A comprehensive framework for transforming vague requests into precise, high-performance LLM prompts through systematic analysis and iterative refinement.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install prompt-engineering-2
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-engineering-2 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 Engineering?
The Prompt Engineering skill provides a professional-grade methodology for designing, optimizing, and validating prompts for large language models. It moves beyond simple trial-and-error by offering a structured workflow that includes deep context gathering, task classification, and strategic implementation of advanced prompting techniques.
By integrating this skill into your workflow, you can ensure that your AI interactions are reliable, cost-effective, and perfectly aligned with your objectives. This framework is essential for developers and researchers who use Openclaw Skills to bridge the gap between human intent and technical AI execution, resulting in higher quality outputs and more robust agent behaviors.
Prompt Engineering Use Cases
- Creating complex multi-step reasoning prompts for analytical tasks
- Optimizing underperforming prompts to improve accuracy and consistency
- Translating vague business requirements into structured prompt templates
- Developing high-stakes prompts with built-in validation and self-consistency checks
- Standardizing prompt development across multi-agent environments
How Prompt Engineering Works
- Exploration: Uncover the user's true needs through strategic questioning about task goals, success factors, and constraints.
- Analysis: Classify the task by complexity and output type to select the optimal strategy, such as Chain-of-Thought or Few-Shot learning.
- Implementation: Build the prompt iteratively, starting with a Minimal Viable Prompt and refining it through progressive disclosure.
- Validation: Conduct rigorous checks for clarity, completeness, and robustness against edge cases.
- Refinement: Use the optimization workflow to diagnose root causes of failures and apply minimal, targeted edits.
Prompt Engineering Setup
To begin using the prompt engineering framework, ensure the skill is installed in your local directory. Access the library of techniques and patterns to guide your design process.
# Example of referencing the skill in your project
openclaw install prompt-engineering
Review the local reference documentation located in the references folder to familiarize yourself with the evaluation framework and pattern library.
Prompt Engineering Data Schema & Taxonomy
The skill organizes its prompt development lifecycle using structured markdown files and a decision-based taxonomy:
| Component | Description | Storage Format |
|---|---|---|
| Prompt Metadata | Version history, design decisions, and limitations | YAML Frontmatter |
| Technique Catalog | Library of specialized prompting methods | techniques.md |
| Pattern Library | Reusable prompt templates for common scenarios | patterns.md |
| Validation Matrix | Quality criteria and evaluation frameworks | evaluation.md |
| Success Metrics | Output examples and performance benchmarks | examples.md |
Prompt Engineering Advanced Features
- Workflow Decision Tree: Automatically routes tasks based on whether the user needs creation, optimization, or bug fixing.
- Multi-Strategy Selection: Recommends specific techniques like Self-Consistency or Few-Shot learning based on task classification.
- Strategy Trade-off Analysis: Evaluates different prompt approaches based on token efficiency vs. output detail.
- Integrated Antipattern Detection: Proactively identifies and fixes common prompting mistakes during the analysis phase.
- Comprehensive Reference Suite: Built-in documentation for advanced pattern application within Openclaw Skills.
SKILL.md
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