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

Beyond the readOnlyHint/openWorldHint/idempotentHint annotations, the description details the fan-out across sources, the meaning of sources_used/sources_failed, that empty sections indicate real absence of data, the resolved:false + notes behavior for private companies, and resolved_from/resolved_to for name inputs. This gives the agent concrete expectations about output structure and edge cases without contradicting the 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 dense and front-loaded with trigger examples, and most sentences carry useful information. However, it runs as one long paragraph and repeats some schema details (e.g., type interchangeability and value shapes), so it is not maximally concise or structurally optimized.

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 complex tool with no output schema, the description thoroughly covers input variants, output sections with pipeworx URIs, source success/failure semantics, and edge cases like private companies. Nothing an agent needs to select and invoke the tool correctly 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?

The input schema already provides 100% description coverage for both parameters, so the baseline is 3. The description adds meaningful nuance — names resolve via SEC EDGAR's company-name match, ticker/CIK/name are all valid regardless of type, and private companies yield resolved:false — which goes beyond the schema's explicit text and justifies a higher score.

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 specific action — producing a full cross-source profile of a US public company in one parallel call — and reinforces it with concrete trigger phrases like 'Tell me about X' and 'brief me on Tesla.' It clearly distinguishes itself from single-pack SEC/XBRL/news lookups by emphasizing the holistic, cross-source scope, even if it does not explicitly contrast with sibling tools like resolve_entity or 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?

It explicitly instructs 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving a clear when-to-use directive with example phrasings. However, it does not provide an explicit when-not-to-use condition or directly mention alternative sibling tools such as compare_entities, so the guidance is clear but not fully exclusionary.

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