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

Annotations indicate read-only, idempotent, and non-destructive. The description adds rich behavioral context: data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), handling of off-calendar fiscal years, sorting by primary metric for 'largest' queries, and return of paired data with citation URIs. No contradictions with 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 a single dense paragraph that front-loads user queries and key action. It contains all necessary information but could be more scannable with bullet points. However, it is not verbose; every sentence adds value.

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 adequately explains what is returned (paired data + citation URIs) and the data sources. It covers sorting and entity types. Minor gap: exact structure of the paired data is not described, but the tool is simple enough (2 params, no nested objects) that agents can infer from context.

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% with brief descriptions. The description adds significant value: it explains what each type pulls (e.g., '10-K revenue + net income + cash + long-term debt' for companies), provides concrete examples (tickers/CIKs, drug names), and clarifies sorting behavior. This goes well beyond the schema.

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's purpose: side-by-side comparison of 2-5 companies or drugs. It provides specific example queries and distinguishes from sequential lookups by noting it replaces 8-15 calls. The verb phrases ('Compare X and Y', 'X vs Y') directly map to user intent.

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 says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities' and gives trigger phrases. It doesn't explicitly mention when not to use it (e.g., for single entity use entity_profile), but the context implies multi-entity comparison. The efficiency claim helps agents prioritize this tool.

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