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

Annotations already declare readOnlyHint, idempotentHint, etc. The description adds significant behavioral context: fan-out to multiple sources, fallback logic, USPTO patent soft-fail, return structure (grouped by source, total_changes, citation URIs), and relative date format details.

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 a single paragraph but is well-organized, beginning with common queries and then detailing sources, parameters, and return structure. Every sentence adds value; no fluff. Could benefit from slight structuring (e.g., bullet points) but remains efficient.

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, date parsing, soft-fails), the description covers all important aspects. No output schema exists, but the return structure is described adequately. The description fully informs an agent on how to invoke and what to expect.

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 baseline is 3. The description adds meaningful context beyond schema: for 'since' it explains relative shorthand and gives examples, for 'value' it mentions ticker or CIK, for 'type' it notes only company is supported. This enhances parameter understanding.

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 provides a change feed for a company in the last N days/weeks/months via one parallel call, with specific data sources listed. It also distinguishes from the sibling tool 'entity_profile' by contrasting dynamic changes vs. static profile.

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 provides example queries and explicitly recommends 'entity_profile' when static profile is needed instead. It describes fallback behavior (GDELT→GNews) and soft-failures, giving clear context. Lacks explicit 'when not to use' beyond the alternative, but is strong overall.

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