neuron_build_persona_from_conversation
Distill a reusable voice from an existing WhatsApp conversation's stored messages — no extension needed. author picks whose voice: 'me' (owner's own outgoing texts), 'contact' (the other party), 'bot', or 'any'. For a group chat, pass senderName/senderPhone to isolate one participant. Requires >=...
This record as markdown: /tools/io-github-conquext-neuron/neuron-build-persona-from-conversation.md
What neuron_build_persona_from_conversation does on Neuron
AI agents invoke neuron_build_persona_from_conversation to trigger actions in Neuron. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | — | |
limit | integer | — | How many recent messages to read (default 200). |
author | string | — | Whose voice to capture. Default 'me'. |
senderName | string | — | For groups: match one participant by display name. |
senderPhone | string | — | For groups: match one participant by phone. |
conversationId | string | Yes | Conversation UUID (from neuron_list_conversations). |
Parameters from the server's own tool schema.
Why neuron_build_persona_from_conversation is rated High
neuron_build_persona_from_conversation triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs neuron_build_persona_from_conversation safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Neuron, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For neuron_build_persona_from_conversation, this is the rule to start with:
neuron_build_persona_from_conversation stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Neuron, apply this rule, and every neuron_build_persona_from_conversation call is checked against it from then on.
Questions about neuron_build_persona_from_conversation
Distill a reusable voice from an existing WhatsApp conversation's stored messages — no extension needed. author picks whose voice: 'me' (owner's own outgoing texts), 'contact' (the other party), 'bot', or 'any'. For a group chat, pass senderName/senderPhone to isolate one participant. Requires >=3 usable text messages. Runs an LLM call. It is categorised as a Execute tool in the Neuron MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
neuron_build_persona_from_conversation accepts 6 parameters: name, limit, author, senderName, senderPhone, conversationId. Required: conversationId. The full parameter table on this page comes from the server's own tool schema.
Register the Neuron MCP server in PolicyLayer and add a rule for neuron_build_persona_from_conversation: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Neuron. Nothing to install.
neuron_build_persona_from_conversation is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the neuron_build_persona_from_conversation rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for neuron_build_persona_from_conversation. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
neuron_build_persona_from_conversation is provided by the Neuron MCP server (neuron-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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