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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses source-failure behavior ('USPTO PatentsView API sunset May 2025 — soft-fails'), expected empty sections ('a company with only small-molecule/generic drugs will show none here'), and 'sources_used'/'sources_failed' semantics. It also explains the private-company `resolved:false` result rather than a bare failure. No annotation contradiction.

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 information-dense and front-loaded with a strong usage directive, and every sentence earns its place given the tool's complexity. However, it is a single long paragraph; structured line breaks or scannable sections would improve readability without cutting content. Minor deduction for density, not for irrelevance.

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?

With no output schema, the description fully compensates by enumerating every return section (cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI) and explaining failure/absence semantics. It also covers input forms, name resolution, and private-company behavior, leaving no obvious gap for correct invocation.

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?

Even though schema coverage is 100%, the description adds substantial meaning: it gives concrete examples for `value` (ticker, zero-padded CIK, company name), explains name resolution via SEC EDGAR, and clarifies that `type` accepts 'company' or 'ticker' interchangeably with identical behavior. This is exactly the formatting nuance an agent needs 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 clearly states the tool produces a 'full cross-source profile of a US public company in ONE parallel call' and grounds it with example queries like 'tell me about X' and 'company profile for Microsoft.' It further distinguishes the tool from single-pack SEC/XBRL/news lookups, which separates it from siblings like resolve_entity and compare_entities.

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 says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving a clear when-to-use rule and an alternative to avoid. It also clarifies when a name resolves vs. a private company returning resolved:false, which helps route the agent to the right action.

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