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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds valuable context: data sources (SEC EDGAR/XBRL, FAERS/FDA), handling of off-calendar fiscal years, sorting by primary metric, and return of citation URIs. This goes beyond the annotations without contradicting them.

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: starting with example phrasings, then core function, then type-specific data sources and output behavior. Every sentence adds relevant information, though it is longer than average; still, it remains 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?

For a tool with no output schema, the description effectively communicates return format (paired data + citation URIs), sorting behavior, and the fact it consolidates many lookups. It lacks explicit error-handling info but covers the essential aspects of invocation and expected output.

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% (both type and values are described), so baseline is 3. The description adds meaning by detailing what each 'type' pulls (10-K financials for companies; FAERS/FDA data for drugs), and it also clarifies the values count and examples. This enriches parameter understanding beyond the schema.

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 a single parallel call, with specific verbs ('compare', 'rank') and resource types. It distinguishes itself from siblings by emphasizing its role for comparative queries and noting it replaces sequential 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?

Explicitly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', giving a clear when-to-use directive. It also mentions it handles both company and drug comparisons. However, it does not explicitly name alternative tools or state when NOT to use it (e.g., for single-entity lookups).

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