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

Beyond the readOnly/idempotent hints, the description transparently explains data sources (SEC EDGAR/XBRL, FAERS), fiscal-year handling, sorting by primary metric, and the return format (paired data + citation URIs). This adds substantial behavioral context without contradicting any 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 densely packed with useful information and front-loaded with trigger phrases, making it easy for an agent to identify matching queries. It is longer than the typical description, but every clause serves a purpose, so it earns its length.

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 tool with no output schema, the description sufficiently explains what will be returned, how results are ordered, and the benefit over multiple calls. It covers all essential aspects for correct invocation and interpretation of results.

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 documents both parameters at 100% coverage, but the description enriches the 'type' parameter by explaining exactly what each enum value retrieves and provides concrete examples for 'values'. This adds practical meaning beyond the schema's plain descriptions.

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 names the action ('side-by-side comparison'), specifies the resource ('companies or drugs'), and defines the scope (2–5 entities in one parallel call). It also distinguishes from sibling tools by explicitly stating it should be preferred over sequential single-pack 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?

Triggers and example phrasings are provided ('Compare X and Y', 'which is bigger', 'rank these companies'), and the description clearly states when to use this tool: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It also gives contextual details about entity types and what metrics each type retrieves.

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