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

The annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered; the description still adds real context by disclosing the fingerprint/spec integrity check, the red-amber-green semantics with reasons, that results are both shown in chat and returned, and that an external arquestra.dev link carrying only codes accompanies them. 'Stores nothing' usefully reinforces the no-side-effect claim. It stops short of describing behavior when verification fails, which is the main behavioral gap.

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, front-loaded with the core transformation, then the verification precondition, then the return/link behavior. Every clause carries information, though the final sentence about the arquestra.dev link is densely packed and slightly harder to parse than the rest.

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 two-parameter, fully documented, non-mutating tool with no output schema, the description covers what it consumes, what it verifies, what it produces, and that it persists nothing. The notable omission is failure behavior when the fingerprint or spec check does not match, which an agent would need in order to handle that case.

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 baseline is 3, but the description adds genuine meaning: it explains why the output must contain the fingerprint line (to confirm the script is unchanged) and that the spec is the same one given to prepare_script, which is the basis for the comparison. It does not add format or syntax detail beyond the schema, so it does not reach the top of the scale.

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 verb and resource are specific: it turns measure.py output into one red/amber/green light per result, with reasons, and returns them. It also states the verification precondition (unchanged script, matching spec), which is concrete enough that an agent can tell this is a render/verify step rather than a measurement step. It never names or contrasts with the siblings example_audits or start_audit, so differentiation is only partial.

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?

Placement in the pipeline is implied by 'output of measure.py' and by the schema's reference to prepare_script, so an agent can infer it runs after measurement. There is no explicit statement of when to prefer this over example_audits or start_audit, nor what to do instead if the fingerprint check fails, leaving the routing decision to inference.

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