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

Annotations already establish readOnly, openWorld, idempotent, and non-destructive, so the burden is lower. The description adds substantial behavioral detail: it fans out across multiple sources, returns 'sources_used'/'sources_failed', soft-fails on the patents source, treats empty sections as real no-data, and returns 'resolved:false' with an explicit notes line for private companies. This goes well beyond the annotations and is highly valuable to an agent.

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 and dense, but nearly every clause earns its place, covering examples, usage preference, source fan-out, return fields, edge cases, and parameter behavior. It is front-loaded with user intents and a routing directive. It could be slightly improved with bullet formatting or shorter sentences, but it is not padded or irrelevant.

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 present, the description carries the full burden of explaining what the tool returns, and it delivers: it enumerates recent_filings, fundamentals, patents, federal_contracts, fda_products, h1b, news, LEI, and sources_used/failed. It also explains fallback behavior and the expected result for private companies. An agent has enough information to call this tool correctly and interpret unusual outcomes.

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 documents both parameters with descriptions, so the baseline is 3. The description adds meaningful semantic nuance: 'type' accepts 'company' or 'ticker' interchangeably, 'value' can be a ticker, zero-padded CIK, or company name, names resolve via SEC EDGAR, and a private company is handled gracefully. These details significantly reduce the chance of misusing the parameters.

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 clearly identifies the tool as a holistic, cross-source profile builder for US public companies, with concrete example prompts to anchor the intent. It differentiates itself from single-pack SEC/XBRL/news lookups and implies it is distinct from siblings like compare_entities or resolve_entity. The resource, verb, and scope are all explicit.

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?

The description is unusually explicit: 'ALWAYS PREFER over chaining single-pack SEC/XBRML/news lookups when the user asks for a holistic view.' It also states what input forms are accepted, what happens for private companies, and when an empty section is expected rather than an error. This effectively routes an agent toward the correct tool and sets expectations around fallback behavior.

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