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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is known. The description adds valuable behavioral context by listing exactly what is returned (extraction source, corroboration score, source list, verification date, freshness summary), helping the agent anticipate output structure.

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 two information-dense sentences plus an input listing. It front-loads the purpose, then gives a usage scenario, then inputs. No filler or repetition; every sentence earns 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?

With an output schema present and readOnly/openWorld annotations, the description specifically covers what data is returned and when to use the tool. For a read-only audit tool, this is sufficiently complete and well-contextualized.

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?

Input schema covers all 3 parameters with 100% description coverage. The description mentions entity_id (required) and entity_type (franchise or work), which mirrors the schema but adds no new semantic detail. The async parameter is only in schema, but it is already documented there, so baseline 3 is appropriate.

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 uses a specific verb ('Audit') and resource ('full data provenance of a content entity'), clearly distinguishing it from siblings by detailing enrichment tags, extraction source, corroboration score, and freshness summary. It conveys exactly what the tool does and its scope.

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?

It explicitly states when to use: 'Use this tool before citing or relying on enriched content data in a high-stakes context.' While it doesn't name alternatives or when-not-to-use, the guidance is unambiguous and contextually strong.

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