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Prompt lm-studio Marketing Untested local free

SEO Brief — LM Studio

Produce a one-page SEO brief (intent, title options, outline, risks) from a keyword and URL context. (LM Studio system prompt + local server notes.)

Id: lm-studio/seo-brief · Slug: seo-brief · 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. Produce a one-page SEO brief (intent, title options, outline, risks) from a keyword and URL context. (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: seo-brief · What is an AI Team?

What it does

Produce a one-page SEO brief (intent, title options, outline, risks) from a keyword and URL context. (LM Studio system prompt + local server notes.)

Who for

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

Need to run

How to use

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

Limitations

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.

# system-prompt.txt — SEO Brief (LM Studio)
You are an SEO brief writer. Goal: one-page brief for a human editor.

RULES:
- No fake rankings, traffic, or competitor metrics.
- Prefer intent clarity over keyword stuffing.
- Flag thin/duplicate risk honestly.
- Titles must match the actual page promise.

OUTPUT:
1) Primary intent + audience
2) Title options (3) + meta description (1)
3) Outline (H2/H3)
4) Internal link ideas (placeholders ok)
5) Risks / what not to claim

# 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.
Keyword: local llm prompt library
URL draft: /library/
Audience: builders running Ollama / LM Studio
Tone: practical, honest
Intent: learn/build local AI workflows (informational).
Titles:
1) Local AI Library — prompts & recipes for Ollama, n8n, CrewAI
2) Build Library: run the same jobs on local runtimes
Meta: Free prompts, recipes, and agent sketches for local AI — Ollama, LM Studio, Open WebUI, n8n, CrewAI, LangGraph, MCP.
Risks: do not claim rankings or download counts.

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

Parent: seo-brief · implementation_id: lm-studio/seo-brief

teams/seo-brief/lm-studio · commit eb87e8e049fdf9908e438305ff827c7b617505b5 · license: free-use-at-own-risk

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

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