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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds substantial non-obvious context: fan-out is parallel and consolidated in one call, sources_used/sources_failed signal real no-data results, an empty fda_products section is expected for small-molecule-only companies, news uses GDELT→GNews fallback, and private companies return resolved:false with an explicit notes line instead of a bare failure. No contradiction with 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 information-dense, and every clause carries operational meaning. Examples and the priority directive are front-loaded, though the body is one sprawling paragraph with many parentheticals; slight restructuring into bullets would improve scanability without losing content.

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?

There is no output schema, so the description correctly carries the burden of explaining return values. It enumerates the result sections (cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/sources_failed), explains URI formats, and covers edge cases like expected empty FDA results and private-company behavior. This is complete enough for an agent to call and interpret the tool reliably.

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 description coverage is 100%, so the baseline is 3. The description goes beyond by explaining that type values "company" and "ticker" are interchangeable and accept the same value shapes, that names resolve via SEC EDGAR company-name match, and that results include resolved_from/resolved_to when a name was supplied. This adds real semantic guidance 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?

The description opens with concrete user intents like "Tell me about X" and "company profile for Microsoft," then defines the operation as a "full cross-source profile of a US public company in ONE parallel call." It clearly distinguishes this from single-source lookup chains by naming the fan-out across SEC, XBRL, patents, contracts, FDA, hiring, news, and GLEIF.

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 "ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view," giving a direct when-to-use instruction and naming the alternative approach. It also clarifies accepted inputs and how private-company results behave, so an agent knows when this tool will fail gracefully rather than error.

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