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

Beyond annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses concrete behavioral details: data sources (SEC EDGAR/XBRL, FAERS, FDA), handling of off-calendar fiscal years, result sorting by primary metric, and return format (paired data + citation URIs). No contradiction with 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 front-loaded with trigger phrases and is dense with useful information. It is somewhat lengthy (~150 words) but every sentence contributes value, and the structure flows logically. Could be tightened slightly, but remains highly effective.

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 covers return format (paired data + citation URIs), data sources, sorting behavior, and entity count limits. It addresses edge cases (off-calendar fiscal years) and handles both modes (company and drug) thoroughly, making it complete for the tool's 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?

While schema covers basic param definitions, the description adds significant meaning: type='company' pulls specific financials (10-K revenue, net income, cash, long-term debt) and type='drug' pulls adverse-event/trial counts. It also clarifies value formats (tickers/CIKs vs drug names), going well beyond the schema's brief examples.

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's function: side-by-side comparison of 2–5 companies or drugs in one call. It uses specific trigger phrases (e.g., 'X vs Y', 'which is bigger') and distinguishes from sequential single-pack lookups, separating 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?

The description explicitly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities' and provides trigger phrases. It gives clear when-to-use context and implicitly excludes single-entity lookups. It also mentions it replaces 8–15 sequential lookups, reinforcing the use case.

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