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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds only that the payload spans several metric families, without saying anything about pagination, freshness, scoping, or auth requirements.

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?

Two sentences, front-loaded with the verb and the returned content, with the purpose clause second. The metric enumeration is dense but each item is informative given no output schema exists to carry that 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?

With no output schema, the description carries the burden of describing what comes back, and it does so by naming the metric categories. For a zero-parameter read tool with full annotation coverage, this is close to sufficient; only freshness/pagination details are 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool is 4. No syntax or filtering semantics are needed.

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 ('Read') plus an explicit enumeration of the resources returned (calibration, labeled outcomes, false-ALLOW rate, regression results, discovery metrics, monitors, verified revenue). That distinguishes it clearly from siblings like record_outcome and create_trust_monitor, which write or verify rather than report aggregate trust metrics.

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 second sentence gives a use case ('audit whether the trust model is improving safely'), which implies when the tool is appropriate. However, it names no alternatives and gives no exclusions or prerequisites, so routing decisions relative to the other trust/economics tools are left to inference.

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