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

The annotations already declare readOnlyHint=true and idempotentHint=true, so the behavioral safety profile is covered. The description adds context that the data comes from historical/closed leads and includes Anti-ICP signals, which is useful but does not go far beyond what annotations already communicate.

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 two short sentences with the trigger condition front-loaded and the output described immediately after. There is no filler or redundant repetition of the title or schema.

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 zero parameters, an output schema present, and read-only/idempotent annotations, the description fully equips an agent to understand what the tool does and when to call it. No additional prerequisites or caveats are needed for such a simple retrieval tool.

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?

The tool accepts zero parameters, so the schema fully covers the parameter surface. The description adds no parameter-specific semantics, but none are needed; this is the correct baseline for a no-parameter tool.

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 explicitly states when to use the tool ('when the user asks what kinds of prospects historically win or lose') and what it returns ('Learned Winning Pattern and Anti-ICP signals'). This gives a specific verb, resource, and clear scope that distinguishes it from sibling tools such as learning_engine or analyze_company.

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 gives a clear, explicit trigger condition for use. It does not name alternative tools or state when not to use it, but the trigger is specific enough that an agent can route the request confidently.

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