analyze_reviews

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

With no annotations, the description must disclose behavioral traits. It mentions that using this tool avoids re-paying the Shulex API, which is a cost-related behavior. However, it does not mention whether the tool is read-only, requires authentication, or any other side effects. Given it is an analysis tool, the description is moderately transparent.

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 concise and well-structured, with separate paragraphs for purpose, usage, arguments, and returns. It is front-loaded with the action. Could be slightly shorter, but no unnecessary filler.

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 the complexity (custom input format) and lack of output schema, the description covers all return fields and provides usage context. It explains how reviews_json can be two different formats, which is crucial. It also mentions the relationship to fetch_reviews. Missing details on error handling or limitations, but overall adequate.

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?

The schema coverage is 0%, so the description must compensate. It does so by specifying that reviews_json accepts either a specific envelope format or a bare list, and explains asin as a 10-character identifier for the report header. This adds significant meaning beyond 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 explicitly states the tool runs AI analysis on reviews to produce a VOC report with specific components (sentiment, pain points, etc.). It distinguishes from sibling tools like fetch_reviews (which fetches reviews) by focusing on analysis of already-obtained reviews.

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 clearly indicates when this tool is useful: after fetching reviews via fetch_reviews or a custom scraper, to get analysis without extra API cost. It does not explicitly state when not to use, but the context is implied.

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