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

Annotations already declare readOnlyHint/openWorldHint/idempotentHint, and the description adds substantial behavioral depth well beyond that: USPTO soft-fail behavior, empty sections meaning 'real no data' not a bug, private companies returning resolved:false with a notes line, and a sources_used/sources_failed mechanism. It also discloses the parallel fan-out across SEC, XBRL, USPTO, USAspending, FDA Purple Book, DOL LCA, GDELT/GNews, and GLEIF. This is rich, honest behavioral disclosure.

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 it is dense with necessary information for a complex multi-source tool. It front-loads usage examples and the 'ALWAYS PREFER' directive, then proceeds through scope, fan-out sources, return sections, edge cases, and input flexibility. No sentence is filler; length is justified by the tool's complexity.

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 to fall back on, the description effectively serves as the return contract: it enumerates cik, company_name, resolved_from/resolved_to, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, and sources_used/sources_failed. It also covers failure modes and the private-company case. Given the tool's complexity and absence of an output schema, this description is complete enough for an agent to call and interpret the result 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?

The schema already covers both parameters at 100%, so the baseline is 3. The description adds real value on top: type is explicitly noted as accepting 'company' or 'ticker' interchangeably, and value is clarified to accept a ticker, zero-padded CIK, or company name with name resolution via SEC EDGAR. Concrete examples ('AAPL', '0000320193', 'Moderna') further sharpen the 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 opens with concrete user phrasings and states a specific verb-resource pair: 'full cross-source profile of a US public company in ONE parallel call.' It clearly distinguishes itself from chained single-source lookups and names sibling-style alternatives like SEC/XBRL/news lookups. This is a model of a purpose-stated description.

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 explicitly tells the agent when to use this tool: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It gives many trigger examples such as 'tell me about X' and 'brief me on Tesla.' However, it does not address when not to use it or how it compares to siblings like compare_entities, resolve_entity, or deep_research, so it stops just short of full alternative-routing guidance.

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