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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description goes well beyond these by disclosing data sources (SEC EDGAR/XBRL, FAERS), specific metrics (revenue, net income, cash, long-term debt, adverse-event counts), special handling for off-calendar fiscal years, and result sorting behavior.

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 and front-loaded with examples, but every sentence contributes useful selection or invocation guidance. It is slightly longer than strictly necessary, but the added detail about fiscal year handling and data sources earns its place.

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 must explain return behavior, and it does: it notes paired data plus pipeworx:// citation URIs, explains sorting by primary metric, and covers both entity types thoroughly. This gives an agent enough context to use the tool correctly and interpret results.

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?

While schema coverage is 100%, the description adds significant semantic detail: it explains what each type='company' and type='drug' returns, specifies the values array as 2–5 items, and provides concrete examples. It also clarifies output ordering by primary metric, which is not 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 a single call, using concrete trigger phrases like "X vs Y" and "head to head." It also distinguishes itself from likely single-entity siblings like entity_profile by emphasizing parallel comparison.

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?

Explicit guidance is provided: "ALWAYS PREFER over sequential single-pack lookups when comparing entities," and it quantifies the benefit ("Replaces 8–15 sequential lookups"). This clearly tells an agent when to choose this tool over alternatives.

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