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

Annotations already declare this is a non-destructive write (readOnlyHint=false, destructiveHint=false), and the description reinforces that by saying the review is *saved* rather than merely computed. It adds genuinely useful context beyond the annotations: the output is advisory, requires human review, and is explicitly not a certification or compliance determination. It does not disclose runtime cost, latency, idempotency, or whether a re-run overwrites an earlier saved 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?

Three sentences, each carrying distinct information: what is produced, what it looks for, and what the scope limits are. The capability statement is front-loaded and the disclaimer closes the description, so nothing is buried and no sentence merely restates the name.

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 must carry the return-value burden; it does partially, saying the result is suggested changes for human review, but gives no sense of structure, severity, or how the saved review is later retrieved. For a mutation tool that triggers an AI evaluation, it is adequate but leaves the agent guessing about result shape and follow-up steps.

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 both parameters are documented in the schema and the baseline is 3. The description adds no meaning beyond the schema: it never mentions the optional 'prompt' parameter, which is the one field an agent could most easily misuse to over-direct or bias the evaluation.

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 names a specific verb and resource: "Generate and save an AI-assisted review of a functional-safety work item and its traceability graph." It also names the concrete output artifacts (candidate requirement gaps, incomplete links, suggested changes). It never names a sibling tool, so the boundary against get_evaluation_result or list_evaluation_results is left to inference.

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?

Usage is implied rather than stated: the agent can infer this is the tool that produces an evaluation, but nothing says when to run it versus retrieving a prior result with get_evaluation_result or listing existing ones. There is no guidance on whether re-running is safe, when an evaluation is stale, or what prerequisites the work item must satisfy.

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