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

Beyond the readOnly/idempotent annotations, the description discloses data sources (SEC EDGAR/XBRL, FAERS, FDA approvals), off-calendar fiscal year handling, result sorting by primary metric, and output structure (paired data + citation URIs). This is rich behavioral context that helps the agent predict the tool's actions and output. No contradiction with 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 dense but well-structured: it front-loads trigger phrases and the core function, then gives usage guidance, type-specific details, and output characteristics. Every sentence adds value, though it is longer than the minimal two-sentence ideal, so it merits a 4 rather than a 5.

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 compensates by explaining that results are sorted by primary metric and that paired data plus citation URIs are returned. It covers data sources and edge cases (e.g., off-calendar fiscal years) adequately for the tool's complexity. It doesn't detail exact response structure or error conditions, but the level of completeness is appropriate.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds significant meaning: it explains what data each 'type' value returns (10-K financials for company, adverse-event counts for drug), and clarifies the expected format for 'values' (tickers/CIKs vs. drug names) with examples. This goes beyond the schema's descriptions, earning a 4.

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 explicitly states the tool performs side-by-side comparisons of 2–5 companies or drugs in a single call, with specific natural-language triggers like 'X vs Y' and 'which is bigger'. It clearly distinguishes itself from sequential lookups by emphasizing 'ONE parallel call', making its purpose 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?

It provides an explicit usage rule: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities,' which gives clear when-to-use guidance. However, it does not name specific alternative sibling tools or state when not to use it, so it falls slightly short of a 5.

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