search_by_topic

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

With no annotations, the description carries the behavioral burden. It does disclose a key behavior—matching curated GitHub topic tags rather than description text—and provides examples. However, it does not mention result ordering, pagination, error behavior, or any constraints on topic matching beyond lowercase/hyphenated guidance in the schema.

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?

Two sentences with no filler. The core action and examples come first, and the usage guidance is concise and immediately actionable.

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 rich schema covering all parameters and the clear differentiator from sibling tools, the description is nearly complete. The only notable gap is the lack of any statement about the return shape, and without an output schema the agent must infer that the result is a list of repository records.

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 description coverage is 100%, so the schema already documents the topic and filter parameters well. The description adds useful context about what a topic tag is and how it differs from free-text, but it does not need to explain parameter syntax since the schema covers it.

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 states a specific verb ('Find') and resource ('GitHub repositories') and narrows the operation to topic-label matching. It explicitly contrasts with free-text search, distinguishing this tool from sibling search_github_repos without needing to inspect the schema.

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?

It gives clear guidance: use this tool when you already know the ecosystem's term for the topic, and frames it as more precise than free-text search. This effectively routes the agent between search_by_topic and search_github_repos with an explicit condition.

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