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

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral details: it makes a single parallel call, handles off-calendar fiscal years correctly, returns results sorted by primary metric, and includes citation URIs. It also describes the specific data pulled for each type. This goes well beyond 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 concise, consisting of two sentences. It front-loads with common user queries, then efficiently conveys the tool's purpose, usage preference, data sources, and behavior. Every sentence adds value; no redundancy.

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 explains return data (paired data + citation URIs, sorted by primary metric). It covers entity types, data sources, and constraints. While it omits details like error handling or pagination, it provides sufficient context for an agent to use the tool effectively given its simplicity.

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 parameters are fully described in the schema. The description adds meaning by providing examples ('company' vs 'drug', tickers vs drug names), clarifying the 2–5 item constraint, and explaining the data each type retrieves. This adds context not in 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 starts with natural language queries like 'Compare X and Y' and 'which is bigger / better', then explicitly states 'side-by-side comparison of 2–5 companies or drugs'. It clearly identifies the action (compare) and the resource (entities), and distinguishes itself from sequential lookups, making the purpose unmistakable.

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 states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', providing clear guidance on when to use this tool. It also explains the data sources for each entity type. However, it does not explicitly state when not to use it (e.g., for a single entity lookup).

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