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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds significant behavioral detail: how fiscal years are handled for companies, the specific data sources (SEC EDGAR, FAERS), and that results are sorted by primary metric. It does not contradict 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 compact (4 sentences) and front-loaded with trigger phrases. Every sentence is substantive, covering usage triggers, data sources, sorting, and efficiency gains. No wasted 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?

Given no output schema, the description explains the return format ('paired data + pipeworx:// citation URIs') and covers all key aspects: entity types, data sources, sorting, and efficiency improvement (replacing 8–15 lookups). It is fully 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?

Schema coverage is 100%, but the description adds meaning beyond the schema: it explains the specific data pulled for each type (e.g., 'latest 10-K revenue', 'FAERS adverse-event counts'), provides example inputs, and clarifies the purpose of the 'values' array per entity type. This enriches the parameter semantics.

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 uses specific verbs ('compare', 'rank') and clearly identifies the resource ('2–5 companies or drugs' in one call). It provides trigger phrases ('X vs Y', 'which is bigger') and explicitly distinguishes from sequential lookups, fulfilling the purpose clarity criterion.

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 states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities,' giving clear context and a strong preference. It does not explicitly list when not to use it (e.g., for non-comparative queries), but the context is clear.

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