Find GitHub repositories by intent

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

With no annotations provided, the description fully describes the tool's behavior: it fires multiple queries against GitHub's live search (including README body), dedupes, pre-ranks, and returns the strongest candidates with trimmed README excerpts and metadata. It also clarifies that the tool returns evidence, not a verdict, which sets accurate expectations.

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 well-structured with a clear intro, an important note, and an example. Every sentence adds value, but it is slightly lengthy. However, the length is justified given the complexity of the tool's usage pattern.

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?

Given the tool's complexity (multiple queries, pre-ranking), the absence of annotations, and the presence of an output schema, the description is complete. It covers how to generate queries, what the server does, and what the agent should do with the results, leaving no critical 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?

Although schema coverage is 100%, the description adds significant meaning beyond the schema: it explains the need for 4-8 varied queries, provides an example of proper expansion, and clarifies the roles of language, min_stars, and max_results in the context of candidate selection. This enhances the agent's understanding of how to use parameters effectively.

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 states that the tool searches GitHub for repositories matching a development intent and returns structured evidence. The verb 'find' and resource 'repos' are specific, and it distinguishes itself well from hypothetical siblings by emphasizing the intent-based search and evidence-returning behavior.

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 provides explicit guidance on when and how to use the tool: expand the user's single intent into 4-8 varied keyword queries, and do not pass one raw phrase. It also explains what to do after receiving results (rank and decide). This fully clarifies usage context and alternatives.

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