers (which is already in the schema description). Baseline 3 is appropriate.

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 searches GitHub repositories by keyword, topic, or description, and lists the returned information (stars, forks, language, topics, license). This distinguishes it from sibling tools like github_repo_info that focus on a single repo, and from other search tools targeting different platforms.

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?

The description implies when to use this tool (to search GitHub repos) vs. siblings like github_repo_info (for detailed info on a single repo) or other search tools (for different platforms). However, it does not explicitly mention when not to use it or provide alternative tools.

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