Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Advanced expert in prompt engineering, custom instructions design, and prompt optimization for AI agents
Advanced expert in prompt engineering, custom instructions design, and prompt optimization for AI agents
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
This skill equips Claude with deep expertise in prompt engineering, custom instructions design, and prompt optimization. It provides comprehensive guidance on crafting effective AI prompts, designing agent instructions, and iteratively improving prompt performance.
Prompt Writing Best Practices: Expert guidance on clear, direct prompts with proper structure and formatting Custom Instructions Design: Creating effective system prompts and custom instructions for AI agents Prompt Optimization: Analyzing, refining, and improving existing prompts for better performance Advanced Techniques: Chain-of-thought prompting, few-shot examples, XML tags, role-based prompting Evaluation & Testing: Developing test cases and success criteria for prompt evaluation Anti-patterns Recognition: Identifying and correcting common prompt engineering mistakes Context Management: Optimizing token usage and context window management Multimodal Prompting: Guidance on vision, embeddings, and file-based prompts
Refining vague or ineffective prompts Creating specialized system prompts for specific domains Designing custom instructions for AI agents and skills Optimizing prompts for consistency and reliability Teaching prompt engineering best practices Debugging prompt performance issues Creating prompt templates for reusable workflows
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.