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

Annotations already mark readOnly/openWorld/idempotent/non-destructive, so the bar is lower, but the description adds substantial context: it names data sources (SEC EDGAR/XBRL, FAERS), mentions off-calendar fiscal year handling, result sorting by primary metric, and citation URI returns. It does not contradict 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 longer than strictly necessary, but every sentence adds value: trigger phrases, type-specific data sources, and the efficiency benefit. The opening is slightly front-loaded with a long list of example phrases, but it's still well-organized and free of filler.

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 absence of an output schema, the description tells the agent what to expect ('paired data + pipeworx:// citation URIs per entity'), the scope (2–5 entities), and the key handling behavior (off-calendar fiscal years). This is sufficient for a tool of this complexity.

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?

Although schema covers both parameters, the description explains what each enum value actually returns: 'company' pulls 10-K revenue/net income/cash/long-term debt, while 'drug' pulls FAERS counts, FDA approvals, and trials. It also clarifies values accept tickers/CIKs or drug names, adding meaning beyond the schema's terse 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 immediately defines side-by-side comparison of 2–5 companies or drugs in one parallel call, with a clear verb ('compare') and resource scope. It also distinguishes itself from sequential single-entity lookups, which separates it from siblings like entity_profile.

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?

It lists concrete trigger phrases ('Compare X and Y', 'X vs Y', 'rank these companies') and explicitly instructs 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' This gives clear when-to-use guidance and names the alternative to avoid, satisfying the dimension.

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