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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered without description help. The description adds genuinely new behavioral context about the payload (error against measured data by partition and channel, with measurement envelope) and the 'quote the model name with the number' instruction, but says nothing about caching, freshness, or cost.

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 and short, which is good, but the closing sentence 'Quote the model name with the number.' is cryptic — it is unclear whether it addresses formatting the request or citing the response, which costs clarity without clearly earning its place.

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?

The description covers the parameter well and an output schema exists so return values need not be explained, but for a zero-usage-guidance tool among six siblings it does not say when this summary is the right call versus running a simulation or fetching a result.

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 0% and the single parameter has no description, so the description must carry the load — and it does, enumerating 'fast', 'full', and an exact report slug like 'prom-5.3'. It also notes the default-adjacent 'full' option implicitly, though it doesn't state which is the default or what 'fast' versus 'full' costs.

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 states a clear resource and scope: model accuracy measured against wind-tunnel and bench data, broken down by partition and channel. It is specific enough that an agent can distinguish it from simulate_powertrain or get_result, though it never names a sibling verbatim.

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?

There is no statement of when to reach for this tool versus the sibling tools such as get_result or the simulation tools. The only guidance given concerns the valid values of `model`, which is parameter semantics rather than when-to-use context.

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