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

Annotations already declare read-only, open-world, and idempotent behavior. The description adds valuable context by disclosing specific data sources (SEC EDGAR/XBRL, FAERS, FDA), off-calendar fiscal year handling, sorting by primary metric, and the return of citation URIs—all beyond what annotations provide.

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 with useful information, front-loaded with the exact user phrasings it matches. No wasted words; each sentence contributes to understanding purpose, usage, or behavior. It's long but appropriately sized for a tool with two parameter types and rich behavioral details.

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?

Even with no output schema, the description explains returns ('paired data + pipeworx:// citation URIs per entity') and sorting behavior, closing the gap. It also specifies limits (2–5) and source logic, making it sufficient for an agent to select and invoke correctly without external docs.

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 further elaborates parameter semantics by explaining what 'type' selects (company vs. drug) and the exact metrics pulled for each, plus examples for values. This adds meaningful depth beyond 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 a single parallel call, listing trigger phrases like 'compare X and Y' and 'X vs Y'. It also distinguishes itself from sequential single-entity lookups, which differentiates it from a sibling tool 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?

Explicitly instructs 'ALWAYS PREFER over sequential single-pack lookups when comparing entities,' providing a clear when-to-use directive. It also covers both entity types (company/drug) and implies the alternative of sequential lookups, though it doesn't name specific sibling tools beyond that distinction.

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