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

Beyond the annotations (readOnly, openWorld, idempotent), the description reveals concrete behaviors: pulls from SEC EDGAR/XBRL and FAERS, handles off-calendar fiscal years, sorts by primary metric, and returns paired data with citation URIs. This adds substantial 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 well-organized: trigger examples, preference rule, per-type data details, output format, and performance note. Every sentence adds actionable information, though the length is a bit high. It earns its place with front-loaded examples and structured specifics.

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?

Despite lacking an output schema, the description explains return format (paired data + citation URIs), sorting behavior, data sources, and fiscal-year handling. For a 2-parameter tool with rich annotations, this provides complete operational context for an agent to invoke 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?

Schema coverage is 100%, so baseline is 3. The description gives examples and data-source details, but these largely reiterate or supplement what the schema already states (e.g., tickers vs. drug names). It adds some value by explaining what each type returns, but does not deeply enhance parameter syntax or constraints.

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 natural-language trigger phrases and explicitly states a side-by-side comparison of 2–5 companies or drugs in one call. It clearly identifies the action (compare) and the resource (entities), and distinguishes itself from sequential single-pack lookups and sibling tools 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 explicitly instructs 'ALWAYS PREFER over sequential single-pack lookups when comparing entities,' providing a clear when-to-use rule and alternative. It also differentiates between type="company" and type="drug" data sources, helping the agent decide when each mode is appropriate.

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