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

Annotations already declare readOnly/openWorld/idempotent and non-destructive, so the bar is lower, yet the description adds substantial behavioral context beyond them: fan-out happens in ONE parallel call, USPTO PatentsView soft-fails until reactivated, an empty fda_products section is expected for small-molecule-only companies, sources_used/sources_failed distinguish real no-data from bugs, and private companies return resolved:false with a notes line rather than failing. These failure and edge-case semantics are exactly what annotations cannot convey.

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 (~280 words) but appropriately so for an eight-source fan-out tool with multiple edge cases. It is front-loaded: purpose and routing guidance come first, followed by return shape and failure semantics. A few parenthetical-heavy clauses (FDA/Purple Book, H-1B DOL LCA) could be restructured, but every clause carries information and nothing is fluff.

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?

For a high-complexity tool with no output schema, the description covers the full call lifecycle: accepted input shapes (ticker, CIK, name), resolution behavior, return sections with pipeworx URIs, per-source failure semantics, expected-empty sections, and the private-company fallback. Nothing an agent needs to correctly invoke the tool or interpret its output is missing.

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 real value beyond the schema by explaining the resolution pipeline for name inputs (SEC EDGAR company-name match, resolved_from/resolved_to, resolved:false for private companies) and by making explicit that type='company' and type='ticker' are interchangeable with identical value shapes, which the schema only implies via the enum. It doesn't add syntax or format details for value beyond what the schema already states.

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 query phrasings and immediately states the deliverable: 'full cross-source profile of a US public company in ONE parallel call.' It names the resource (US public company), the scope (eight named data sources), and explicitly contrasts itself with chained single-pack SEC/XBRL/news lookups, so an agent can distinguish it from siblings like resolve_entity and 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?

The instruction 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view' is explicit when-to-use guidance naming the alternative pattern and the triggering condition. It also scopes applicability by stating that private companies return resolved:false with a notes line, and notes the expected empty FDA section, so an agent knows when the tool's output is legitimate and when it is insufficient.

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