Support Triage — Ollama

Classify an inbound message, propose a first reply hold, and flag escalation — human sends. (Ollama Modelfile + chat prompt for offline runs.)

Id: ollama/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 Ollama. Classify an inbound message, propose a first reply hold, and flag escalation — human sends. (Ollama Modelfile + chat prompt for offline runs.)

How this runtime fits

This Ollama 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. (Ollama Modelfile + chat prompt for offline runs.)

Who for

Builders working on Support jobs who can run Ollama themselves.

Need to run

You will run this locally or on infra you control.
No production credentials in prompts or committed files.
Ollama installed
A local instruct model pulled

How to use

Install Ollama and pull a base model you already trust (example: llama3.2).
Save the Modelfile above in an empty folder.
Run: ollama create botshelf-support-triage -f Modelfile
Run: ollama run botshelf-support-triage
Paste your input (see Example in). Expect the structured output; then stop.

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

Modelfile — Create a local model with the system prompt
prompt.md — User-facing run instructions

Full prompt / config / code

# Modelfile — Support Triage (Ollama)
FROM llama3.2
SYSTEM """
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
"""
PARAMETER temperature 0.3
PARAMETER num_ctx 8192

# Build & run (safe, local):
#   ollama create botshelf-support-triage -f Modelfile
#   ollama run botshelf-support-triage
#
# Safety: no network tools required. Do not pass API keys into the Modelfile.

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

Works best with 8k+ context instruct models. Smaller models may skip sections — ask it to continue once.

Canonical Team

Parent: support-triage · implementation_id: ollama/support-triage

GitHub source

teams/support-triage/ollama · 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)