GitHub repository/file data

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

No annotations are provided, so the description must disclose behavioral traits. It does not mention whether the operation is read-only, requires authentication, or has rate limits. The word 'Structured' hints at output format but offers no transparency about side effects or access requirements.

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?

The description is a single, front-loaded sentence with no redundant words. Every word adds meaning, making it concise and well-structured.

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?

For a simple tool with one parameter and no output schema, the description lists the expected data types (stars, forks, contributors, file content), which provides some completeness. However, it does not specify the exact response structure, error behavior, or whether file content is raw or structured, leaving gaps.

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?

The schema fully describes the only parameter `url` as 'GitHub repository or file URL', and the tool description repeats this without adding new meaning. With 100% schema coverage, the baseline is 3, and the description provides no additional parameter context.

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?

The description clearly identifies the tool as providing structured GitHub repository or file data, listing specific data types (stars, forks, contributors, file content). It is distinct from sibling tools that target other platforms, though it lacks an explicit action verb like 'fetch' or 'retrieve'.

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?

The description implies the tool is for GitHub URLs and data, but it does not explicitly state when to use this tool over alternatives such as smart_scrape or other web_data tools. No exclusions or alternative recommendations are provided.

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