aiagentwithdhruv/skool-rag
claude-skills/.claude/skills/skool-rag/SKILL.md
Query Skool community content using RAG pipeline with vector search. Use when user asks to search Skool knowledge, find community answers, or query Skool content.
$ install --global
skillsauthnpx skillsauth add aiagentwithdhruv/automation skool-ragInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Mar 30, 2026, 8:03 PM55.0s4 files scanned
SKILL.md
- name:
- skool-rag
- description:
- Query Skool community content using RAG pipeline with vector search. Use when user asks to search Skool knowledge, find community answers, or query Skool content.
- argument-hint:
- [query]
- context:
- fork
- agent:
- Explore
- allowed-tools:
- Bash, Read, Write, Edit, Glob, Grep
Skool RAG Pipeline
Goal
Query Skool community content using a RAG (Retrieval-Augmented Generation) pipeline with vector search and reranking.
Scripts
./scripts/skool_rag_prepare.py- Prepare content for indexing./scripts/skool_rag_index.py- Index content in Pinecone./scripts/skool_rag_query.py- Query the knowledge base
Pipeline
1. Prepare Content
python3 ./scripts/skool_rag_prepare.py --community makerschool
Scrapes and chunks community content.
2. Index in Pinecone
python3 ./scripts/skool_rag_index.py --input .tmp/skool_chunks.json
Creates OpenAI embeddings and stores in Pinecone.
3. Query
python3 ./scripts/skool_rag_query.py --query "How do I get my first client?"
Pipeline:
- OpenAI embeddings for query
- Pinecone vector search
- Cohere reranking
- Claude response generation
Environment
PINECONE_API_KEY=your_key
OPENAI_API_KEY=your_key
COHERE_API_KEY=your_key
ANTHROPIC_API_KEY=your_key
Schema
Inputs
| Name | Type | Required | Description |
|------|------|----------|-------------|
| query | string | Yes | Natural language question to search for |
| community | string | No | Community slug to index (default: makerschool) |
Outputs
| Name | Type | Description |
|------|------|-------------|
| answer | string | AI-generated answer with source references |
Credentials
| Name | Source |
|------|--------|
| PINECONE_API_KEY | .env |
| OPENAI_API_KEY | .env |
| COHERE_API_KEY | .env |
| ANTHROPIC_API_KEY | .env |
Composable With
Skills that chain well with this one: skool-monitor
Cost
Pinecone + OpenAI embeddings + Cohere reranking + Claude
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