Agent skill recommender. Input a user need, task description, or existing skill list; output best matching skills, install rationale, duplicate/merge candida...
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设计与多媒体
Skill Design Guide
试用Design better AI skills with proven architecture patterns. Helps you decide Workflow vs Agent, pick the right pattern (Prompt Chaining, Routing, Parallelization, Orchestrator-Workers, Evaluator-Optimizer), write clean SKILL.md files, and catch common mistakes with a governance-aware quality checklist. Based on design principles from Anthropic, OpenAI, and LangChain.
它能做什么
Design better AI skills with proven architecture patterns. Helps you decide Workflow vs Agent, pick the right pattern (Prompt Chaining, Routing, Parallelization, Orchestrator-Workers, Evaluator-Optimizer), write clean SKILL.md files, and catch common mistakes with a governance-aware quality checklist. Based on design principles from Anthropic, OpenAI, and LangChain.
技能文档
Skill Design Guide
30-Second Test: If you're writing a SKILL.md or your skill "works but feels messy", load this guide.
🆚 What This Is (and Isn't)
| Tool | Purpose |
|---|---|
| skill-creator | HOW to structure a SKILL.md file |
| THIS GUIDE | WHY behind design decisions — Workflow vs Agent, which pattern |
This guide answers WHY, not HOW. See references/agent-design-research.md for full industry research background.
✅ 3 Usage Modes
| Mode | Trigger | Output |
|---|---|---|
| New Design | "I want to build a [X] skill" | Architecture blueprint (pattern + structure) |
| Skill Review | "Review this skill" / "Check quality" | Report via checklist |
| Pattern Selection | "Should I use X or Y?" | Pattern recommendation with rationale |
Hard Rules
These cannot be violated. They override all other considerations.
- Simplicity first. Start with a single SKILL.md. Add complexity only when simpler solutions fail.
- Brain ≠ Hands. LLM decides what to do (SKILL.md). Deterministic code does it (scripts/). Never mix them.
- No full preload. References are loaded on-demand. Never dump everything into context at once.
- Every skill must have: triggers, steps tagged
[Deterministic]/[LLM], Hard Rules, Failure Handling, Output Format.
Principle Zero: Simplicity First
Start simple. Add complexity only when simpler solutions fall short.
Practical checklist:
- Single SKILL.md before multiple files
- Deterministic code before LLM
- Fixed workflow before dynamic Agent
- Ship MVP, iterate from output quality
Principle One: Brain / Hands / Session
| Layer | Role | File |
|---|---|---|
| Brain | Decision logic, workflow definition | SKILL.md |
| Hands | Deterministic execution | scripts/ |
| Session | Knowledge base, config, templates | references/, assets/ |
Your skills already follow this: data-ai-daily-brief (scripts fetch data), benjie-model (Session layer for other skills).
Step 1: Workflow or Agent?
One question: Are the task steps predetermined?
| Type | When |
|---|---|
| Workflow | Steps are clear and predictable → choose this (faster, cheaper, debuggable) |
| Agent | Steps uncertain, need dynamic planning → choose this (flexible but costly) |
Most things are workflows. Don't pick Agent because it sounds advanced.
Step 2: Pick a Pattern
Five workflow patterns. Full details in references/pattern-details.md.
| Pattern | Best For |
|---|---|
| Prompt Chaining | Sequential steps with checkpoints |
| Routing | Clear input types → different paths |
| Parallelization | Independent subtasks |
| Orchestrator-Workers | Unpredictable subtasks (sparingly!) |
| Evaluator-Optimizer | Generate→Evaluate→Repeat until pass |
Step 3: Skill Structure
Required
| Component | Content |
|---|---|
| SKILL.md | YAML frontmatter (name, description, read_when) + workflow + Hard Rules + Failure Handling + Output Format |
Optional
| Component | When |
|---|---|
references/ | Domain knowledge (loaded on demand) |
scripts/ | Deterministic steps |
assets/ | Templates, configs |
SKILL.md Template
---
name: my-skill
description: One sentence. Trigger keywords: a, b, c.
version: 1.0.0
read_when:
- "trigger phrase 1"
- "trigger phrase 2"
---
# Skill Name
Overview paragraph.
