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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds substantial behavioral context: fan-out across sources, sources_used/sources_failed semantics, empty sections meaning real no-data rather than failure, the private-company resolved:false case, an API sunset soft-fail, and the expected empty FDA section for small-molecule companies. This is far beyond what annotations provide.

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 dense, with every clause adding distinct information: examples, scope, preference rule, source list, return fields, edge cases. It is front-loaded with the most important action guidance ("ALWAYS PREFER") and uses inline code and semicolons to compress detail. Minor redundancy exists between the query examples and the subsequent summary, but overall it earns its length.

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 and the absence of an output schema, the description covers everything an agent needs: input variants, resolution behavior, return sections (including pipeworx URIs), source success/failure reporting, no-data expectations, and known API issues. No critical operational detail is missing.

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 the baseline is 3. The description adds useful semantics beyond the schema: zero-padded CIK format, name resolution via SEC EDGAR, resolved_from/resolved_to behavior when a name is passed, and the private-company outcome. The interchangeability of type='company' and 'ticker' is also reinforced with examples.

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 and resource: "full cross-source profile of a US public company in ONE parallel call." It clearly distinguishes the tool from chained single-pack lookups by instructing "ALWAYS PREFER" when a holistic view is requested, which separates it from siblings like deep_research or resolve_entity.

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 explicitly says to prefer this tool over chaining SEC/XBRL/news lookups when the user wants a holistic company view, and it explains the accepted input forms (ticker, CIK, name). It does not explicitly exclude non-US companies or name sibling tools like deep_research/compare_entities as alternatives, but the context is clear enough for most selection decisions.

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