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

Beyond the annotations it discloses free-tier quota (1/day), the $0.05 x402 fallback cost, that an unchanged page short-circuits to earlier findings, that reaction_id is retained 30 days, and that there is no score. The findings shape (category, severity, personas, evidence, why it matters, fix) tells the agent what will come back from a check-heavy operation.

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 dense sentences, front-loaded with the core purpose before the output shape, quota, and simulated-perspective caveat. The enumeration of finding fields is long but earns its place because no output schema exists to carry it.

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?

With no output schema, the description supplies the return shape itself, plus cost, quota, verification semantics, and the caveat that this is simulation. Nothing an agent needs to decide whether to call it or how to interpret results is missing.

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%, so a 3 is the baseline, but the description earns extra credit by explaining what previous_reaction_id is for behaviorally (verify fixes; unchanged page returns earlier findings without consuming the free check) and by constraining url to a homepage. The schema covers syntax; the description covers intent.

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?

It states a specific verb and resource with unusual precision: eight simulated customer perspectives read one homepage and report evidence-backed buying blockers. It is clearly distinct from list_checks and audit_site, but it overlaps awkwardly with the verify_fixes sibling by claiming fix verification through previous_reaction_id without naming that alternative.

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?

It gives clear context for when to call it (one homepage, problems that would stop purchases) and describes the fix-verification path in concrete terms. It also caveats that the perspectives are simulated, not real customers. It never explicitly excludes cases or names a sibling tool for an adjacent job.

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