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
関連サーバー
Office 365 Calendar
Access Office 365 Calendar data, providing workday insights and productivity analytics.
Zephyr Scale
Manage Zephyr Scale test cases through the Atlassian REST API.
Procesio MCP Server
Interact with the Procesio automation platform API.
Macuse
Let your AI assistant directly manage calendar, email, notes, and control any Mac app.
FreelanceOS
Freelance business manager — clients, proposals, invoices, time tracking, scope, and follow-ups. 37 MCP tools.
Tellers.AI - Prompt Based Video Editing
Give video editing skills to your agent
PostalForm MCP
Mail real letters from agents: PDF → checkout → status.
Anki MCP
A MCP server that enables AI assistants to interact with Anki, the spaced repetition flashcard application.
Google Spreadsheet MCP
Full Google Sheets integration - read, write, format cells, create charts, use formulas, and manage spreadsheets.
MCBU Campus Assistant
A chatbot for Manisa Celal Bayar University student affairs, featuring a web scraper, student database, and API integration tools for automation.