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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond these hints: it fans out to SEC EDGAR, GDELT, GNews, and USPTO; explains the GDELT→GNews fallback on rate-limits/5xx; discloses the PatentsView API sunset causing soft-fail; and states it makes 'ONE parallel call' (performance behavior). This goes well beyond annotation basics.

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 dense but every sentence earns its place: it starts with natural-language examples, explains sources and fallback behavior, covers `since` formats, summarizes the return shape, and gives an explicit pointer to the sibling tool. It is front-loaded with intent and avoids filler.

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?

For a complex tool with multiple upstream APIs and fallback logic, the description is remarkably complete. It discloses the exact return structure (changes[] grouped by source, total_changes, pipeworx:// citation URIs), the behavior on rate limits/5xx, the USPTO soft-fail, and the alternative for static views. No output schema exists, but the description provides sufficient information to understand what will be returned.

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%, so the baseline is 3. The description mostly reiterates what the schema already says about `since` (ISO vs relative shorthand) and `value` (ticker/CIK). It adds a minor recommendation ('Use "30d" or "1m" for typical monitoring') but does not introduce new semantic meaning for any parameter.

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 multiple natural-language paraphrases ('What's new with X', 'latest on Y') and clearly states it's a 'change feed for a company in the last N days/weeks/months in ONE parallel call.' It explicitly distinguishes itself from the sibling tool entity_profile ('Use entity_profile instead when you want the static profile'), demonstrating a specific verb+resource+scope with clear 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 gives explicit when-to-use context with concrete query examples and window options. It names the key alternative ('entity_profile') and explains why you'd choose that instead ('static profile... regardless of window'). It also describes the fallback behavior across data sources, providing clear guidance on what the tool is suited for.

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