A specialized assistant for designing, optimizing, and deploying high-performance prompts tailored specifically for Anthropic Claude models.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install claude-prompt
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 claude-prompt 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 Claude Prompt Engineering Assistant?
The Claude Prompt Engineering Assistant is a sophisticated tool designed to help developers and AI enthusiasts harness the full potential of Anthropic Claude series models. By leveraging industry-leading best practices, this skill enables the creation of structured, reliable, and context-aware prompts that significantly improve model output quality and consistency.
As part of the Openclaw Skills ecosystem, this assistant specializes in advanced techniques such as XML tag structuring, Chain of Thought (CoT) reasoning, and precise role-setting. It bridges the gap between basic instructions and complex agentic behaviors, ensuring that your AI applications perform with professional-grade accuracy and safety.
Claude Prompt Engineering Assistant Use Cases
- Designing robust system prompts for production-grade AI applications.
- Optimizing existing prompts to reduce hallucinations and improve formatting.
- Building RAG (Retrieval-Augmented Generation) systems with precise retrieval instructions.
- Managing complex multi-turn dialogues and context windows for long-document analysis.
- Implementing few-shot examples to guide specific output styles and logic.
How Claude Prompt Engineering Assistant Works
- Analyze the user's intent to define a clear role and objective for the Claude model.
- Apply XML tags to wrap instructions, context, and data, providing a clear structural hierarchy that Claude natively understands.
- Implement reasoning chains within thinking tags to ensure the model processes complex tasks step-by-step.
- Incorporate few-shot learning examples to demonstrate the expected input-output mapping.
- Refine the output through prefilling techniques or specific format constraints (e.g., JSON or Markdown) to meet technical requirements.
Claude Prompt Engineering Assistant Setup
To integrate this skill into your environment, use the Openclaw Skills CLI for a seamless installation:
# Install the Claude Prompt skill
openclaw install claude-prompt-engineering
# Configure your model preferences
openclaw configure claude-prompt --version 3.5-sonnet
Claude Prompt Engineering Assistant Data Schema & Taxonomy
The skill organizes prompt components into a structured taxonomy for maximum clarity and reusability:
| Component | Tag / Structure | Purpose |
|---|---|---|
| Context | <context> |
Defines the background and environment for the task. |
| Task | <task> |
Outlines the specific action the AI must perform. |
| Examples | <examples> |
Contains few-shot input/output pairs for pattern matching. |
| Logic | <thinking> |
Used for Chain of Thought reasoning to improve accuracy. |
| Constraints | <output_format> |
Explicitly defines the desired structure of the response. |
Claude Prompt Engineering Assistant Advanced Features
- System Prompt Specialization: Create expert-level personas with 15+ years of domain-specific experience.
- Assistant Prefilling: Force JSON or code-only responses by pre-populating the assistant's starting message.
- Long Document Handling: Specialized templates for extracting information from massive context windows without loss of detail.
- Tool Call Integration: Optimized prompts for teaching Claude how to use external search or calculation tools accurately.
- Anti-Pattern Filtering: Automated identification and correction of vague instructions or multi-task overloading.
SKILL.md
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