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

Annotations already declare readOnly/idempotent/openWorld, and the description adds substantial behavior beyond them: the parallel fan-out across sources, sources_used/sources_failed semantics ('an empty section is a real "no data", not a bug'), the private-company resolved:false + notes behavior, the FDA 'none is expected, not a failure' caveat, and the GDELT→GNews fallback. This is exactly the kind of interpretation guidance agents need.

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?

Every sentence carries real content and there is no fluff except the roadmap note 'person/place coming soon', but the entire description is one dense unbroken paragraph with no bullets, headings, or visual scansion. The return-field documentation, while valuable given the missing output schema, is dumped mid-paragraph rather than structured, hurting readability for an agent parsing the text.

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?

For a high-complexity tool with no output schema, the description covers nearly everything needed to invoke and interpret it correctly: return shape (cik, company_name, recent_filings with URIs, fundamentals, patents, contracts, FDA, hiring, news, LEI), empty-result semantics, input formats, resolution behavior, and edge cases (private company, small-molecule-only FDA portfolio). Only minor gaps like rate limits or news time windows remain.

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 coverage is 100%, so baseline is 3; the description earns the extra point by adding meaning beyond the schema: it states that type='company' and type='ticker' behave identically, that value accepts three forms with concrete examples, that names resolve via SEC EDGAR, and how a private-company input behaves at the result level.

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 in 'full cross-source profile of a US public company in ONE parallel call' and reinforces it with query examples ('research Acme', 'company profile for Microsoft'). It is visually distinct from the single-pack lookups it names as alternatives, so an agent can tell what it does without inspecting the schema.

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 gives an explicit trigger ('ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view'). However, it does not name the sibling tools that should win in other cases (e.g., resolve_entity, lookup, scan_competitor_ai_presence), nor does it state when NOT to use this tool, so the exclusion side is left to inference.

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