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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description builds on this by detailing the internal fan-out across SEC EDGAR, XBRL, USPTO, GDELT/GNews, GLEIF, and specific return fields. It also discloses a known limitation (USPTO patent source sunset May 2025) and fallback behavior, providing rich behavioral context beyond the 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 relatively long but well-organized: it starts with trigger phrases, then states the core purpose, followed by a bullet-like list of return components. Every sentence contributes information; the length is justified by the tool's complexity. Could be pared down slightly, but it avoids 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 (multi-source aggregation) and lack of an output schema, the description comprehensively covers what the tool returns: CIK, company name, filings with URIs, fundamentals with specific fields, patent status with sunset date, news sources, and LEI. It also addresses the input constraint (names not supported) and provides a fallback reference.

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 both parameters having clear descriptions (type only 'company', value accepts ticker or CIK). The description reinforces that names are not supported and references resolve_entity, adding practical value. While the schema already does a good job, the description's examples and context slightly enhance understanding.

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 defines the tool's purpose as generating a holistic profile of a US public company from multiple sources in a single call. It distinguishes itself from sibling tools like resolve_entity and from chaining multiple single-purpose lookups, with explicit instructions to prefer this tool when a broad view is needed.

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 clear usage guidance: it gives trigger examples, states when to use (holistic queries) and when not (if only a name is available, use resolve_entity first). It explicitly says 'ALWAYS PREFER over chaining single-pack lookups', offering direct comparison to alternatives.

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