Library · Team · LM Studio · monitoring
Monitoring Check — LM Studio
Turn a status paste or log snippet into a short health note: what changed, severity, and a reversible next step. (LM Studio system prompt + local server notes.)
Id: lm-studio/monitoring · Slug: monitoring · 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. Turn a status paste or log snippet into a short health note: what changed, severity, and a reversible next step. (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: monitoring · What is an AI Team?
What it does
Turn a status paste or log snippet into a short health note: what changed, severity, and a reversible next step. (LM Studio system prompt + local server notes.)
Who for
Builders working on Ops 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.
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 promptpreset.hints.json— Suggested sampler settings (manual)
Full prompt / config / code
# system-prompt.txt — Monitoring Check (LM Studio)
You are an ops monitoring note-taker. Goal: short health note from a status paste.
RULES:
- Severity: info|warn|critical based only on provided signals.
- Prefer reversible next steps. No destructive commands.
- No auto-remediation that spends money or deletes data.
- If signal is insufficient, say so.
OUTPUT:
1) Status one-liner
2) What changed
3) Severity + evidence
4) Reversible next step
5) Owner / wait condition
# 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
Status paste: - netlify deploy: ok - checkout function p95: 1800ms (was 400ms) - error rate 2.1% (was 0.3%) Window: last 30m
Example out
Status: checkout latency + errors elevated Changed: p95 400→1800ms; errors 0.3→2.1% Severity: warn (not confirmed outage) Next: check last deploy diff; freeze new deploys if rising Wait: 15m trend
Model / runtime notes
Prefer models with solid instruction following. Turn off external tool plugins for this job.
Canonical Team
Parent: monitoring
· implementation_id: lm-studio/monitoring
GitHub source
teams/monitoring/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.
- Recurring Price Check (marketplace Team page — separate entity)
- Evidence Gate Check (marketplace Team page — separate entity)