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

With no annotations, the description carries the full burden and delivers: it records a conversation, consumes the account's message quota, and requires a full-access key because a read-only key returns 401. These are exactly the side effects and auth constraints an agent needs before calling.

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?

Three sentences, front-loaded with the core action, then usage, then behavioral caveats. Every sentence 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?

For a 3-parameter tool with no output schema and no annotations, the description covers purpose, usage, side effects, and auth well. It doesn't describe the shape of the chatbot reply (e.g., whether metadata comes back), a minor gap given no output schema exists.

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%, so botId, message, and sessionId are already documented in the schema, including the session-continuation semantics. The description adds no parameter-specific detail (like format or bounds) beyond the schema, so the baseline of 3 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 states a specific verb and resource ('Send a visitor message to a chatbot and get its reply') and clarifies the exact perspective ('exactly as a website visitor would see it'). This distinguishes it from siblings like list_chatbots, create_chatbot, or get_leads, which do not send conversational messages.

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 clear use cases: testing how the chatbot answers and checking knowledge-base coverage. These are concrete triggers for invocation. However, it doesn't state when NOT to use it or name an alternative tool for related tasks, keeping it short of a 5.

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