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

Annotations already indicate read-only, open-world, and idempotent behavior. The description adds significant detail: fans out to SEC EDGAR, GDELT→GNews fallback, USPTO soft-fail, and returns structured changes grouped by source. No contradiction with 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 a single paragraph but front-loads example queries and covers key information. Every sentence adds value, though a more structured format (e.g., bullet points) could improve readability.

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?

No output schema, but the description mentions return structure (changes[] grouped by source + total_changes + citation URIs). Parameter details are complete, and fallback/error behavior is noted. Adequate for tool complexity.

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 value by explaining the 'since' parameter format (ISO date or relative shorthand like '7d') and providing usage guidance ('Use "30d" or "1m" for typical monitoring'). It also clarifies 'value' can be ticker or CIK.

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 over a time window, with example queries like 'What's new with X' and 'latest on Y'. It distinguishes itself from the sibling 'entity_profile' tool, which provides static profiles.

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 recommends using 'entity_profile' instead for static profiles, giving clear context for when to use this tool. However, it does not explicitly state when not to use it beyond that alternative.

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