/install skill-distiller
Skill Distiller
Trigger Phrases
Methodology solidification, process standardization, experience extraction, pattern refinement, system building.
Philosophy
A good skill turns "fuzzy wisdom" into "clear paths."
The essence of any quality skill is a closed loop: Problem-Driven → Theory Anchored → Process Solidified → Tools Implemented
Workflow (Four-Step Method)
Step 1: Precisely Define the Problem
Goal: Clearly articulate "what exactly is the problem" rather than "what you want to do."
Guiding Questions:
- How often does this problem occur?
- How much time/energy does this problem consume?
- Have you tried to solve it before? How? Where did you get stuck?
- If this problem were completely solved, what changes would it bring?
Output Format:
## Problem Definition
### Problem Description
[State it in one sentence]
### Trigger Scenarios
- Scenario A:
- Scenario B:
### Pain Point Severity
[Rated 1-5], impacting [what]
### Known Attempts
| Solution | Effect | Blockers |
|----------|--------|----------|
| ... | ... | ... |
Step 2: Find Theoretical Support
Goal: Find the "underlying principles" that are documented and logically sound for solving this problem.
Theory Source Priority:
- Expert Methodologies — Specific practices of domain experts (e.g., STEP framework from Contagious, MECE from The Pyramid Principle)
- Classic Theories — Frameworks with academic or practical validation (e.g., AIDA, FOGRA, SMART)
- Industry Consensus — Widely recognized standards in the field
- Cross-Domain Transfer — Logic validated in other domains, transferred to the current problem
Guiding Questions:
- In this domain, are there recognized experts or books?
- Are there existing frameworks or formulas that can be used?
- If you were to teach someone else, how would you explain it?
Output Format:
## Theoretical Support
### Core Theory
- **Theory Name**: [Name it]
- **Source**: [Book/Course/Expert/Original]
- **Core Idea**: State it in one sentence
### Theory Excerpt
> [Key original text]
### How to Apply the Theory
[How this theory solves your problem]
### Additional References
- Reference A:
- Reference B:
Step 3: Structure the Process
Goal: Turn the theory into an actionable set of steps.
Principles:
- Each step is executable and verifiable
- Clear inputs and outputs
- Closed loop: output of previous step is input of next step
- Fallback plans for exceptions
Guiding Questions:
- What is the first step?
- After completing the first step, how do you know it was done correctly?
- What is the input for the second step?
- Loop until closed
Output Format:
## Process Specification
### Process Overview
[Process Name]: [Starting Point] → [Step 1] → [Step 2] → ... → [Closing Point]
### Detailed Steps
#### Step 1: [Step Name]
- **Input**:
- **Action**:
- **Output**:
- **Success Criteria**: [How to know this step is done well]
- **Exception Handling**: [What to do if something goes wrong]
#### Step 2: [Step Name]
... (same structure as above)
### Closed-Loop Validation
- Can you return to Step 1 from the final step? ✅/❌
- Does each step have a clear output? ✅/❌
- Are exceptions handled? ✅/❌
Step 4: Provide Execution Tools
Goal: Provide tool support for the entire process, enabling automated or semi-automated execution.
Tool Types:
- Information Collection: Search, RSS, crawlers
- Content Generation: Templates, prompts
- Automation Execution: Scripts, workflows
- Storage Management: Note-taking systems, file structures
- Validation: Checklists, evaluation criteria
Guiding Questions:
- Which steps in this process are repetitive?
- Which steps can be templated?
- Which steps are currently the most time-consuming?
- To what extent do you want automation?
Output Format:
## Execution Tools
### Tool Inventory
| Tool | Type | Purpose | Automation Level |
|------|------|---------|------------------|
| ... | ... | ... | ... |
### Prompt Templates
#### [Scenario Name]
[Prompt text]
### Templates/Checklists
#### [Template Name]
[Template content]
### Automation Scripts
- Script Path: [Path]
- Function: [What it does]
- Usage: [How to use it]
Skill Output Summary
After completing the four steps, aggregate the output into an executable SKILL.md draft:
## [Skill Name]
**One-sentence description**: [What problem does this skill solve]
**Applicable Scenarios**:
- ...
**Process**: Problem → Theory → Process → Tools (detailed in respective sections)
---
[Paste the content from each section here]
Usage Tips
- Don't have to complete all four steps: If the user only wants to do one step (e.g., only define the problem), just do that step
- Iterate and refine: Start with a rough version, then refine after using it a few times
- Start small: Distill a small problem first, then gradually expand
- Don't overdo tools: One handy tool is more valuable than ten fancy ones
- Be specific about the problem: "I write slowly" is not a problem; "It takes me 2 hours just to figure out the opening for each short video script" is a problem
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install skill-distiller - 安装完成后,直接呼叫该 Skill 的名称或使用
/skill-distiller触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Skill Distiller 是什么?
Skill Distiller. Triggered when users encounter repetitive problems, need to systematize a solution in a certain domain, or want to solidify someone's method... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 111 次。
如何安装 Skill Distiller?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install skill-distiller」即可一键安装,无需额外配置。
Skill Distiller 是免费的吗?
是的,Skill Distiller 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Skill Distiller 支持哪些平台?
Skill Distiller 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Skill Distiller?
由 OpenLark(@openlark)开发并维护,当前版本 v1.0.0。