bluesky_search

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

Without annotations, the description fully discloses the return format (posts array with fields), the need for authentication, the fact it's free, and common error types. This provides complete behavioral transparency for the agent.

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 concise sentences: purpose, auth requirement, return format and errors. It is front-loaded with the main action and avoids any fluff.

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 9 parameters and no output schema, the description covers the return structure, auth requirements, and common errors. It explains the key aspects needed for the agent to invoke the tool correctly, including the default for sort and the need for no hashtag prefix on tags (though tag detail is in schema). It feels 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 high (89%), so baseline is 3. The description adds value by clarifying the query format (Lucene-style, with examples) and explaining the sort enum meanings ('latest' for freshness, 'top' for engagement). This goes beyond the schema's minimal descriptions.

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 public Bluesky posts with filters by keyword, author, mentions, tag, or language, using the specific endpoint. This differentiates it from sibling tools like bluesky_mentions (which may focus on mentions only) and bluesky_post (which creates posts).

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 mentions that authentication is now required (handle + app password) and lists common errors (VALIDATION_ERROR, PLATFORM_ERROR), guiding the user on prerequisites and error handling. However, it does not explicitly contrast this tool with alternatives like bluesky_mentions for mention-specific searches, leaving some ambiguity for the AI agent.

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