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

Annotations already cover readOnly/openWorld/idempotent, and the description adds substantial behavior: fan-out across sources, soft-failure of patents, meaning of empty sections, resolved:false for private companies, and source success/failure reporting. This goes far beyond the structured annotations.

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 densely informative, and it front-loads the core purpose with examples before diving into field-by-field details. It could be easier to parse with bullet structure, but every sentence contributes meaningful operational detail.

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 carries the full burden of explaining return values, and it does: it lists each returned section, notes fallback behavior, explains empty sections, and clarifies failure modes. An agent has enough context to invoke this 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% and the description largely restates the schema's parameter guidance: type accepts 'company' or 'ticker' interchangeably and value can be a ticker, zero-padded CIK, or name. The added examples and SEC EDGAR resolution note are helpful but not a major semantic step 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?

States a specific verb and resource: produce a 'full cross-source profile of a US public company' in one call, with concrete example phrasings. It differentiates from chaining single-pack SEC/XBRL/news lookups, but does not explicitly distinguish itself from related sibling tools like deep_research or compare_entities.

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?

Provides explicit trigger phrasings ('Tell me about X', 'research Acme', 'brief me on Tesla') and an explicit rule: ALWAYS PREFER over chaining single-pack lookups for a holistic view. It does not discuss when to prefer alternatives like deep_research or compare_entities, so the exclusion guidance is incomplete.

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