analyze_review_metrics

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

No annotations are provided, so the description bears the full burden. It performs adequately by enumerating the computed outputs in detail. However, it omits operational attributes like data freshness, read-only safety, or any side effects of invoking the tool.

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 run-on sentence; zero fluff and every clause adds information about the tool's behavior. The main purpose is front-loaded with a colon introducing the metric list, though the long list of comma-separated items is slightly dense 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 3-parameter analysis tool with an output schema, the description covers the core purpose and main input. However, it doesn't document max_listings, and with no annotations to convey safety hints, subtle gaps remain in what an agent needs to call it correctly.

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?

With 0% schema coverage, the description must compensate. It covers the keyword parameter via "for an Amazon India keyword" and the marketplace via implicit Amazon.in scoping. However, max_listings is completely unexplained — an agent would not know what it controls from the description alone.

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?

Names a specific verb ("Measure") and resource ("review barrier for an Amazon India keyword") and details the exact outputs (median, quartiles, rating spread, months-to-match, beatable listings, new sellers). This distinguishes it from analyze_review and research_product, though not as explicitly as it could from the similarly-named analyze_competition/analyze_competitors.

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 implies when to use it — when an agent needs competitive review metrics for a keyword — but never explicitly states when to prefer it over the many siblings (analyze_competition, analyze_reviews, analyze_competitors). The broad metric list gives strong hints, yet no explicit routing or when-not-to-use guidance is present.

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