Search customer conversations

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

With no annotations, the description carries the full burden and does well: it discloses server-side waiting up to `wait_seconds`, the partial-result escape hatch (returns a search id to resume), and that the call consumes BuzzSearch credits at the API rate with the exact charge reported as `credits_charged`. It stops short of covering auth requirements, failure modes, or what happens when credits run out.

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 opening sentence front-loads the value proposition, then proceeds to mechanics, link handling, waiting, and cost in a logical order. It is somewhat dense at roughly 110 words, but each sentence carries distinct operational information rather than restating the name.

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 tool with no output schema, the description states the return shape (an answer with top quotes, or the search id), the cost field (`credits_charged`), and the resume path, which is everything an agent needs to call and follow up on it. No material gap is left for a four-parameter search tool.

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 baseline is 3, but the description adds real meaning beyond the schema: link-in-query interception behavior, the wait/resume semantics tied to `wait_seconds`, and the source scope spanning four platforms. Only `depth` and the default source set are left entirely to the schema.

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 names a specific verb and resource (research what real people say across Reddit, YouTube, TikTok, Facebook) and enumerates the pipeline: discover threads, read comments, extract verbatim quotes, write a cited answer. It also names sibling tools (`get_search`, `list_searches`) so the agent can distinguish this from them without opening a 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?

Explicit routing is given: a query containing a platform link reads that link's comments directly (with an optional follow-up question), and a search id should be resumed with `get_search`. It also instructs the agent to check `list_searches` first because a prior search on the same topic is free to reread — a concrete when-to-use/when-not condition.

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