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

Beyond annotations (readOnlyHint, openWorldHint, etc.), the description details fan-out behavior across SEC EDGAR, GDELT→GNews fallback with conditions, USPTO soft-fail due to PatentsView API sunset, and the exact return format (changes[], total_changes, citation URIs). This is rich behavioral context not available from annotations alone.

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 dense paragraph but well-organized, front-loaded with usage examples. Each clause adds value (sources, fallbacks, return structure, alternative). Slightly long but justified by the tool's multi-source complexity.

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 no output schema, the description compensates by stating the return shape ('structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'). It also covers source limitations, partial failure modes, and parameter semantics, making it self-sufficient for an agent to invoke 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?

The schema already covers all three parameters with 100% description coverage, including `since` formats and `value` examples. The description adds no meaningful parameter semantics beyond what the schema provides, 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 clearly states the tool provides a 'change feed for a company in the last N days/weeks/months' with specific examples like 'What's new with X'. It distinguishes itself from sibling entity_profile by explicitly naming it as the alternative for 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 gives explicit guidance on when to use this tool versus entity_profile: 'Use entity_profile instead when you want the static profile...'. It also shows natural-language query triggers and mentions it operates in 'ONE parallel call', implying efficiency for batch change queries.

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