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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds substantial behavioral details: it fans out to SEC EDGAR, GDELT→GNews fallback (with explanation of when fallback occurs), and USPTO patents with a note about API sunset. It also describes the return structure with changes[], total_changes, and citations. 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 relatively long but front-loaded with example queries and a clear purpose statement. Every sentence provides useful information, such as source details, fallback behavior, and output format. It could be slightly more concise, but the structure effectively supports understanding.

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?

The tool has no output schema, so the description must explain return values; it does: 'Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs.' It also covers multi-source behavior, fallback, and date parsing. Given the complexity, this description is complete and leaves no critical gaps.

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 beyond schema: it explains that `since` accepts ISO date format or relative shorthand, gives examples, and recommends typical values. This clarifies usage beyond the schema's brief description.

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 clear example queries and states it is a 'change feed for a company in the last N days/weeks/months in ONE parallel call.' It explicitly distinguishes from the sibling tool entity_profile, saying when to use that instead. The purpose is specific, actionable, and clearly differentiated.

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 on when to use this tool versus entity_profile ('Use entity_profile instead when you want the static profile...'). It also advises on the `since` parameter with examples and recommendations ('Use "30d" or "1m" for typical monitoring'), fulfilling the when-to-use and parameter-usage criteria.

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