twitter_request_catalog

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

With no annotations provided, the description carries the full burden and discloses significant behavioral details: it fetches the upstream NDJSON on every call (network dependency, ensures freshness), keeps query IDs and feature flags current, and returns ranked templates. This transparency about the live-fetch behavior and output format goes well beyond what's needed.

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?

Three sentences cover purpose, usage examples, output format, and behavioral transparency without waste. It's front-loaded with the core purpose in the first sentence and efficiently packs useful operational details into the remaining two. Every sentence earns its place.

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?

Despite no output schema, the description compensates by stating results are ranked templates in the argument shape for twitter_api_request, which sufficiently communicates the return type for a search tool. With a simple 2-param schema at 100% coverage and rich behavioral disclosure, the description is complete for this tool's complexity.

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% and both parameters have descriptions in the schema. The description adds context that query terms must match all space-separated terms (AND semantics beyond case-insensitivity) and that results are ranked templates. This adds marginal value beyond the schema but is light on parametrization details like how limit interacts with ranking.

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 a catalog by operation name, path, method, or content, with specific operation examples (SearchTimeline, UserByScreenName, etc.). It also clarifies the key output property: templates already converted to the argument shape for twitter_api_request, which distinguishes its purpose from the sibling tool that actually executes requests.

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 clear usage context: use operation-like terms to search the catalog. It names the sibling tool (twitter_api_request) and frames results as pre-converted arguments for it, establishing when to use this tool (for discovering templates) vs. the sibling (for making requests). However, it doesn't explicitly state when NOT to use it or list alternative search approaches.

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