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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable behavioral detail beyond annotations: it lists specific data sources (SEC EDGAR/XBRL, FAERS), mentions handling of off-calendar fiscal years, describes sorting by primary metric, and states the return format (paired data + citation URIs). This fully discloses behavior, with no contradiction to 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 every sentence earns its place. It front-loads with examples, then provides preference guidance, per-type details, fiscal-year handling, sorting behavior, and efficiency benefits. No wasted words; it's well-structured and appropriately sized for 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?

This is a complex tool with two entity types and no output schema. The description covers all essential context: what data is pulled for each type, fiscal-year handling, result sorting, return format, and efficiency. It leaves no meaningful gaps for the intended use case.

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 both parameters, the description adds substantial meaning: for 'type', it explains the different data sources and fiscal-year handling for 'company' vs 'drug'; for 'values', it gives concrete examples (tickers vs names) and explains the min/max. This goes far beyond the schema 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 is extremely clear: it states the tool performs side-by-side comparison of 2–5 companies or drugs in one call. It uses specific verbs like 'compare' and 'rank', and provides trigger examples ('X vs Y', 'which is bigger'). It also explicitly distinguishes from sequential single-pack lookups, making its unique 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?

The description explicitly states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', providing a clear directive for when to use this tool instead of alternatives. It also explains what each type ('company' vs 'drug') does, giving concrete context for choosing the right mode.

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