Ai Test

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

Annotations already declare readOnly, idempotent, and non-destructive, so the safety profile is covered. The description adds value beyond them by disclosing the key side-effect boundary ("without creating a conversation") and previewing the three-part return (classification, spam flag, generated reply) for a tool that has no output schema.

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?

Two tightly written sentences, with the core action and its side-effect constraint front-loaded and the use case following. Every clause earns its place with 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 compensates by describing the return payload, and it clarifies the non-mutating behavior that annotations only imply. An agent has everything needed to call this correctly.

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 description coverage is 100% and both parameters are documented in the schema, including a helpful pointer to organization_list for the organizationId. The description adds no further parameter-level meaning, so the baseline 3 for schema-documented params is appropriate.

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 opens with a specific verb+resource ("Simulate an incoming customer message") and immediately clarifies scope by stating it works "without creating a conversation." It also enumerates exactly what it returns (classification, spam verdict, reply), letting an agent distinguish it from siblings like ai_draft_reply or conversation_reply without opening any schema.

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?

It gives a clear context for use ("Useful to check classifications, prompts and knowledge"), which tells the agent this is a pre-flight/testing tool rather than a production action. However, it names no alternative tool and states no explicit when-not-to-use condition, so it falls short of the 5-level routing guidance.

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