find_complaint_signals

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

With no annotations, the description carries the full behavioral burden, but it only states a high-level extraction action. It does not disclose behavior around pagination (page), rating filtering (minRating), output format, or whether the operation is read-only, leaving significant behavioral traits unspecified.

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 a single efficient sentence with no filler, and it front-loads the core extraction action. It is brief without being wasteful, making it easy to parse.

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 three parameters, no annotations, and no output schema, the description is too sparse. It omits parameter semantics, output shape, any usage caveats, and behavioral details, so an agent lacks the full picture needed for correct invocation.

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 0% and the description does not explain any of the three parameters. It only alludes to 'ASIN' in the phrase 'ASIN review page'; page and minRating are completely undocumented, so an agent cannot infer their meaning, defaults, or constraints from the text.

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, 'Extract,' and identifies a precise resource: complaint-like reviews and recurring VOC signals from an ASIN review page. This clearly distinguishes it from siblings like get_amazon_reviews or summarize_review_ratings, which handle broader retrieval or rating summaries.

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 intended use is implied: use this tool when you need complaint-related insights from a review page. However, there are no explicit when-to-use, when-not-to-use, or alternative-routing statements, and no sibling tools are referenced.

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