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

Annotations already signal readOnly/open world/idempotent/non-destructive behavior, and the description adds rich behavioral detail: it fans out across many sources, soft-fails on expired patent APIs, treats empty FDA sections as expected, and resolves private companies to a resolved:false result with an explicit notes line. This goes well beyond the annotations and prepares the agent for realistic failure modes.

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 but information-dense and front-loaded with trigger examples and the core purpose. It is not a model of concise structure, but every clause carries important operational detail, especially around source-specific behavior and expected empty results.

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, fan-out tool with no output schema, the description is unusually complete. It enumerates the major returned sections, explains source failure semantics, documents fallback behavior, distinguishes private vs public companies, and defines valid input forms. An agent has enough context to select and invoke the tool correctly.

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 covers both parameters with clear descriptions, so the baseline is 3. The description adds value by providing concrete examples (AAPL, 0000320193, Moderna), explaining that type values are interchangeable, and describing how names resolve via SEC EDGAR. This is helpful but not a dramatic expansion beyond the schema.

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 verb and resource: it produces a 'full cross-source profile of a US public company in ONE parallel call.' It also gives concrete trigger phrases and contrasts itself with single-pack SEC/XBRL/news lookups, so an agent can distinguish it from similar research/entity tools.

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 clearly says to use this tool 'when the user asks for a holistic view' and to ALWAYS PREFER it over chaining single-pack lookups. It does not name specific sibling tools or provide explicit 'do not use when' exclusions, but the intended usage context is strongly and directly conveyed.

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