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

Annotations already indicate read-only, open-world, and idempotent behavior. The description adds important behavioral details: for companies, it pulls latest 10-K financials with correct fiscal year handling; for drugs, it pulls FAERS adverse-event counts, FDA approvals, and trial counts. It also mentions result ordering by primary metric and return of citation URIs.

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 slightly verbose but well-structured and front-loaded with trigger phrases. Every sentence adds value, though some details (e.g., fiscal year handling) could be integrated more concisely without losing informativeness.

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 adequately explains what the tool returns (paired data with pipeworx:// URIs). It specifies result sorting behavior and covers both entity types comprehensively. Given the simplicity of the input schema, the description is complete and leaves no critical gaps.

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%, but the description adds meaningful context. For 'type', it explains the data sources for each enum value. For 'values', it provides examples and format constraints (tickers/CIKs for companies, drug names for drugs). This goes beyond the schema's minimal 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 identifies the tool's purpose: side-by-side comparison of 2-5 companies or drugs. It provides trigger phrases ('Compare X and Y', 'X vs Y', etc.) and specifies the data sources for each type (SEC EDGAR for companies, FAERS for drugs). This differentiates it from 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?

The description explicitly advises preferring this tool over sequential single-pack lookups when comparing entities. It also provides concrete trigger phrases that indicate when to use, effectively guiding the agent on appropriate usage scenarios versus alternatives.

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