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

The description goes far beyond the readOnly/openWorld/idempotent annotations, detailing the parallel fan-out across many sources, the meaning of sources_used/sources_failed, the expected-empty behavior for certain company types, and the resolved:false path for private companies. This gives an agent a realistic model of what the call returns and what counts as success or null data.

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 and the tool is complex, so the length is mostly justified. It front-loads trigger phrases and the core 'one parallel call' value proposition, then organizes output semantics and edge cases. The repeated mention of type interchangeability is slightly redundant with the schema, but the overall structure earns its place.

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 no output schema, the description provides remarkably complete context: input variants, source coverage, resolved/unresolved behavior, source-failure semantics, expected empty sections, and a note about patents API soft-failing. An agent has what it needs to invoke the tool correctly and interpret results.

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 both parameters are already documented. The description adds meaningful behavior: type values are interchangeable, value can be ticker/CIK/name, and names resolve through SEC EDGAR's company-name match. This extends the schema rather than merely repeating it.

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 precise action: produce a full cross-source profile of a US public company in one parallel call. It clearly differentiates itself from narrower single-source lookups and lists the accepted input forms (ticker, CIK, name).

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 explicit trigger scenarios ("Tell me about X", "research Acme", "brief me on Tesla") and instructs to prefer this over chaining single-pack SEC/XBRL/news lookups for holistic questions. It does not name specific sibling alternatives or state when NOT to use it, but the guidance is strong and actionable.

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