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

Annotations already mark readOnly/idempotent/openWorld. The description adds substantial behavioral context: it fans out across multiple sources in parallel; returns `sources_used`/`sources_failed`; explains empty sections are real 'no data' not bugs; defines the private-company fallback (`resolved:false` with an explicit `notes` line); and clarifies that type/value are interchangeable. No contradictions with 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 dense single paragraph. It front-loads the core purpose and the 'ALWAYS PREFER' guidance, but then lists every return field in a long run-on sentence with many parenthetical clauses. The content is valuable but the structure is hard to scan; a bulleted return-fields list would improve it. It is not concise, though each piece mostly earns its place.

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?

No output schema exists, so the description must carry the burden of explaining return values. It does so thoroughly: enumerates all major return sections (recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI), explains sources_used/sources_failed, and handles edge cases (private companies, no data). Minor omissions (e.g., exact units for salary range, ordering of news) exist, but the tool is well specified for an agent to call it 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 covers both params with 100% description coverage and includes enums. The description adds clarification that 'company' and 'ticker' behave identically and that `value` accepts ticker, CIK, or company name in either case, plus examples of zero-padded CIKs. This goes slightly beyond the schema's already thorough descriptions.

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?

States a clear purpose: 'full cross-source profile of a US public company in ONE parallel call.' The verb 'profile' plus explicit examples ('Tell me about X', 'brief me on Tesla') and resource scope distinguish it from single-source lookups and sibling research tools. It also names the preferred use case versus chaining single-pack lookups.

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?

Explicitly directs agents to 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' This provides a clear when-to-use, and names the alternative (single-pack lookups). The 'when' is further illustrated with user-phrase examples. It does not explicitly list when not to use it, but the preference statement implies the boundary.

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