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

Annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint false) indicate safety. The description adds significant behavioral context: parallel fan-out to multiple APIs, fallback logic, soft-fail for USPTO, accepted date formats, and the structure of the response (grouped changes, citations). This goes well beyond 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 a single dense paragraph that front-loads with example queries, then details sources and format. While efficient and informative, it could benefit from slight structure (e.g., bullet points) for easier scanning. However, every sentence serves a purpose.

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?

With three parameters, high schema coverage, no output schema, and rich annotations, the description fully equips an agent: it explains what the tool does, how to use parameters, what to expect in the response (structured changes, citations), fallbacks, and when to choose an alternative. 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 for all three parameters. The description adds value by providing concrete examples for `since` ('7d', '30d', '3m', '1y') and a recommendation ('Use 30d or 1m for typical monitoring'), and clarifies `value` accepts ticker or CIK. This is meaningful guidance 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 directly states the tool provides a change feed for a company in a time window, with specific examples ('What's new with X', 'latest on Y'). It lists the data sources (SEC EDGAR, GDELT→GNews, USPTO) and explicitly distinguishes from the sibling tool entity_profile, which provides static profiles. This is a specific verb+resource 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 usage context with example queries, explains fallback behavior (GDELT→GNews), and provides a clear when-not-to-use directive: 'Use entity_profile instead when you want the static profile...' This leaves no ambiguity about when to invoke this tool versus alternatives.

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