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

Despite annotations already marking it read-only and idempotent, the description adds substantial behavioral context: it details data sources (SEC EDGAR/XBRL, FAERS), fiscal year handling (AAPL Sep, NVDA Jan), sorting by primary metric, and that output includes paired data and citation URIs. 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 somewhat long but well-organized: trigger phrases first, then behavior, then data sources, then output. Each sentence adds value, and the front-loading of example queries makes it immediately actionable. A slightly tighter structure could earn a 5, but it remains efficient.

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 covers both input and output well: it explains what metrics are pulled for each type, how they're sorted, that results are paired, and includes citation URIs. It also addresses edge cases like off-calendar fiscal years, making it highly complete for a tool with only two simple parameters.

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% for both parameters, but the description enriches meaning by explaining what 'company' vs 'drug' types return (e.g., 10-K revenue vs FAERS counts) and giving concrete value examples (tickers/CIKs for company, drug names for drug). This goes beyond the schema's basic 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.' It includes concrete trigger phrases ('X vs Y', 'which is bigger') and distinguishes itself from siblings by explicitly noting it replaces 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: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' Describes the exact scenarios (comparison, ranking, head-to-head) and even differentiates between company and drug use cases, making it clear when this tool is the right choice.

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