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r28ai

recruiting-ops-mcp

by r28ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

github_search_repositories

Read-onlyIdempotent

Search GitHub repositories by keywords and qualifiers like language, stars, topic, org, or license to research a candidate's public work and projects for recruiting.

Instructions

Search repositories with qualifiers, e.g. 'topic:cli language:go stars:>500'. Rate limited to 30 requests per minute.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesThe query containing one or more search keywords and qualifiers, e.g. `tetris language:assembly stars:>100`. Qualifiers include `language:`, `stars:`, `forks:`, `topic:`, `org:`, `user:`, `license:`.
pageNoThe page number of the results to fetch. Defaults to 1.
sortNoSorts the results by number of stars, forks, help-wanted issues, or how recently the items were updated. Default: best match.
orderNoDetermines whether the first search result returned is the highest number of matches (`desc`) or lowest (`asc`). Ignored unless `sort` is provided. GitHub uses `desc` when this is absent.
perPageNoThe number of results per page (max 100). Defaults to 30.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover read-only, open-world, and idempotent behavior. The description adds a valuable operational constraint: a rate limit of 30 requests per minute, which is not available from annotations or schema.

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?

Two sentences with no waste. The purpose and example are front-loaded, followed by the rate limit. Every sentence earns its place.

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?

The schema and annotations are rich, and the description adds a key rate-limit detail. It is nearly complete for a search tool, though it could note that results are paginated or what the response contains if an agent needed that reassurance.

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 all five parameters and qualifier syntax. The description's example query is consistent with the schema but does not add meaning beyond it, making the baseline 3 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 states a specific verb and resource: search repositories. The example query with qualifiers makes the scope unambiguous and distinguishes it from sibling tools like github_search_commits or github_repos_list_languages.

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?

Usage is implied by the tool name and description, but there is no explicit when-to-use or when-not-to-use guidance, nor any comparison to alternatives such as github_repos_list_languages or tavily_search.

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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