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

Goes well beyond the annotations: discloses the external data flow ('Sent to Google Gemini on Vertex for this review only; Edge keeps no copy'), a rate limit ('A few per user per day'), a privacy warning about secrets/personal data, and a presentation rule ('present the result as Gemini's view, separately from your own'). The only softness is that the rate limit is vague and failure/refusal behavior is not described, but the disclosure level is far above what readOnlyHint/openWorldHint provide.

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?

Front-loaded with the purpose, then workflow, then constraints and privacy. Every sentence carries information, though the long semicolon-chained sentence about skill/Source/request_id is dense and would read better split into shorter steps.

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?

Despite having six parameters and no output schema, the description covers what the tool returns, how inputs should be sourced, the privacy and rate-limit envelope, and how to report the result to the user. An agent has everything needed to call it correctly and present the output appropriately.

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 baseline is 3, but the description adds real meaning: it explains the relationship between skill, source and request_id (all three come from a find_skill result), the precedence between skill and rubric, the neutral default when neither is supplied, and the hard constraint that artifact must be literal text because 'Gemini cannot read files or URLs'. It does not clarify 'question' specifically, keeping it just under a 5.

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 and resource ('get an independent second opinion on a piece of work') and enumerates the artifact types it accepts (draft, plan, code diff, decision, design spec, message). It also names the producing model family (Google Gemini) and what comes back (verdict, 0-10 score, reasons, fixes), which clearly separates it from siblings like find_skill or use_skill.

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?

Explicit routing is given: 'To judge through an expert method, first call find_skill for a review skill... and pass its Skill, Source and request_id here; or pass a short rubric; with neither, Gemini uses a neutral reviewer rubric.' That is a complete when-to-use-which-input decision tree naming the alternative tool.

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