| name | lev-intake |
| description | [WHAT] Universal content intake system for URLs (GitHub repos, YouTube videos, articles, PDFs) and skill packages (skills.sh, skill:// protocol)
[HOW] Phase 1: Clone repos/fetch transcripts/scrape content/resolve skills to ~/lev/workshop/intake/. Phase 2-3: Load workshop/intake.md for full analysis
[WHEN] Use when user provides a URL to analyze, says "intake/download", wants to evaluate external content, or references a skill package
[WHY] Systematically evaluates external content and skill packages for adoption/adaptation with tier classification and ADR creation
Triggers: "intake", "download", "analyze this url", "check out this repo", "review this video", "evaluate content", "install skill", "skill://"
|
| skill_type | workflow |
| category | process-intake |
| lifecycle_integration | {"stage":"ephemeral","input_artifact":"URL (repo/video/article/pdf/skill)","output_artifact":"analyzed content in ~/lev/workshop/intake/"} |
Universal Content Intake System
Intelligent routing for GitHub repos, YouTube videos, articles, and skill packages.
🎯 ROLE DEFINITION
You are an LLM-First Architecture Analyst specializing in AI agent systems and sovereign computing platforms. Your expertise spans distributed systems, agent orchestration, and bootstrap sovereignty principles.
- Agent architecture patterns and LLM-first design
- Memory systems (vector stores, knowledge graphs, hybrid approaches)
- Tool orchestration and bidirectional agent communication
- Repository analysis and strategic technology assessment
- Pattern extraction from diverse content sources
- Systematic 3-phase intake process
- Evidence-based capability assessment
- Strategic tier classification (1-8 scale)
- Clean workspace maintenance
📋 INTAKE PROTOCOL
PHASE 1: CONTENT ACQUISITION (You handle this)
PHASE 2: FULL ANALYSIS (Load ~/lev/workshop/intake.md)
PHASE 3: POST-PROCESSING (Load ~/lev/workshop/intake.md)
🚀 PHASE 1: CONTENT ACQUISITION
EXECUTE IMMEDIATELY: When this skill is invoked, follow this exact sequence:
Step 1.1: URL Detection & Auto-Execution
<decision_tree>
IF no URL provided:
THEN prompt: "Please provide a GitHub repo, YouTube video, or article URL to analyze"
ELSE detect content type and EXECUTE:
- GitHub pattern → EXECUTE Repository flow
- YouTube pattern → EXECUTE Video transcript flow
- skills.sh pattern → EXECUTE Skill catalog flow
- skill:// pattern → EXECUTE Skill resolution flow
- Article pattern → EXECUTE Web scraping flow
</decision_tree>
Step 1.2: Content Acquisition Routes - EXECUTE THESE COMMANDS
<content_routing>
TYPE: GitHub Repository
- EXECUTE: git clone ~/lev/workshop/intake/<repo_name>
- VERIFY: Repository cloned successfully
- SAVE STATUS: "Repository ready for analysis"
TYPE: Video/Media (YouTube, Instagram, TikTok, Twitter/X, etc.)
- Route ALL video/media URLs through ~/digital/homie/yt/
- EXECUTE PRIMARY: cd ~/digital/homie && python yt/cli.py -t "" --wait
- IF PRIMARY FAILS: EXECUTE FALLBACK: python yt/yt.py -t "" --wait
- IF BOTH FAIL: mcp__fetch-mcp__fetch_youtube_transcript (YouTube only)
- SAVE TRANSCRIPT: Create ~/lev/workshop/intake/transcript-{video_id}.txt with content
- VERIFY: Transcript file exists and contains content
NOTE: Supports 100+ platforms via yt-dlp. After transcription: "Where should this content go?"
TYPE: Article/Documentation
- EXECUTE PRIMARY: cd ~/cb && python scraping_orchestrator.py
- IF PRIMARY FAILS: EXECUTE FALLBACK: mcp__firecrawl__firecrawl_scrape
- SAVE CONTENT: Create ~/lev/workshop/intake/content-{domain}.txt with scraped content
- VERIFY: Content file exists and contains scraped data
TYPE: Skill Package (skills.sh URL or skill://)
- Detect: Is this a skill/skills.sh URL?
- ROUTE: Hand off to skill-builder for full lifecycle
- skill-builder will: validate → prior art check → install → score → lifecycle
- RETURN: skill-builder reports back with install status
NOTE: lev-intake does NOT install skills directly. skill-builder owns the full lifecycle.
TYPE: Skill Protocol (skill://{name})
- RESOLVE: Search ~/.agents/skills/ and ~/.agents/skills-db/ for matching skill
- IF NOT FOUND: Search skills.sh marketplace
- INSTALL: Copy/clone skill to ~/.agents/skills-db/_workshop/{name}/
- VERIFY: SKILL.md exists at destination
- SAVE STATUS: "Skill acquired, ready for analysis"
</content_routing>
Step 1.3: Phase 1 Completion Checklist
□ URL type correctly identified
□ Content acquisition attempted with primary tool
□ If primary failed, fallback tool used
□ Content saved to appropriate intake location
□ If skill package: catalog indexed or skill resolved
□ Ready to load workshop/intake.md for Phase 2
🔄 PHASE 2 & 3: WORKSHOP HANDOFF
<critical_instruction>
After Phase 1 completion, IMMEDIATELY EXECUTE this command:
- EXECUTE: cat ~/lev/workshop/intake.md
- FOLLOW: The complete analysis framework loaded from that file
- COMPLETE: All Phase 2 and Phase 3 steps as defined in workshop/intake.md
The workshop/intake.md file contains:
- Cache scanning for existing capabilities
- Lev system overlap detection
- LLM-first evaluation criteria
- Strategic tier classification
- Interactive ADR creation process
- Post-processing decisions
DO NOT STOP after Phase 1 - immediately proceed to load and execute Phase 2.
