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

Goes well beyond the readOnly/destructive/idempotent annotations: defines the deterministic processing order (trim → PK dedup → required/range checks), states dedup keeps the first row and skips later-row field checks, that missing keys are retained and flagged, that numeric strings are neither converted nor range-checked, that only top-level strings are trimmed, and that inputs are not mutated. It also discloses the operating model (free, unauthenticated, stateless, per-call rules) and the privacy posture (usage metadata recorded, bodies not stored).

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: purpose and return values land in the first clause, with behavioral caveats after. It is dense and semicolon-heavy – some sentences pack two distinct facts (e.g. the collision note) – but nearly every sentence carries decision-relevant information.

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 six-parameter, stateful-behaving audit tool with an output schema already covering return structure, the description covers the remaining risk surface: ordering effects, what dedup drops, what gets flagged but retained, and the REVIEW-does-not-clear warning. Nothing an agent needs to call it correctly 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 the schema already carries the per-parameter burden and baseline is 3. The description still adds semantics the schema does not spell out as clearly: the 500-row ceiling, the trim-collision example ('a ' and 'a' collide), and the fact that duplicate removal short-circuits later required/range checks on skipped rows.

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?

First sentence gives a specific verb pair ('audit and optionally clean'), the resource ('JSON rows'), the hard scope (up to 500), and the return shape (cleaned_rows, zero-based issues, counts). It also names the sibling it is not (trust_validate_data) for type enforcement, so the agent can tell the two apart without opening either schema.

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?

Explicitly routes type-enforcement work to trust_validate_data and warns to inspect issues before use because REVIEW persists after repair, plus notes that an empty array returns ALLOW. Clear usage context, but it does not say when to prefer this over the other audit-related siblings (trust_check_action, trust_check_spend).

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