An intelligent local knowledge assistant that imports documents into OpenClaw and automatically generates retrieval practice exercises to improve memory retention.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install openclaw-knowledge-coach
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install openclaw-knowledge-coach using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is OpenClaw Knowledge Coach?
The OpenClaw Knowledge Coach is a powerful utility designed to bridge the gap between static information storage and active knowledge mastery. By leveraging the OpenPraxis CLI, this skill enables users to build a local knowledge assistant that does more than just index files; it proactively creates practice materials like free-recall prompts, Q&A pairs, and application-based scenarios. This approach ensures that your personal documentation becomes a source of continuous learning rather than just a digital archive.
Built for developers and power users who value privacy and local execution, this skill is a cornerstone of the Openclaw Skills ecosystem. It supports various file types, including Markdown and images with built-in OCR, allowing you to ingest diverse data sources and immediately generate a review queue based on spaced repetition principles. Whether you are studying for a certification or mastering a new codebase, this coach automates the pedagogical heavy lifting.
OpenClaw Knowledge Coach Use Cases
- Automating the creation of flashcards and quizzes from technical documentation.
- Managing personal knowledge bases with structured metadata and chunking.
- Setting up spaced repetition schedules for long-term retention of local notes.
- Extracting knowledge from image-based notes using integrated OCR.
- Generating scenario-based questions to test the application of stored concepts.
How OpenClaw Knowledge Coach Works
- Confirm the knowledge domain and source folders containing the target files.
- Normalize the source data into a standardized record format with unique document IDs.
- Split long-form content into manageable chunks with stable, deterministic IDs.
- Ingest the normalized records into the local OpenClaw knowledge base.
- Generate retrieval exercises (free-recall, QA, or application) for every ingested chunk.
- Build a review queue using spaced repetition intervals to ensure long-term mastery.
OpenClaw Knowledge Coach Setup
To get started with this skill, install the OpenPraxis CLI via pip:
pip install openpraxis
praxis llm setup
You can also configure your preferred LLM provider and API keys using environment variables:
export OPENAI_API_KEY="your_key_here"
# Or use ARK_API_KEY, MOONSHOT_API_KEY, etc.
Verify your configuration with:
praxis llm show
OpenClaw Knowledge Coach Data Schema & Taxonomy
The skill organizes knowledge using a deterministic mapping system to ensure consistency across updates. Exercises and insights are structured as follows:
| Field | Description |
|---|---|
| doc_id | Unique identifier for the source document |
| chunk_id | Stable ID for specific content segments (e.g., doc_id#chunk-001) |
| exercise_id | Unique ID for generated practice scenes |
| type | The exercise category: free-recall, qa, or application |
| next_review | Scheduled date for the next spaced repetition session |
OpenClaw Knowledge Coach Advanced Features
- Multi-type exercise generation including free-recall and scenario-based application.
- Built-in OCR extraction for processing image-based notes and diagrams.
- Export capabilities to Markdown or JSON for integration with other Openclaw Skills.
- One-shot runtime model overrides for specific ingestion tasks.
- Deterministic ID mapping to prevent duplicate content and track learning progress over time.
SKILL.md
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