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

Annotations already mark the tool read-only and idempotent, and the description adds substantial behavioral context: parallel fan-out across sources, sources_used/sources_failed semantics, empty sections meaning real absence of data, private-company resolved:false behavior, and USPTO API sunset soft-fail. This far exceeds the annotation baseline with no contradictions.

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 front-loaded with triggers and the core directive, then densely packs source and return information. It is information-dense and mostly earns its length, but it runs as one long semicolon-heavy paragraph and partially duplicates parameter semantics already present in the schema.

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, the description carries the full burden of explaining return values and edge cases, and it does so comprehensively: each output section is named, source-specific caveats are provided, and failure/empty states are explicitly handled. Nothing an agent needs to invoke this complex tool correctly appears to be 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?

Input schema coverage is 100% and already documents both parameters well, giving a baseline of 3. The description adds helpful concrete examples (ticker 'AAPL', CIK '0000320193', name 'Moderna'), clarifies that type values behave identically, and notes future person/place support, but much of this is corroboration rather than entirely new parameter meaning.

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 full cross-source profile for US public companies, with example queries and the key phrase 'full cross-source profile ... in ONE parallel call.' It is specific about the resource and scope, but it does not explicitly name sibling tools like resolve_entity or compare_entities to differentiate them, so it stops short of a 5.

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 gives explicit triggering conditions ('Tell me about X', 'brief me on Tesla', 'when the user asks for a holistic view') and an explicit preference directive: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups.' This tells an agent exactly when to select this tool and what to favor it over, which is strong usage guidance.

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