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

Beyond the readOnly/openWorld/idempotent annotations, the description explains data sources (SEC EDGAR/XBRL, FAERS), handles off-calendar fiscal years, sorts results by primary metric, and returns paired data plus citation URIs. This rich behavioral context is not provided by the annotations and significantly aids the agent in understanding the tool's side effects and output.

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 most critical purpose (side-by-side comparison in one call) and then efficiently packs details on data sources, sorting, and return format. Every sentence contributes essential context, with no fluff or repetition.

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?

Given the tool has no output schema, the description compensates by stating it returns paired data and citation URIs. It covers key behavioral aspects for both entity types, addresses fiscal year handling, and notes that it replaces many sequential lookups. This makes the description sufficient for an agent to understand what the tool does and what to expect from it.

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 the schema already describes the parameters, the tool description adds substantial meaning: it explains what type='company' vs 'drug' retrieve and gives concrete examples (tickers like AAPL, MSFT; drug names like ozempic, mounjaro) for the values array. This goes well beyond the schema's basic descriptions, fully compensating for any residual ambiguity.

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 comparisons of 2–5 companies or drugs in one parallel call. It provides example queries and explicitly distinguishes itself from sequential single-entity lookups, making its purpose and scope unmistakable.

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?

The description gives explicit when-to-use guidance ('ALWAYS PREFER over sequential single-pack lookups when comparing entities'), lists trigger phrases like 'X vs Y' and 'which is bigger', and details the type-specific behavior for 'company' and 'drug'. It effectively communicates when this tool is the right choice over alternatives.

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