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

Annotations already establish readOnly/non-destructive, so the description's real contribution is the state machine (queue position or progress while running, verified comparison when done) plus a data-integrity rule about quoting and estimates. Missing is anything about how long a measurement typically takes or how often to poll.

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, then the two states, then the quoting constraint. Three sentences with no filler; the final sentence's 'do not invent numbers' is defensive but carries genuine instruction value for a results tool.

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?

No output schema exists, so the description bears the burden of describing return values; it does so at a functional level (queue position, progress, verified comparison, other slowdowns) without detailing field structure. For a one-parameter read-only poll tool this is nearly sufficient, though a hint on result shape would complete it.

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% and the single audit_id parameter is fully documented in the schema as 'audit_id from measure_site'. The description adds no syntax, format, or validity detail beyond that, so the baseline of 3 applies.

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+resource ('status or result of a measurement') and anchors it to its producer: 'started with measure_site'. The two-state return (running vs done) makes it immediately distinguishable from the sibling measure_site.

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?

The dependency on measure_site is explicit, and the running/done branches tell the agent what to expect on each call, implying a polling pattern. It does not state outright that the agent should re-call until completion, nor any polling cadence, so guidance is clear but not fully prescriptive.

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