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

Annotations already cover read-only, idempotent, closed-world safety. The description adds genuinely new facts: no model is run server-side ('welance runs no model for this'), the call is free, and an empty brief yields a {{BRIEF}} placeholder template rather than an embedded one. It stops short of describing the exact response payload, but the key behavioral traits are disclosed.

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 core purpose, and the free/no-model-run caveats are placed early. Most sentences carry useful routing or behavioral content, though the line breaks are slightly awkward and a couple of clauses (temperature advice) could be tightened.

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 takes on return-value duty and does explain that the prompt text, verdict JSON Schema and ruleset_version come back, plus how they feed the next tool. Only the precise response shape is left implicit, which is a minor gap for a single-optional-parameter read tool.

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 0%, so the description must carry the single parameter — and it does, explaining that brief gets embedded and an empty value produces a template with a {{BRIEF}} placeholder. That is meaningfully more than the bare schema offers, though it doesn't indicate expected brief format or size.

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 — returns the judge prompt and verdict JSON Schema — and clarifies its unusual role: the text is for the caller's own model to answer. This separates it cleanly from siblings like aggregate_verdicts (which consumes the answer) and get_improvement_prompt.

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?

Gives explicit workflow: fetch the prompt, answer it with your own model at temperature 0, return only the JSON array, then pass that array with the brief and ruleset_version to aggregate_verdicts. It also names the two modes (pass brief vs leave empty) and the condition that selects each.

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