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

Annotations state readOnly/openWorld/idempotent. The description adds significant behavioral context: fans out across multiple sources, GDELT→GNews fallback on rate-limit/5xx, USPTO soft-fails due to PatentsView sunset, and returns changes[] grouped by source. This is exactly the kind of extra transparency that helps agents anticipate side effects and failure modes.

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 well-structured: front-loaded with intent-revealing examples, then a clear summary, followed by source details, parameter guidance, output shape, and an alternative. Every sentence adds value; no filler or 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?

For a multi-source aggregation tool with no output schema, the description covers all necessary context: sources, fallback logic, API sun-setting caveat, date formats, output structure (changes[], total_changes, citation URIs), and alternative tool usage. 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 coverage is 100%, but the description goes further: it explains `since` accepts ISO or relative shorthand with examples and recommends '30d' or '1m' for typical monitoring, and clarifies `value` can be a ticker or zero-padded CIK. This enriches parameter understanding 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 provides specific verbs and resources: 'change feed for a company in the last N days/weeks/months in ONE parallel call' and lists fan-out sources (SEC EDGAR, GDELT/GNews, USPTO). It clearly distinguishes from sibling entity_profile by stating when to use that instead.

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?

Includes realistic example natural-language queries ('What's new with X'), gives parameter usage guidance ('Use "30d" or "1m" for typical monitoring'), and explicitly names an alternative tool: 'Use entity_profile instead when you want the static profile.' This is strong when/when-not guidance.

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