get_conversation_flow
Retrieve the visual conversation flow graph and automated decision tree for a bot.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| bot_id | Yes |
Retrieve the visual conversation flow graph and automated decision tree for a bot.
| Name | Required | Description | Default |
|---|---|---|---|
| bot_id | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden: it implies a read but says nothing about permissions, whether the graph is empty for bots without a visual flow, or what the graph structure contains. Return shape matters here because the tool produces a graph object and there is 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?
One sentence, front-loaded with the verb and resource, with no filler. It is efficient, though its brevity comes partly from omitting information the agent needs rather than from tight editing alone.
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?
A read tool with no annotations and no output schema needs the description to convey at least the rough return shape (graph nodes/edges vs. a decision tree) and the bot_id requirement. Neither is present, so an agent knows the purpose but not what to expect back or how to call it 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 0%, so the single parameter bot_id is undocumented in both schema and description. The description never mentions bot_id, whether it accepts an ID vs a name, or where to obtain it, failing to compensate for the coverage gap.
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?
States a specific verb ('Retrieve') and a specific resource ('visual conversation flow graph and automated decision tree') scoped to a bot. This clearly separates it from read siblings like get_chatbot and get_chatbot_instructions, though it never names an alternative explicitly.
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?
There is no statement of when to use this versus get_chatbot_instructions, get_chatbot, or update_conversation_flow; the read/navigate relationship to the update tool is left entirely to inference. Usage is only implied by the word 'Retrieve'.
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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