verify_fix

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does a good job: discloses that the tool only reports observed failures for rules not in the supported passing list, that unknown rules and missing evidence never clear, and that a cleared finding is not a user endorsement of the fix. It also explains the regression guard behavior. It does not explicitly state whether the operation is read-only or has side effects, but given the described behavior (a check), this is implicit. One might argue for a 5, but the lack of explicit mention of side-effect-freeness or any destructive potential is a tiny gap; still, it's quite thorough.

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 solid paragraph, slightly long but information-dense. It front-loads the purpose, then adds critical caveats. It could be split into bullet points for readability, but every sentence earns its place — no filler. The length is justified given the complexity (supported rules, evidential requirements, regression guard, exclusions).

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 and no annotations, the description does an excellent job of covering everything an agent needs: what it does, when to use it, what the return statuses mean, what constitutes a pass (explicit server evidence for the requested route and both viewports), which rules are supported for passing, what happens for other rules, and how to handle judge/interaction/site checks. It also mentions the regression guard, covering the risk of a fix breaking something else. Very complete.

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 the schema already documents all four parameters. The description adds context about the rule parameter (which rules are supported for passing) and hints at the interaction states for state/form/interaction rules, but does not add substantial new semantics beyond what's in the schema. The description does not mention default values or relationships that are not already present in the schema. Baseline 3 is appropriate.

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 states the specific verb ('re-check'), resource ('ONE rule on ONE page'), and purpose ('did my fix land?'). It clearly distinguishes itself from a full re-audit by naming the alternative (audit_url) and explaining the difference (one route, no crawl, no judge). The description is not a tautology; it explains the tool's role in the fix-verify workflow.

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 explicitly states when to use this tool (after editing to fix a finding, to verify a specific fix) and when not to use it (for judge, interaction and site checks — says to re-run audit_url for those). It also names the sibling tool audit_url as the alternative. It provides clear conditions: a pass requires explicit server evidence for the requested route and both viewports, and unsupported rules cannot pass. This is explicit and actionable.

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