A sophisticated prompt engineering tool designed to analyze, extract, and compress long instructions into high-density, token-efficient formats.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install prompt-compress
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 prompt-compress 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 Prompt Compress?
Prompt Compress is an essential utility within the Openclaw Skills ecosystem focused on maximizing the efficiency of Large Language Model (LLM) interactions. By identifying core tasks and eliminating redundant fillers, polite phrases, and common-sense fluff, it ensures that your prompts remain semantically intact while significantly lowering API costs and latency.
This skill transforms natural language into structured, high-density representations. Whether you are dealing with context window limitations or simply trying to optimize your development budget, Prompt Compress provides the logical framework to strip away the noise and keep the signal.
Prompt Compress Use Cases
- Reducing long prompts to save on token costs and stay within context window limits.
- Extracting core keywords and constraints from complex user instructions.
- Optimizing prompt structure for better model adherence and faster processing.
- Handling over-length context inputs by summarizing and compressing historical data.
- Streamlining RAG (Retrieval-Augmented Generation) outputs before feeding them to a model.
How Prompt Compress Works
- Initial Analysis: The skill identifies the core task, key constraints, and redundant content such as polite language or repetitive descriptions.
- Keyword Extraction: It prioritizes nouns and verbs over adjectives, preserving technical terminology and specific names while discarding generic modifiers.
- Structured Transformation: Natural language sentences are converted into structured formats using brackets and symbols (e.g., [Task] instead of "Please help me with...").
- Compression Application: Specific strategies like symbol replacement and content merging are applied based on the desired compression level.
- Validation & Output: The system calculates the savings ratio and outputs the high-density prompt alongside token statistics.
Prompt Compress Setup
To integrate this skill into your environment, follow these steps:
# Add the prompt-compress skill to your local agent
openclaw install prompt-compress
# Configure compression intensity (Light, Medium, Heavy, Extreme)
openclaw config prompt-compress --level medium
Once installed, you can trigger the skill using keywords like 'compress prompt' or 'optimize tokens' within the Openclaw Skills framework.
Prompt Compress Data Schema & Taxonomy
The skill organizes data using a structured summary format to ensure transparency in token savings.
| Metadata Field | Description |
|---|---|
| Original Tokens | The count of tokens in the raw input prompt |
| Compressed Tokens | The count of tokens after optimization |
| Savings Ratio | The percentage of tokens removed (e.g., 60%) |
| Compressed Content | The final optimized string ready for LLM consumption |
| Compression Level | Categorized as Light (20-30%), Medium (40-60%), Heavy (60-80%), or Extreme (80%+) |
Prompt Compress Advanced Features
- Multi-level compression intensity tailored for different LLM reasoning capabilities.
- Integration with RAG workflows to compress retrieved document snippets before injection.
- Symbolic replacement engine that converts verbose instructions into mathematical or logical notation.
- Contextual memory compression for maintaining long-running conversations without hitting token caps.
- Support for structured templates like JSON or Markdown to improve model parsing efficiency.
SKILL.md
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