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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses specific data sources (SEC EDGAR/XBRL, FAERS), handling of off-calendar fiscal years, sorting by primary metric, and the return format including citation URIs. This provides substantial behavioral 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 each sentence serves a purpose: examples, explicit priority, data specifics, fiscal year handling, sorting behavior, and output format. It is front-loaded with the most critical usage guidance and wastes no words.

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 properly explains return values ('paired data + pipeworx:// citation URIs') and also covers scope constraints (2–5 entities), sorting, and the efficiency benefit. This is complete for a comparison tool with two parameters and rich annotations.

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?

The schema already describes both parameters fully (100% coverage). The description adds interpretive value by explaining what each enum value (company vs drug) actually retrieves (10-K financials vs FAERS/trial data), which goes beyond the schema's simple 'Entity type' labeling. However, the core parameter semantics are already covered by the schema 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 clearly states the tool performs side-by-side comparisons of 2–5 companies or drugs in one parallel call. It distinguishes from siblings like entity_profile by explicitly prioritizing this tool over sequential single-entity lookups, and uses trigger phrases ('X vs Y', 'which is bigger') to make the purpose undeniable.

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 via example queries and directly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It also contrasts with alternatives by stating it replaces 8–15 sequential lookups, giving clear direction on when this tool should be chosen over sibling tools.

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