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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses fan-out across multiple sources, source-specific soft-fail behavior (USPTO sunset, GDELT→GNews fallback), the meaning of sources_used/sources_failed, and that an empty FDA section is expected rather than a bug. It also explains resolved:false behavior for private companies.

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 definition is long and dense, but it is front-loaded with intent and examples, and every clause carries operational meaning (source list, return fields, failure semantics, input normalization). It structures the return contract inline rather than relying on an output schema, so the length is largely justified, though it could be broken into clearer sections.

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 defines the return shape (cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/sources_failed) and explains edge cases like empty source sections and private-company resolution. The agent has everything needed to call the tool and interpret its response 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 value by giving concrete examples ('AAPL', '0000320193', 'Moderna'), explaining name resolution via SEC EDGAR, the resolved_from/resolved_to fields, and the private-company resolved:false behavior — all useful 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 leads with concrete user utterances and states the core operation: 'full cross-source profile of a US public company in ONE parallel call.' It further disambiguates from alternative approaches by explicitly preferring this tool over chaining single-pack SEC/XBRL/news lookups for holistic requests.

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?

It gives an explicit condition ('when the user asks for a holistic view') plus a clear directive ('ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups'). It also tells the agent what input shapes are accepted and how private companies are handled, so routing and failure behavior are clear.

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