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

Annotations already declare readOnly/openWorld/idempotent, and the description adds substantial behavioral detail beyond that: it discloses data sources (SEC EDGAR/XBRL, FAERS, FDA), handles off-calendar fiscal years (AAPL, NVDA), sorts results by primary metric, and returns citation URIs. This gives the agent a clear picture of what happens during execution.

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 information-dense but well-structured: it starts with trigger phrases, then states the core function, then provides type-specific details, sorting behavior, and output format. Every sentence earns its place, with no redundant or filler content.

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's moderate complexity (two parameters, no output schema), the description covers key aspects: what it returns (paired data + citation URIs), how results are ordered, and what metrics are produced per type. It lacks explicit response structure details, but the description is sufficient for an agent to select and invoke the tool correctly.

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 baseline is 3. The description enriches parameter meaning by explaining what each 'type' value retrieves (company: 10-K financial metrics; drug: FAERS counts, approvals, trials) and clarifies the 'values' parameter with examples. This goes beyond the bare enum/description in 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 one parallel call, with explicit trigger phrases ('X vs Y', 'which is bigger') and a distinct resource (companies/drugs). It distinguishes itself from siblings by emphasizing it replaces sequential lookups, making its purpose specific and non-overlapping.

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 guidance on when to use the tool: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It names the alternative approach but does not explicitly exclude cases like single-entity lookups or mention a specific sibling tool as a fallback. Thus clear context with no explicit when-not exclusions.

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