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

Beyond the readOnly/idempotent annotations, the description discloses specific data pulled for each type (10-K financials for companies, FAERS/FDA/trial counts for drugs), handles off-calendar fiscal years, sorts by primary metric, and mentions citation URIs in returns. This provides rich behavioral context.

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 the core purpose and trigger phrases, then succinctly covers type-specific details, sorting, output, and efficiency. Every sentence earns its place without unnecessary fluff, given the tool's complexity.

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 still explains return values (paired data + citation URIs). It covers data sources, entity types, sorting behavior, and parallels the schema's constraints (2–5 items). The tool is fully comprehensible without needing to consult other resources.

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?

Although schema coverage is 100%, the description adds substantial meaning: type='company' vs 'drug' behavior, examples of values (['AAPL','MSFT'], ['ozempic','mounjaro']), and details on what data is pulled for each type. This goes far beyond the schema's basic enum and array 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 clearly states the tool performs side-by-side comparison of 2–5 companies or drugs in one parallel call, with explicit trigger phrases like 'compare X and Y' and 'head to head'. It distinguishes itself from single-entity lookups by emphasizing 'ALWAYS PREFER 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?

Provides explicit guidance on when to use this tool: when comparing entities, it should be preferred over sequential single-pack lookups. It also gives concrete examples of user intents and notes it replaces 8–15 sequential lookups, reinforcing the use case.

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