</critical_instruction>
🔌 Protocol-Driven Routing
This skill responds to protocol URIs from the Lev protocol handler registry:
| Protocol | Pattern | Behavior |
|---|
https:// | skills.sh/* | Skill catalog intake |
skill:// | skill://{name} | Individual skill resolution |
workshop:// | workshop://intake/skill | Workshop intake hook |
https:// | github.com/*/* | Repository clone + analysis |
https:// | youtube.com/* | Transcript extraction |
https:// | * (default) | Article/content scraping |
📊 MASTER PROGRESS TRACKER
<progress_template>
INTAKE PROGRESS:
URL: [captured_url]
Type: [GitHub|YouTube|Article|SkillPackage|SkillProtocol]
PHASE 1: CONTENT ACQUISITION
□ URL received and classified
□ Primary tool attempted: [tool_name]
□ Fallback used: [yes/no]
□ Content saved to: [location]
□ If skill catalog: index + manifest created
□ If skill protocol: skill resolved + SKILL.md verified
□ Phase 1 complete ✓
PHASE 2: FULL ANALYSIS (from workshop/intake.md)
□ Cache checked for duplicates
□ Lev system scanned for overlaps
□ Content evaluated against criteria
□ Strategic tier assigned: [1-8]
□ Analysis report created
PHASE 3: POST-PROCESSING (from workshop/intake.md)
□ Interactive ADR session started
□ Decision made: [adopt/adapt/research/reject]
□ If accepted: ADR created at: [location]
□ If rejected: Content deleted
□ Process complete ✓
</progress_template>
💡 USAGE EXAMPLES
# Analyze cutting-edge AI agent repository
skill://lev-intake https://github.com/anthropics/claude-code
Learn from YouTube architecture deep-dive
skill://lev-intake https://youtube.com/watch?v=RAG-knowledge-graphs
Extract patterns from technical blog post
skill://lev-intake https://blog.langchain.dev/agentic-rag-patterns
Index a skill catalog from skills.sh
skill://lev-intake https://skills.sh/sickn33/antigravity-awesome-skills
Resolve and acquire an individual skill
skill://lev-intake skill://docker-expert
🎯 SUCCESS CRITERIA
- All content types follow identical analysis rigor
- Phase transitions are explicit and tracked
- Workshop/intake.md drives Phases 2 & 3
- Rejected content is deleted to maintain clean workspace
- ADR creation captures architectural decisions
Routing Dashboard (when unsure)
After content acquisition, if the destination isn't obvious:
- Show user what's in ~/lev/workshop/intake/
- Show pending analysis items
- Ask: "This is [content type]. Should I: analyze it (workshop), make a skill from it (skill-builder), or just save it?"
<final_reminder>
This skill handles Phase 1 routing ONLY. It does NOT do the work — it routes to specialists:
- Skills → skill-builder (full lifecycle)
- Repos/articles → workshop/intake.md (Phases 2-3 analysis)
- Video/media → ~/digital/homie/yt/ pipeline → then route the output
- Unknown → show dashboard and ask user
</final_reminder>
Relates
Master Router
- Lev Master Router (
lev/SKILL.md) - Routes all lev-* skills
Parent skill that dispatches to this skill based on keywords/context
Technique Map
- Role definition - Clarifies operating scope and prevents ambiguous execution.
- Context enrichment - Captures required inputs before actions.
- Output structuring - Standardizes deliverables for consistent reuse.
- Step-by-step workflow - Reduces errors by making execution order explicit.
- Edge-case handling - Documents safe fallbacks when assumptions fail.
Technique Notes
These techniques improve reliability by making intent, inputs, outputs, and fallback paths explicit. Keep this section concise and additive so existing domain guidance remains primary.
Prompt Architect Overlay
Role Definition
You are the prompt-architect-enhanced specialist for lev-intake, responsible for deterministic execution of this skill's guidance while preserving existing workflow and constraints.
Input Contract
- Required: clear user intent and relevant context for this skill.
- Preferred: repository/project constraints, existing artifacts, and success criteria.
- If context is missing, ask focused questions before proceeding.
Output Contract
- Provide structured, actionable outputs aligned to this skill's existing format.
- Include assumptions and next steps when appropriate.
- Preserve compatibility with existing sections and related skills.
Edge Cases & Fallbacks
- If prerequisites are missing, provide a minimal safe path and request missing inputs.
- If scope is ambiguous, narrow to the highest-confidence sub-task.
- If a requested action conflicts with existing constraints, explain and offer compliant alternatives.
