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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds detailed behavioral context: it fans out to multiple sources (SEC EDGAR, GDELT→GNews, USPTO), explains the fallback mechanism, and notes the PatentsView API sunset causing soft-fail. This goes well beyond the 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 fairly long but every sentence contributes useful information. It is well-structured: starts with examples, then describes functionality, parameter behavior, source details, fallbacks, and alternative tool. It could be slightly more succinct without losing clarity, but it 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 data sources, fallback, parameter parsing, no output schema), the description is complete. It explains the return format: 'structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'. It also addresses edge cases like the PatentsView API sunset. No gaps remain.

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% with descriptions on all three parameters. The description adds significant meaning: explains `since` accepts ISO dates or relative shorthand ('7d', '30d', '3m', '1y') and suggests '30d' or '1m' for typical monitoring; clarifies `value` can be ticker or CIK; and restates that `type` is only 'company'. This adds value 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 starts with concrete example queries ('What's new with X', 'latest on Y') and explicitly states it is a 'change feed for a company in the last N days/weeks/months'. It clearly distinguishes from the sibling tool 'entity_profile' by specifying when to use the alternative. This is a specific verb+resource with sibling differentiation.

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 explicit guidance: 'Use entity_profile instead when you want the static profile'. It also explains the fallback behavior (GDELT preferred, GNews when rate-limited or 5xx) and notes that USPTO soft-fails until reactivated. This clearly informs when and how to use the tool.

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