promptify

What This Skill Does

The Promptify skill serves as the primary intelligence layer for prompt engineering within OpenClaw. It is designed to transform vague, unstructured, or suboptimal user requests into high-fidelity, actionable prompts that yield significantly better results from any LLM. By leveraging an internal framework based on a four-part contract (Role, Task, Constraints, Output), Promptify ensures that every query is context-aware and structurally sound. It intelligently manages modifiers for deep research, web lookups, or user clarification, ensuring that the model has all necessary information before attempting a response.

Installation

To integrate this skill into your environment, run the following command in your terminal: clawhub install openclaw/skills/skills/tolibear/promptify

Use Cases

• Developer Productivity: When you need to refactor complex code or integrate a new API, Promptify triggers codebase research to ground the response in your specific project structure.
• Content Creation: Transform a simple "write an article" request into a structured brief that includes tone, audience targeting, and formatting constraints.
• Complex Problem Solving: Use it to break down high-level, vague goals into a multi-step analytical process (Analyze → Plan → Implement → Validate).
• Learning & Research: When you need the latest information, the web-researcher modifier ensures the model consults external sources for the most current data.

Example Prompts

1. "Optimize my prompt: I want to build a Python web scraper for a dynamic site. Make it clear and structured."
2. "Make this clearer: Help me write a blog post about AI agents. Use the +web modifier to find recent statistics."
3. "This project needs to refactor our user authentication module, use +deep to look at the existing codebase and suggest a more secure pattern."

Tips & Limitations

• Modifiers: Always append modifiers like +ask, +deep, or +web when you know your requirements. If you omit them, the agent will rely on auto-detection, which may occasionally require additional clarifying questions.
• XML Tags: Promptify heavily utilizes XML tagging for complex prompts; ensure the receiving model is capable of parsing XML for the best results.
• Scope: Promptify is a model-agnostic optimization tool. It optimizes the prompt structure but relies on the underlying LLM's capabilities to execute the final task effectively. Avoid using it for highly sensitive cryptographic operations that require internal, non-AI logic.