list_chatbotsList the chatbots your account can manage (your current team's chatbots). Returns each chatbot id, name and type. Use the id with the other tools.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It states the scope and return fields but does not disclose any behavioral aspects like read-only nature, pagination, rate limits, or authorization requirements. This is adequate but incomplete.
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 sentences are concise and front-loaded with the purpose. Every sentence adds value, no fluff.
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 list tool with no output schema, the description explains the return values. It lacks details on sorting or data structure, but given the low complexity, it is mostly complete.
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?
There are zero parameters, so baseline is 4. The description adds value by specifying what is returned (id, name, type), which is not in the schema.
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 chatbots the user's account can manage, specifying the scope ('current team's chatbots') and the returned fields (id, name, type). It distinguishes from sibling tools like get_chatbot (single) and list_sources.
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 explicitly says 'Use the id with the other tools,' providing clear guidance on how to use the output. However, it doesn't compare to alternatives like get_chatbot or list_sources, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.