Loreto Skills Generator
Feed any YouTube video, article, PDF, or image into the Loreto API and receive production-ready skill packages, complete with SKILL.md, test scripts, and reference stubs.
loreto-mcp
Turn any YouTube video, article, PDF, or image into a reusable Claude Code skill — without leaving your editor.
What it does
Loreto analyzes a content source and extracts structured skill packages that Claude Code can apply to future tasks. Each skill contains:
SKILL.md— Principles, failure modes, implementation steps, and architectural patternsREADME.md— Overview and usage context- Reference files — Supporting patterns and data structures
- Test script — Runnable validation for the skill's core concepts
Save skills to .claude/skills/ and Claude picks them up automatically on relevant tasks — reducing hallucinations, token usage, and re-explaining the same concepts over and over.
Sample skills
The sample-skills/ folder contains real skills generated by Loreto from a single technical video on hybrid AI architecture. Browse them to see exactly what you get:
| Skill | What it teaches |
|---|---|
designing-hybrid-context-layers | Architect hybrid retrieval systems that combine vector search, graph traversal, and structured data |
temporal-reasoning-sleuth | Enable agents to trace decision chains and reconstruct causal sequences across long time horizons |
synthesizing-institutional-knowledge | Capture and query organizational knowledge in a way AI agents can reliably reason over |
diagnosing-rag-failure-modes | Identify and fix the 7 most common RAG pipeline failure patterns |
routing-work-across-ai-harnesses | Dynamically route tasks to the right AI harness based on task type and context |
evaluating-ai-harness-dimensions | Score and compare AI harness options across speed, cost, accuracy, and controllability |
detecting-harness-lockin | Spot vendor lock-in signals early and design for portability |
benchmarking-ai-agents-beyond-models | Measure agent performance at the system level, not just model level |
auditing-intelligence-context-fit | Audit whether the right intelligence layer is solving the right problem |
Each folder includes the full SKILL.md, README.md, and any reference files — ready to drop into .claude/skills/.
Setup
1. Get an API key
Sign up at loreto.io to get your free API key (lor_...).
2. Install
pip install loreto-mcp
Or run directly without installing (requires uv):
uvx loreto-mcp
3. Configure Claude Code
User-scoped (works across all your projects) — add to ~/.claude/mcp.json:
{
"mcpServers": {
"loreto": {
"command": "uvx",
"args": ["loreto-mcp"],
"env": {
"LORETO_API_KEY": "lor_..."
}
}
}
}
Project-scoped (shared with your team) — add to .mcp.json at your project root:
{
"mcpServers": {
"loreto": {
"command": "uvx",
"args": ["loreto-mcp"],
"env": {
"LORETO_API_KEY": "${LORETO_API_KEY}"
}
}
}
}
4. Verify
Restart Claude Code and run /mcp — you should see loreto listed with generate_skills and get_quota.
Usage
Once connected, just ask Claude Code naturally:
Use Loreto to extract skills from https://www.youtube.com/watch?v=JYcidOS9ozU
Extract skills from this article and save them to .claude/skills/
Check my Loreto quota before we start.
Claude calls generate_skills, receives the full skill package, and can write the files directly to your project.
Available tools
| Tool | Description |
|---|---|
generate_skills | Extract ranked skill packages from a URL. Returns full file contents ready to save. |
get_quota | Check calls used, monthly limit, and plan for your API key. |
generate_skills parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
source | str | required | URL to analyze — YouTube, article, public PDF, or image |
source_type | str | "auto" | "auto" | "youtube" | "article" | "pdf" | "image" |
test_language | str | "python" | "python" | "typescript" | "javascript" |
include_visuals | bool | true | Embed Mermaid diagrams in SKILL.md |
context | str | null | 1–3 sentence hint to guide extraction (max 500 chars) |
themes_to_process | list[str] | null | Follow-up call: skill names from a previous response's queued themes |
Supported sources
| Source | Notes |
|---|---|
| YouTube videos | Up to 60 minutes |
| Web articles | Any publicly accessible URL |
| PDFs | Up to 100 pages |
| Images | Diagrams, whiteboards, slides (up to 20 MB) |
Configuration
| Environment variable | Required | Default | Description |
|---|---|---|---|
LORETO_API_KEY | Yes | — | Your Loreto API key (lor_...) |
LORETO_BASE_URL | No | https://api.loreto.io | Override for local development |
Plans
Free and paid plans available. See loreto.io/pricing for current limits.
License
MIT
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