Search topics

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

The readOnlyHint and openWorldHint annotations already establish that this is a safe, external search operation. The description adds useful semantics about featured and curated topics, but it does not describe pagination behavior, rate limits, authentication needs, or the full return shape.

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 three short sentences with the core action front-loaded, a concrete example, and the follow-up usage instruction. Every sentence contributes useful information without repetition.

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?

With no output schema, the description does enough by saying it returns exact topic names and distinguishing featured and curated topics. It could be slightly more complete by mentioning pagination or the returned fields, but the schema documents the pagination parameters.

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 baseline is 3. The description adds meaning beyond the schema by explaining that featured topics are highlighted by GitHub and curated topics have extra descriptions, directly clarifying the featured_only and curated_only filters.

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 uses a specific verb and resource: 'Find the exact GitHub topic names for a concept.' It also gives a concrete example mapping and names the sibling tool where the results are intended to be used, making it easy to distinguish from search_repositories.

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 clearly tells the agent to use the returned topic names in search_repositories, which is the key usage path. However, it does not explicitly state when not to use this tool or compare it against directly searching repositories without topic normalization.

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