开源 AI 营销技能库，涵盖增长实验、销售漏斗、内容运营、外呼、SEO 和财务自动化。是营销团队的 AI 助手。
开源 AI 营销技能库，涵盖增长实验、销售漏斗、内容运营、外呼、SEO 和财务自动化。是营销团队的 AI 助手。
# 克隆仓库
git clone https://github.com/ericosiu/ai-marketing-skills
# 进入目录
cd ai-marketing-skills
# 查看文档
cat README.mdOpen-source Claude Code skills for marketing and sales teams. Built by the team at Single Brain — battle-tested on real pipelines generating millions in revenue.
These aren't prompts. They're complete workflows — scripts, scoring algorithms, expert panels, and automation pipelines you can plug into Claude Code (or any AI coding agent) and run today.
| Category | What It Does | Key Skills |
|---|---|---|
| Growth Engine | Autonomous marketing experiments that run, measure, and optimize themselves | Experiment Engine, Pacing Alerts, Weekly Scorecard |
| Sales Pipeline | Turn anonymous website visitors into qualified pipeline | RB2B Router, Deal Resurrector, Trigger Prospector, ICP Learner |
| Content Ops | Ship content that scores 90+ every time | Expert Panel, Quality Gate, Editorial Brain, Quote Miner |
| Content OS Portable Starter | Bootstrap a vendor-neutral, draft-first content control loop | Config Schema, Approval Gates, Connector Matrix, Readback Templates |
| Personal Strategic Signal Intelligence | Turn private reading, bookmarks, notes, and applied work into source-grounded decision intelligence | Attention Drift, Decision Court, Bookmark-to-Build, Content Negative-Space |
| Outbound Engine | ICP definition to emails in inbox — fully automated | Cold Outbound Optimizer, Lead Pipeline, Competitive Monitor |
| SEO Ops | Find the keywords your competitors missed | Content Attack Briefs, GSC Optimizer, Trend Scout |
| Finance Ops | Your AI CFO that finds hidden costs in 30 minutes | CFO Briefing, Cost Estimate, Scenario Modeler |
| Revenue Intelligence | Prove content ROI and turn sales calls into strategy | Gong Insight Pipeline, Revenue Attribution, Client Report Generator |
| Conversion Ops | Score any landing page and turn survey data into lead magnets | CRO Audit, Survey-to-Lead-Magnet Engine |
| Podcast Ops | One episode → 20+ content pieces across every platform | Podcast-to-Everything Pipeline, Content Calendar |
| Team Ops | Ruthless performance audits and meeting intelligence | Elon Algorithm, Meeting-to-Action Extractor |
| Sales Playbook | Value-based pricing framework that turns $10K deals into $100K deals | Pre-Call Briefing, Tiered Packager, Call Analyzer, Pattern Library |
| Autoresearch | Karpathy-inspired optimization loops for conversion content — 50+ variants, expert scoring, evolved winners | Variant Generator, Expert Panel Scorer, Evolution Engine |
| Deck Generator | AI-generated slide decks with consistent visual styles in minutes | Image Generator, Google Slides Builder, Style Presets |
| YT Competitive Analysis | Find outlier videos and packaging patterns across any YouTube channels | Outlier Detector, Title Pattern Extractor, Channel Benchmarker |
| Video Content Engine | Diagnose any video and route it into the strongest justified content portfolio | Long-form Optimizer, Shorts Engine, Tutorial, Case Study, Paid Creative |
| Show-and-Tell Video Slate | Turn real builds and first-party proof into ranked 15-minute video episodes before production | Evidence Inventory, Episode Scoring, Packaging Gates, Shoot Order |
| Shortform Idea Grill | Interview, score, and rank proof-led short-form video ideas | Five-Second Hooks, Three-Second Scores, Talking Bullets, CTA Mapping |
| Net-New Video Editor | Turn fresh talking-head recordings into reversible, review-ready vertical drafts | JSON Edit Plans, FFmpeg Rendering, Captions, Hook Cards, Visual QA |
| X Long-Form + Humanizer | Write X articles that sound human — with a 24-pattern AI slop detector | Post Writer, Humanizer Checklist, ASCII Diagram Builder |
Each skill category has its own README with setup instructions. The general pattern:
# 1. Clone the repo
git clone https://github.com/ericosiu/ai-marketing-skills.git
cd ai-marketing-skills
# 2. Pick a category
cd growth-engine # or sales-pipeline, content-ops, etc.
# 3. Install dependencies
pip install -r requirements.txt
# 4. Set up environment variables
cp .env.example .env
# Edit .env with your API keys
# 5. Run
python experiment-engine.py create \
--hypothesis "Thread posts get 2x engagement vs single posts" \
--variable format \
--variants '["thread", "single"]' \
--metric impressions