list_suggested_messagesList a chatbot's suggested messages (the clickable prompts shown to visitors). Use the returned id with update_suggested_message or remove_suggested_message.
| Name | Required | Description | Default |
|---|---|---|---|
| chatbot_id | Yes | The chatbot id. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are empty, so the description carries full burden. It does not disclose behavioral traits like read-only nature, rate limits, or side effects. The description is minimal and adds no transparency beyond the name.
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 a single, well-structured sentence that front-loads the purpose and adds downstream utility. No wasted words.
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 simple tool with one parameter and no output schema or nesting, the description covers core functionality and use of results. Could mention that it returns a list of suggested messages, but the name implies that.
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 schema coverage is 100% with a clear description for chatbot_id. The tool description adds no additional meaning beyond the schema, so baseline score 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 clearly states the tool lists a chatbot's suggested messages and specifies they are clickable prompts for visitors. It distinguishes its purpose from siblings by naming the specific resource and connecting to update/remove 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 description indicates using the returned id with update_suggested_message or remove_suggested_message, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., get_chatbot or list_chatbots). No context on when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource and action (sources, suggested messages, chatbots, inbox, leads, analytics, insights). There is no ambiguity between tool purposes.
All tool names follow a consistent verb_noun pattern (add_, get_, list_, recrawl_, update_). The naming convention is uniform and predictable.
15 tools is well-scoped for a chatbot manager. The set covers all key functional areas without being excessive or insufficient.
The tool surface is largely complete but lacks delete operations: there is no 'remove_suggested_message' (though referenced in a description) and no way to delete a source. These are notable gaps.