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

Annotations already indicate a safe read-only, idempotent operation. The description goes beyond by explaining data sources (SEC EDGAR/XBRL, FAERS, FDA), special handling of off-calendar fiscal years, sorting behavior, and that results include paired data + citation URIs. This adds rich context without contradicting the 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 trigger phrases and purpose, then systematically explains type-specific behavior, sorting, and output format. There is no fluff or redundancy; it's a well-structured, information-rich paragraph.

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 and the absence of an output schema, the description covers all critical aspects: when to use, what it does, per-type data sources, sorting, return format, and even a performance note (replaces 8–15 sequential lookups). The agent has enough context to invoke it correctly without needing additional clarification.

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%, but the description adds meaning by explaining what each type parameter does (company pulls financial metrics, drug pulls adverse-event and trial counts) and provides concrete examples for the values array. This goes well beyond the schema's own parameter 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 opens with explicit trigger phrases and states the core function: "side-by-side comparison of 2–5 companies or drugs in ONE parallel call." It clearly distinguishes from siblings by saying "ALWAYS PREFER over sequential single-pack lookups when comparing entities," making it unambiguous when this tool is the right choice.

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 provides explicit when-to-use guidance through trigger phrases and a strong directive to prefer this tool over sequential single-pack lookups. It also clarifies what each type ('company' vs 'drug') retrieves, giving the agent enough context to decide when this tool is appropriate versus alternatives.

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