Support Triage — LM Studio

Classify an inbound message, propose a first reply hold, and flag escalation — human sends. (LM Studio system prompt + local server notes.)

Id: lm-studio/support-triage · Slug: support-triage · Status: Untested · Untested on this machine — recipe reviewed for safety (no secrets, no destructive commands, no auto-spend). Mark tested after you run it locally.

What is this

Prompt for LM Studio. Classify an inbound message, propose a first reply hold, and flag escalation — human sends. (LM Studio system prompt + local server notes.)

How this runtime fits

This LM Studio pack is a local AI agent / local AI workflow for the parent AI Team. It is a single-prompt (or system-prompt) pack — do not force multi-agent system language here.

Parent AI Team: support-triage · What is an AI Team?

What it does

Classify an inbound message, propose a first reply hold, and flag escalation — human sends. (LM Studio system prompt + local server notes.)

Who for

Builders working on Support jobs who can run LM Studio themselves.

Need to run

You will run this locally or on infra you control.
No production credentials in prompts or committed files.
LM Studio installed
A GGUF/instruct model loaded

How to use

Open LM Studio and load a local instruct model.
Paste system-prompt.txt into the System Prompt field.
Apply sampler hints (temperature ~0.3).
Chat with the Example in payload; copy the structured reply.
If using the local server, keep it bound to localhost.

Limitations

Not a substitute for professional legal, medical, or investment advice.
Outputs can be wrong; human review required before publish or spend.
Stage-1 Library items are free recipes — marketplace ready-to-use teams remain separate.
Local models may omit sections; re-prompt once if needed.
No harvesting of personal data beyond what the operator pasted.

Test status

Status: Untested · Untested on this machine — recipe reviewed for safety (no secrets, no destructive commands, no auto-spend). Mark tested after you run it locally.

Files

system-prompt.txt — Paste into LM Studio system prompt
preset.hints.json — Suggested sampler settings (manual)

Full prompt / config / code

# system-prompt.txt — Support Triage (LM Studio)
You are a support triage assistant. Goal: classify and draft a hold reply.

RULES:
- Human sends the message. You do not send email/chat.
- Never ask for passwords, seed phrases, or full card numbers.
- Escalate billing disputes and safety issues.
- Keep the hold reply short and kind.

OUTPUT:
1) Category + urgency
2) What we know / need
3) Hold-reply draft
4) Escalate? yes/no + why

# preset.hints.json (apply manually in UI; do not auto-download weights)
{
  "temperature": 0.3,
  "top_p": 0.9,
  "max_tokens": 2048,
  "repeat_penalty": 1.1,
  "notes": "Disable any tool plugins that can spend money or mutate production systems."
}

# Optional local server:
# LM Studio → Start server → OpenAI-compatible http://localhost:1234/v1
# Point your client at that base URL. No cloud key required for local weights.

Example in

From: user@example.com
Subject: charged twice?
Body: I see two USDT sends. Order #1842. Need help.

Example out

Category: billing / duplicate payment | urgency: high
Know: order #1842, two USDT sends claimed
Need: txids, amounts, times
Hold-reply: Thanks — please reply with both txids…
Escalate: yes — payment mismatch

Model / runtime notes

Prefer models with solid instruction following. Turn off external tool plugins for this job.

Canonical Team

Parent: support-triage · implementation_id: lm-studio/support-triage

GitHub source

teams/support-triage/lm-studio · commit eb87e8e049fdf9908e438305ff827c7b617505b5 · license: free-use-at-own-risk

Structural check: PASS · env: structural (structural only — does not set Verified)

Related Library items

Related marketplace Team pages

Soft thematic links only — not identity merges. Marketplace Teams ≠ Library AI Team records.

First Reply Hold (marketplace Team page — separate entity)
Hold Reply Inbox (marketplace Team page — separate entity)