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

Annotations already declare readOnly/openWorld/idempotent/non-destructive behavior, and the description adds substantial context: parallel source fan-out, soft-failure for USPTO, 'empty section is a real no-data, not a bug,' resolution behavior for names, and the private-company resolved:false path. This goes far beyond the annotations and gives agents accurate expectations.

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 every segment earns its place: trigger examples and the preference rule come first, followed by a dense but structured enumeration of sources, return fields, and edge-case semantics. No filler or repetition of structured data is present.

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 compensates by specifying exact return fields, source behavior, failure semantics, and input edge cases. An agent has enough information to invoke the tool correctly and interpret both expected and unexpected 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?

The schema already has 100% description coverage for type and value. The description adds meaningful nuance: accepted value forms (ticker, zero-padded CIK, company name), name resolution via SEC EDGAR, and the fact that type accepts 'company' or 'ticker' interchangeably. This is a solid enhancement over the schema, though the schema already carries the core 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 names a specific verb and resource: 'full cross-source profile of a US public company.' It leads with concrete user phrasings, and explicitly contrasts itself with 'chaining single-pack SEC/XBRL/news lookups,' making it easy for an agent to identify this tool as the holistic-profile option.

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?

Usage conditions are explicit: use it when the user asks for a holistic view, and 'ALWAYS PREFER' it over chaining single-source lookups. It also explains how private companies are handled and that type/value shapes are interchangeable. It does not explicitly name alternative sibling tools such as deep_research or compare_entities, but the guidance is otherwise clear.

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