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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond annotations: it explains the tool reads precomputed artifacts rather than probing live, that missing component availability explains omitted evidence, and that DataPulse is read-only with no API key required. It also clarifies the tool does not verify signatures, which is a meaningful behavioral disclosure. Minor gap: it doesn't detail the exact structure of the returned trust score or evidence objects, but the output schema likely covers that.

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?

The description is dense but well-organized, front-loading the core purpose and then covering exclusions, usage guidance, and operational constraints. Every sentence adds information. It could be slightly more concise, but the density is justified given the need to distinguish from many sibling tools.

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 read-only aggregation tool with a single parameter, full schema coverage, and an output schema, the description is complete. It covers what the tool returns, what it does not do, when to use it, and operational constraints. The output schema handles return-value details, so nothing critical is 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?

Schema coverage is 100%, so the schema already documents the single parameter. The description adds value by explaining the parameter is a stable dataset slug returned by search_datasets, giving an example ('fuelprice'), and clarifying that display names are not resolved here. This goes beyond the schema's basic description and examples.

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 clearly states the tool aggregates published attestation facts, trust score, numeric components, and evidence for one canonical dataset id. It distinguishes itself from sibling verification tools by explicitly naming verify_attestation, verify_dataset, and verify_evidence as alternatives.

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 description explicitly states when to use this tool ('assemble the published trust view') and when not to use it ('do not use it for receipt verification, live comparison, or signature verification'), naming the specific sibling tools to use instead. It also provides operational guidance about rate limits and retry behavior.

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