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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses cost, data-source limitations (blind to cited-without-querying hosts), the 2026-09-15 fan-out exposure caveat, and semantic distinctions such as ownSite hygiene vs outreach. It also clarifies what progress.opened means and how to act on it.

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 and front-loaded with the core definition, but it is a single long paragraph with metaphorical language like 'honest cross' and 'corroboration homework' that could be tightened. Every clause adds information, but the structure could be clearer.

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?

Given the output schema exists and the sole parameter is optional, the description covers all critical interpretive pitfalls: data source, entity classifications, hygiene semantics, denominator caveat, progress.opened usage, and cost. An agent has enough context to invoke and interpret the tool correctly.

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 100% and the only parameter, user_intent, is fully described in the input schema. The tool description adds no extra meaning to this optional parameter, 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?

The description clearly identifies the tool as returning trust entities AI engines consult, with a specific resource and provenance. It does not explicitly reference sibling tools, so differentiation rests on the unique 'trust entities' concept rather than naming an alternative.

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 gives clear operational context: it reads connected/stored data, is free, and explains when low findingsWithFanouts should trigger a fresh scan rather than being read as absence. It does not explicitly list when-not-to-use or direct the agent to a named sibling tool.

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