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

Beyond annotations (readOnlyHint, etc.), the description details multi-source parallel fan-out, fallback logic, parameter formatting, and return structure. It also notes soft-fail for USPTO due to API sunset, which is critical behavioral context not covered by annotations.

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 front-loaded with natural language queries, followed by concise, structured details. Every sentence serves a purpose: defining scope, listing sources, explaining parameters, and contrasting with sibling. No filler or repetition.

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 tool's complexity (multiple sources, fallback, parameter options) and no output schema, the description covers most aspects well. It explains return structure and fallback behavior. However, it could briefly mention error handling or response shape beyond what is stated, leaving a minor gap.

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?

With 100% schema coverage, the schema already describes parameters well. The description adds value by explaining the `since` parameter formats with concrete examples and typical usage ('Use "30d" or "1m" for typical monitoring'). This enriches understanding beyond the schema.

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 explicitly states the tool provides a 'change feed for a company in the last N days/weeks/months in ONE parallel call' and lists specific data sources. It distinguishes itself from the sibling tool `entity_profile` by contrasting dynamic vs static profile retrieval.

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 example queries and explicitly recommends using `entity_profile` for static profiles. It also explains the fallback behavior between GDELT and GNews under rate-limiting or errors, providing practical guidance for when to use this tool.

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