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

With no annotations, the description carries the burden and does well: it declares 'Read-only', states the return shape (findings with code, severity, remedy), and warns 'Check complete before trusting an empty error list' — a genuine behavioral caveat. It stops short of detailing permissions or failure modes of the tool itself.

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?

Dense but front-loaded: the purpose leads, the checks follow, and the return/caveat sentences close. No filler, though the enumeration is long for a single-sentence run.

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?

No output schema, so it is right that the description explains what returns (findings with code, severity, remedy); no annotations, so the read-only claim and empty-result caveat are necessary. Remaining gap is the absence of any hint about cost or latency of a full diagnostic.

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?

One parameter with 100% schema description coverage, so the schema already documents botId and its source. The description adds no format or ID-syntax detail beyond that, so the baseline 3 applies.

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?

Specific verb-plus-resource framing ('find out why a website chatbot does not answer or does not show up') enumerates the exact conditions checked: access, message limit, credit, LLM provider, origins, knowledge sources, and chat activity. This is clearly distinct from the sibling list/update/create tools.

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 trigger condition is stated plainly (chatbot not answering or not appearing) and the schema points to smartwebchat_list_chatbots for the botId. No explicit when-not or alternative-tool routing is given, 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.