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

Annotations already declare readOnly, idempotent, and non-destructive, so the safety bar is lower. The description adds genuine behavioral context beyond them: the review is against a fixed rubric and the outcome is binary (PASS, or FAIL with every finding surfaced as a tool error), which tells the agent how to interpret the result.

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?

Two sentences, front-loaded with the rubric criteria and followed by the inputs and return behavior. The rubric enumeration is long but each item earns its place; no 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?

For a read-only validation tool with no output schema, the description covers what is checked, what inputs are required, and what the pass/fail outcome means. It is complete enough to call correctly; only explicit routing against sibling review tools 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 description coverage is 100%, so the baseline is 3. The description restates that source, fixture, interpretation, and component sources must be passed but adds no syntax or format nuance beyond what the schema already documents, including the nested fixture object.

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?

States a specific verb (reviews) and resource (dashboard or overview page source) and enumerates the rubric: complete source, unchanged data, supported claims, hierarchy, scan order, and component usage. An agent knows exactly what the tool inspects. It does not explicitly name or distinguish itself from the similarly-named sibling finalize-dashboard-review, so it stops short of a 5.

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?

Invocation context is implied by 'Pass the page source, the data fixture, its interpretation and the component sources', which tells the agent how to call it, but there is no explicit when-to-use versus the related finalize-dashboard-review or get-review-rules siblings, and no stated prerequisites.

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