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

The description adds rich behavioral context beyond the annotations: it explains the data sources (SEC EDGAR, GDELT→GNews fallback, USPTO with soft-fail), date parsing, return structure (changes grouped by source, total_changes, citation URIs), and the multi-tool parallel call. No contradictions with annotations (readOnlyHint, openWorldHint, idempotentHint, non-destructive are all consistent).

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 concise and well-structured: it opens with illustrative examples, states the core function, details sources and fallbacks, explains the parameter, and explicitly differentiates a sibling. Every sentence adds value with no redundancy.

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?

Given the tool's complexity (multiple sources, fallback logic, date handling, no output schema), the description is remarkably complete. It covers all key behaviors: source selection, fallback behavior, date format flexibility, output structure, and explicit comparison with entity_profile. An agent can confidently decide to invoke this tool based on this description.

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 schema already documents parameters well. The description adds practical context (e.g., relative date shorthands, ticker vs CIK, typical monitoring window), but the marginal benefit is moderate. Baseline 3 is appropriate.

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 clearly states it is a 'change feed for a company in the last N days/weeks/months' and distinguishes it from the sibling tool 'entity_profile' which provides a static profile. It also covers the multi-source fan-out, making the tool's purpose very specific and actionable.

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 the agent when to use this tool (for temporal changes) and when not to ('Use entity_profile instead when you want the static profile'). It also provides example queries and guidance on the 'since' parameter, including typical values like '30d' or '1m'.

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