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

Annotations provide readOnlyHint, openWorldHint, idempotentHint, destructiveHint false. The description adds substantial behavioral context: it makes one parallel call, fans out to multiple sources, soft-fails for patents due to API sunset, accepts ISO date or relative shorthand, 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 moderately long but efficient. It front-loads with example queries, then concisely details behavior, parameters, and return structure. Every sentence adds value. A very minor reduction for slight verbosity in the source listing, but overall well-structured.

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?

Despite no output schema, the description details return structure: 'changes[] grouped by source + total_changes count + pipeworx:// citation URIs'. It also mentions soft-fail for patents and the parallel call behavior. For a tool with multiple data sources and no output schema, this is complete enough 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?

Schema description coverage is 100%. The description adds meaning beyond the schema: explains `type` is limited to 'company', `value` can be ticker or CIK, and `since` accepts ISO date or relative shorthand with a recommendation ('30d' or '1m'). It also clarifies the window semantics in context.

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'), then clearly states it's a 'change feed for a company in the last N days/weeks/months in ONE parallel call'. It specifies data sources (SEC EDGAR, GDELT→GNews, USPTO) and explicitly distinguishes from sibling `entity_profile`. The purpose is unmistakable.

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 tells when to use `entity_profile` instead ('when you want the static profile... regardless of window'). It also clarifies the tool handles multiple sources in one call, with fallback behavior (GDELT→GNews). No mention of when not to use beyond the sibling alternative, but that is sufficient for clear guidance.

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