Fetch detailed statistics and metadata for a GitHub repository. Returns star count, fork count, open issue count, primary programming language, project description, last updated timestamp, and contributor count. Use for evaluating open-source projects, competitive analysis, or monitoring project health.
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | Repository in format 'owner/repo' (e.g. 'facebook/react', 'kubernetes/kubernetes') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds behavioral context beyond annotations (readOnlyHint, openWorldHint) by specifying the exact data returned (star count, fork count, etc.). It does not contradict annotations and provides useful details about the tool's output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is two sentences: first clearly states the action, second lists returns and use cases. No fluff, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has only one parameter, no output schema, but description lists all return values explicitly. Complete for a low-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with a clear description, so the description does not need to add parameter details. It correctly avoids repetition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool fetches detailed statistics and metadata for a GitHub repository, listing specific data points (star count, fork count, etc.). It distinguishes itself from sibling tools like search_github which is for searching, and get_npm_package/get_pypi_package which are for other ecosystems.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides explicit use cases: 'evaluating open-source projects, competitive analysis, or monitoring project health.' While it does not explicitly state when not to use or alternatives, the context from sibling tools makes the intended usage clear.
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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Each tool targets a distinct data source and operation: GitHub repos, npm packages, PyPI packages, arXiv papers, GitHub search, Google Scholar, and Stack Overflow. Even the two GitHub tools differ in purpose (get specifics vs search). No overlap.
All tool names follow a consistent verb_noun pattern using snake_case: get_* and search_*. The verbs are precise and the nouns clearly indicate the target resource.
With 7 tools, the set is well-scoped for a developer toolkit covering package registries, code search, academic resources, and Q&A. Each tool serves a distinct purpose without bloat.
The set covers major developer resources (GitHub, npm, PyPI, arXiv, Google Scholar, Stack Overflow). Missing are tools for other registries (e.g., Maven, Docker Hub) and package search for npm/PyPI (only get by name), but core workflows are well represented.