hn-search

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 explains the tool returns structured results, supports filtering and sorting, and implies it is a read-only search. No destructive actions, rate limits, or auth needs are mentioned, which is acceptable for a simple search tool.

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 two concise sentences with no wasted words. It front-loads the core purpose and then lists key features and use cases, making it easy to scan.

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 search tool with no output schema, the description adequately covers what the tool returns and how to customize results. Given the simplicity of the tool and presence of detailed input schema, the description is complete.

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 coverage is 100%, providing a baseline of 3. The description adds value beyond schema by explaining usage details: exact phrases for 'q', types 'story/comment', sort options 'relevance' or 'date', date range values ('day/week/month/year/all'), and limit range (1–20). This enriches parameter understanding.

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 the tool searches Hacker News stories and comments, specifying what data it returns (titles, scores, comment counts, authors, URLs). It distinguishes itself from numerous sibling tools by its specific domain and functionality.

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 context for using the tool (tech news, community sentiment, discussion discovery) and explains filtering/sorting options. It lacks explicit when-not-to-use or alternatives, but the use cases are clear.

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