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ai-marketing-skills

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。

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2026-08-16
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详细介绍

项目简介

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。

适用场景

代码审查与优化
自动化测试编写
文档生成与维护
代码重构建议

快速开始

# 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.md

原文 README

AI Marketing Skills

Open-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.


🗂️ Skills

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

🚀 Quick Start

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