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

Annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) already establish the safety profile, and the description adds substantial behavior beyond them: it discloses cross-source fan-out, the GDELT→GNews fallback, that empty sections mean real 'no data' not a bug, and that private companies return resolved:false with an explicit notes line rather than a bare failure.

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 long but front-loaded: user intents, core purpose, and routing preference come first, followed by source list, return shape, and edge cases. The middle source enumeration is one dense run-on sentence with parentheticals, which hurts scannability, but every segment earns its place and nothing is redundant.

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 (fan-out across 8+ sources) and the absence of an output schema, the description carries the full burden of explaining return values — and it does: cik, company_name, resolved_from/to, recent_filings URIs, fundamentals fields, sources_used/sources_failed. It also sets expectations for edge cases (private companies, small-molecule-only drug companies) that would otherwise look like bugs.

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% — the schema already documents both params with examples ('AAPL', '0000320193', 'Moderna') and the interchangeability of type values. The description reinforces this but adds little parameter-level meaning beyond the schema; the resolved_from/resolved_to detail describes output semantics rather than input semantics.

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 states a specific verb+resource: 'full cross-source profile of a US public company in ONE parallel call.' It names the fan-out sources, the return shape, and the accepted input forms, and it differentiates from siblings like resolve_entity and deep_research by positioning itself as the holistic single-call profile tool.

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?

Explicit routing guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' The user-intent examples at the start ('Tell me about X', 'brief me on Tesla') clarify exactly which queries trigger this tool, and the 'person/place coming soon' note scopes it to companies.

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