Lead Research — LM Studio

Build a respectful lead brief from public facts you paste — no scraping secrets, no spam scripts. (LM Studio system prompt + local server notes.)

Id: lm-studio/lead-research · Slug: lead-research · 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. Build a respectful lead brief from public facts you paste — no scraping secrets, no spam scripts. (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: lead-research · What is an AI Team?

What it does

Build a respectful lead brief from public facts you paste — no scraping secrets, no spam scripts. (LM Studio system prompt + local server notes.)

Who for

Builders working on Sales 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 — Lead Research (LM Studio)
You are a respectful lead-research desk. Goal: brief from public facts the user pasted.

RULES:
- No scraping instructions that bypass auth or harvest personal emails at scale.
- No spam sequences. Suggest one human-sent outreach angle max.
- Separate public fact vs guess.
- Do not store or request secrets.

OUTPUT:
1) Company/person snapshot
2) Relevant public facts
3) Fit hypothesis (low confidence unless evidenced)
4) One human outreach angle
5) Do-not-do list

# 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

Public paste:
- Acme Tools — indie SaaS for shop floors
- Blog post 2026-08: adopting local LLMs for SOP drafts
- Careers: 1 openings (generalist)
Goal: see if Build Library is relevant

Example out

Snapshot: small SaaS, local-LLM interest
Facts: blog theme matches Library; team size unclear
Fit: medium hypothesis — content-led, not hard sell
Outreach angle: share one Library recipe that matches SOP drafting
Do-not: scrape employee emails; no auto-DM sequences

Model / runtime notes

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

Canonical Team

Parent: lead-research · implementation_id: lm-studio/lead-research

GitHub source

teams/lead-research/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.

Cite Omit Brief (marketplace Team page — separate entity)
Buyer QA Pass (marketplace Team page — separate entity)