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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable context beyond that: it fans out to multiple sources, reports sources_used/sources_failed, and explains that empty sections are real 'no data' states, not bugs. It also discloses that a private company returns resolved:false with a notes line rather than a failure. The only minor gap is not describing latency or rate-limit behavior, but the parallel fan-out nature is clear.

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 dense but front-loaded with example queries and the 'ALWAYS PREFER' directive, which is the most important usage guidance. While it is long, every sentence carries operational information: sources, return fields, input normalization, and failure semantics. It would benefit from a little structural trimming, but it earns its length given 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 no output schema, the description compensates well by listing return components (cik, company_name, recent_filings with URIs, fundamentals, etc.) and explaining failure semantics. It also covers the input space thoroughly. The only missing piece is a brief note about typical response size or latency, which would help agents set expectations, but the tool is complex and this is a minor gap.

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 schema documents both parameters fully. The description reinforces the semantics by enumerating accepted input shapes and noting that type accepts 'company' or 'ticker' interchangeably — a nuance explicitly stated in the schema enum description but usefully echoed. It adds the resolution behavior (resolved_from/resolved_to) that isn't in the schema, which helps the agent understand what to expect.

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 states a clear verb-resource relationship: it produces a full cross-source profile of a US public company in a single parallel call. It enumerates the sources (SEC, XBRL, USPTO, USAspending, FDA Purple Book, DOL LCA, news, GLEIF) and return components, distinguishing it from narrow single-source lookups.

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 explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also clarifies accepted input forms (ticker, CIK, company name) and what happens for private companies (resolved:false with a notes line). This gives the agent clear decision rules for when to use this tool versus alternatives.

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