## Workflow
### Step 1: [Deterministic] Confirm Input
- Validate input exists
- If missing, stop and report
### Step 2: [Deterministic] Load Materials
- Read `references/xxx.md` (only needed files)
### Step 3: [LLM] Core Execution
- Generate output following these rules:
- Rule 1
- Rule 2
### Step 4: [LLM] Self-Check
- Verify output meets criteria → fix → re-output
### Step 5: [Deterministic] Save Output
## Hard Rules
> These cannot be violated.
1. Rule 1
2. Rule 2
## Failure Handling
| Scenario | Action |
|----------|--------|
| Source file not found | Stop, report missing file |
| Output 50% over limit | Compress and rewrite |
## Output Format
[Define exact format and fields]
Step 4: Quality Checklist
After completing a skill, run the full governance-aware checklist. Load references/quality-checklist.md for details.
Structure ✓ | Principles ✓ | Tools ✓ | Guardrails ✓ | Observability ✓
Anti-Patterns
| Anti-Pattern | Fix |
|---|---|
| Over-engineering | Start with single SKILL.md |
| Full preload | Load references on-demand only |
| God Skill | Split duties — one skill, one thing |
| All-LLM | Scripts for deterministic steps |
| No guardrails | Add Hard Rules + Failure Handling |
| Vague output | Define exact format and fields |
| Publishing dirty | Before publishing, run skill-publish to audit and clean |
After Design: Publishing
When the skill is ready to share on ClawHub/GitHub, use skill-publish to audit and publish. It handles: personal data scanning, frontmatter validation, content cleanup, bilingual enforcement, file separation (local vs published), and dual-platform push.
Failure Handling (for this guide itself)
| Scenario | Action |
|---|---|
| User asks for code, not design | Redirect to skill-creator |
| Pattern comparison ambiguous | Load references/pattern-details.md |
| Review request without skill details | Ask: "Show me your SKILL.md or describe what the skill does" |
| User wants to publish a completed skill | Redirect to skill-publish |
References (on-demand)
| Need | Load |
|---|---|
| 25-point checklist | references/quality-checklist.md |
| Pattern deep dive | references/pattern-details.md |
| Platform-specific config | references/platform-compatibility.md |
| Industry research background | references/agent-design-research.md |
| Anthropic tool design | references/anthropic-tool-design.md |
| Publishing to ClawHub/GitHub | Use skill-publish (separate skill) |
v1.4.6 | Based on Anthropic/OpenAI/LangChain design principles | 2026-08-02
Changelog:
- v1.4.6: Published merged content to the correct slug
skill-design-guide-skill— restores 9metadata.openclaw.tags(discoverability) + 1.4.4 governance-aware checklist / Governance & Continuity checks. (Prior 1.4.5/1.4.6 attempts landed on a strayskill-design-guideslug by mistake; that duplicate should be deleted.) - v1.4.5: Restored
metadata.openclaw.tags(9 discoverability tags) dropped in the 1.4.4 sync; no content change beyond 1.4.4 governance additions - v1.4.4: Added governance checks for single source of truth, private-data separation, secret scanning, retry/re-run, external-action gates, and persistent task continuity
- v1.4.3: Restored display name "Skill Design Guide"
- v1.4.2: Consolidated
reference/+references/into a singlereferences/dir; fixed all reference paths - v1.4.1: Fixed display name
- v1.4.0: Refactored for progressive disclosure — split checklist/patterns/platform into
references/; added Hard Rules + Failure Handling; reduced SKILL.md from 13K to ~5K chars - v1.3.0: Added usage scenarios, Chinese version (SKILL_zh.md)
- v1.2.0: Platform-agnostic rewrite, added Credits
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