An optimization utility for AI agents to handle large-scale knowledge documents through thematic chunking and indexed retrieval.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install md-knowledge-spliter
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 md-knowledge-spliter 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 Knowledge Splitter?
Knowledge Splitter is a technical utility designed to optimize how AI agents interact with extensive documentation within the Openclaw Skills ecosystem. When knowledge files grow too large—typically exceeding 5KB—loading the entire document into the agent's context window becomes inefficient and costly. This skill provides a structured methodology to break down large Markdown files into smaller, thematic chunks, ensuring high-speed access and reduced token consumption.
By leveraging a central index, the skill enables agents to perform surgical lookups. Instead of parsing a massive file, the agent identifies the relevant segment through tags and scenarios defined in a metadata file, significantly improving the accuracy and response time of information retrieval tasks.
Knowledge Splitter Use Cases
- Managing large project specifications or technical documentation that exceeds standard context limits.
- Organizing complex thematic knowledge bases for specialized AI research workflows.
- Implementing incremental updates to documentation without re-processing entire datasets.
- Improving agent performance by reducing the latency associated with reading large file buffers.
How Knowledge Splitter Works
- Analysis: The agent identifies a large knowledge file that triggers an optimization signal.
- Thematic Splitting: The document is partitioned into chunks (ideally <2KB) based on specific subjects or functional categories.
- Index Generation: An INDEX.md file is created within the directory to map each chunk to its corresponding tags and application scenarios.
- Metadata Lookup: When a query occurs, the agent first reads the INDEX.md to determine which chunk contains the necessary information.
- Targeted Retrieval: The agent loads only the specific chunk file or uses offset-based reading for precise data access.
Knowledge Splitter Setup
To implement this within your environment, ensure your knowledge directory follows the expected hierarchy. You can initialize the structure using standard terminal commands:
mkdir -p knowledge/your-topic-chunks
touch knowledge/your-topic-chunks/INDEX.md
Ensure that your Openclaw Skills configuration allows the agent to read and write within the knowledge/ path to maintain the index and chunks dynamically.
Knowledge Splitter Data Schema & Taxonomy
The skill organizes information using a directory-based taxonomy. This structure allows for both human-readable browsing and machine-optimized retrieval.
| File/Folder | Purpose | Format |
|---|---|---|
INDEX.md |
Central registry mapping chunks to tags and use cases. | Markdown Table |
XX-topic.md |
Individual content chunks (thematic fragments). | Markdown |
source_full.md |
Optional original document for full-text fallback. | Markdown |
The INDEX.md must contain a table with columns for File, Tags, and Applicable Scenarios to guide the agent's selection logic.
Knowledge Splitter Advanced Features
- Offset & Limit Support: Uses advanced file reading tools to specify exact byte offsets for granular data extraction.
- Semantic Tagging: Supports a robust metadata system within the index for high-precision matching of agent queries.
- Fallback Mechanisms: Automatically falls back to the full source file if the information found in a chunk is insufficient.
- Synchronized Indexing: Workflows to keep the chunk index in sync with manual updates to the knowledge base, ensuring Openclaw Skills always have access to current data.
SKILL.md
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