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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds substantial behavioral context beyond annotations: the parallel fan-out across multiple sources, specific return fields (filings, fundamentals, patents, news, LEI), the USPTO API sunset and soft-fail behavior, GDELT→GNews fallback, and the zero-padded CIK requirement. This enriches the agent's understanding of execution and output.

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 packed with useful information: example queries, data sources, return fields, caveats, and parameter guidance. It is structured with clauses and semicolons, and every sentence contributes value. While not as lean as some, the length is justified by the tool's complexity.

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 (multiple sources, fallbacks, specific output fields), the description is exceptionally complete. It documents return structure (cik, filings with URIs, fundamentals, patents, news, LEI), input constraints, API sunset, and fallback behavior. With no output schema, the description fully compensates, leaving no major gaps.

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 value by providing concrete examples ('AAPL', '0000320193'), explaining the zero-padding requirement, and clarifying the 'company' enum limitation. This goes beyond the schema's field descriptions, justifying a 4.

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 explicitly states the tool's function: 'full cross-source profile of a US public company in ONE parallel call.' It provides clear example user intents and lists specific data sources (SEC EDGAR, XBRL, USPTO, news, GLEIF) and return fields, making the purpose unmistakable. It also distinguishes from siblings via the 'ALWAYS PREFER over chaining single-pack lookups' directive.

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 guidance is explicit: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also states when not to use (names not supported) and directs to resolve_entity first if only a name is available. This provides clear when-to-use and when-not-to-use guidance.

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