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

Beyond the annotations (readOnlyHint, idempotentHint, etc.), the description discloses important behavior: fans out to multiple sources, GDELT preferred with GNews fallback on rate limiting or 5xx, and the PatentsView API sunset causing USPTO to soft-fail until reactivated. It also states the return structure and citation URIs, adding substantive transparency about how the tool behaves.

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 well-structured and front-loaded: begin with user-intent phrases, then a one-line definition, followed by source details, parameter examples, return format, and an alternative tool. Every sentence adds value and the length is appropriate for a tool with multiple data sources and fallback behavior.

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?

There is no output schema, so the description responsibly explains the return shape ('changes[] grouped by source + total_changes count + pipeworx:// citation URIs'). It also covers input nuances, fallback behavior, and the relevant alternative, making the tool fully usable without needing to infer details beyond annotations and schema.

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 documents all three parameters (100% coverage), so the baseline is 3. The description adds practical value by giving explicit examples of the `since` parameter ('2026-04-01', '7d', '30d', '3m', '1y') and recommending '30d' or '1m' for typical monitoring, clarifying how the parameter maps to the source windows.

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 opens with intent-matching paraphrases and then clearly states it is a 'change feed for a company in the last N days/weeks/months' that fans out to SEC EDGAR, GDELT/GNews, and USPTO. This specific verb+resource definition distinguishes it from the sibling tool entity_profile, which is explicitly called out 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 provides explicit when-to-use context through example queries and states 'Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.' This directly guides tool selection and names the alternative, exceeding the baseline for usage guidance.

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