Alfred Claw a96d0d8889 Initial commit: 6 AI marketing skill categories

- growth-engine: Autonomous experiment engine (Karpathy autoresearch for marketing)
- sales-pipeline: RB2B router, deal resurrector, trigger prospector, ICP learner
- content-ops: Expert panel, quality gate, editorial brain, quote miner
- outbound-engine: Cold outbound optimizer, lead pipeline, competitive monitor
- seo-ops: Content attack briefs, GSC optimizer, trend scout
- finance-ops: CFO briefing, cost estimate, scenario modeler

79 files, all sanitized - zero hardcoded credentials or internal references.

2026-03-27 20:14:52 -07:00

3.1 KiB

Raw Blame History

AI Sales Pipeline

Complete AI-powered sales pipeline automation: website visitor identification → intent scoring → suppression → campaign routing → dead deal resurrection → trigger prospecting → self-learning ICP optimization.

When to Use

Use this skill when:

Setting up automated outbound from website visitor identification (RB2B)
Running suppression checks before cold outreach
Routing leads to the right cold email campaigns
Reviving closed-lost deals from HubSpot
Finding companies showing buying signals (new hires, funding, job postings)
Analyzing prospect approve/reject patterns to improve ICP targeting

Tools

RB2B Pipeline (visitor → outbound)

Script	Purpose	Key Command
`rb2b_webhook_ingest.py`	Webhook server + intent scoring	`python3 rb2b_webhook_ingest.py --serve --port 4100`
`rb2b_suppression_pipeline.py`	5-layer suppression checks	`python3 rb2b_suppression_pipeline.py --email user@co.com`
`rb2b_instantly_router.py`	Full pipeline: score → suppress → route → enroll	`python3 rb2b_instantly_router.py --serve --port 4100`

Deal Intelligence

Script	Purpose	Key Command
`deal_resurrector.py`	3-layer dead deal revival (time decay + POC expansion + champion tracking)	`python3 deal_resurrector.py --top 10 --dry-run`
`trigger_prospector.py`	Web signal monitoring (new hires, funding, agency searches)	`python3 trigger_prospector.py --days 7 --top 15`
`icp_learning_analyzer.py`	Learn from approve/reject decisions, recommend ICP changes	`python3 icp_learning_analyzer.py`

Configuration

All scripts use environment variables for API keys and configuration. Copy .env.example to .env and fill in your values.

Required Environment Variables

HUBSPOT_API_KEY — HubSpot private app token (Deal Resurrector, Suppression)
INSTANTLY_API_KEY — Instantly API key (Router, Suppression)
BRAVE_API_KEY — Brave Search API key (Trigger Prospector)
DATABASE_URL — PostgreSQL connection string (ICP Analyzer only)

Key Customization Points

Intent scoring: Edit PAGE_INTENT_SCORES dict in webhook_ingest to match your URL patterns
Agency detection: Edit AGENCY_KEYWORDS_* in router for your market
Loss reason scoring: Edit LOSS_REASON_BONUS in deal_resurrector for your close reasons
Signal queries: Edit SEARCH_QUERIES in trigger_prospector for your target market
Campaign routing: Edit data/campaigns.json with your Instantly campaign UUIDs

Data Flow

RB2B Webhook → Ingest (score) → Suppress (5 layers) → Route (classify) → Instantly
HubSpot CRM  → Deal Resurrector (score + draft emails) → Review Queue
Brave Search → Trigger Prospector (score + enrich) → Outreach Queue
Prospect DB  → ICP Analyzer (learn patterns) → Filter Recommendations

Dependencies

Python 3.9+
requests (for HubSpot API)
psycopg2-binary (for ICP Analyzer only)
No other external dependencies — scripts use stdlib HTTP server and urllib

3.1 KiB Raw Blame History