/install skill-forge-ai
Skill Forge v3.3
Forges high-quality SKILLs that auto-trigger reliably and produce stable, structured output. Full pipeline: adaptive interview → creation → self-validation (with security check) → SkillHub peer benchmarking.
When to Use
CRITICAL: You MUST invoke this skill IMMEDIATELY as your FIRST action when:
- User wants to create a new skill
- User wants to add a custom skill to the workspace
- User asks to set up a skill template
- User asks "how to create a skill"
- User mentions creating/adding/making any skill
DO NOT:
- Just explain how to create a skill without invoking this tool
- Provide manual instructions without calling this skill first
- Defer the skill creation to later steps
Three Iron Rules
Violating any rule = broken Skill.
Rule 1: Write Description FIRST — AI scans all Skill descriptions every conversation. Vague description = never auto-triggers = dead Skill.
Rule 2: One Skill = One Job — Don't cram multiple scenarios into one Skill. Multi-purpose Skills trigger chaotically and output inconsistently.
Rule 3: Keep under 150 lines — Over 200 lines = AI slows down and accuracy drops. Move detailed docs to references/ directory.
SKILL Structure
- Directory:
.trae/skills/\x3Cskill-name>/ - File:
SKILL.mdinside the directory - Optional:
references/for detailed docs (keep SKILL.md lean)
SKILL.md Format
---
name: "\x3Cskill-name>"
description: "\x3Cwhat it does + when to trigger. Core keywords in first 200 chars>"
---
# \x3CSkill Title>
## 任务
\x3COne sentence: only does X, does NOT do Y or Z>
## 输出格式
\x3CFixed output structure. Every field format must be concrete, never "organize clearly">
## 规则
\x3C3-5 hard rules. Each must be directly actionable by an intern. Delete all defaults>
## 示例
\x3COne complete input-output pair covering edge cases>
Required Fields
| Field | Location | Description |
|---|---|---|
name |
frontmatter | Unique identifier |
description |
frontmatter | CRITICAL: (1) what it does + (2) when to invoke + (3) Do NOT scope. Under 200 chars. Keywords FIRST. |
detail |
body | 4-module content after frontmatter |
Phase 0: Intent Recognition & Adaptive Interview
Read references/interview-flow.md for the complete interview methodology. Summary below.
Step 0.1: Element Check
Scan context for 5 essential elements: Single scenario / Trigger condition / Output format / Scope boundary / Hard constraints.
- ≥4 ready → Confirm with user, skip to Phase 1
- \x3C4 ready → Enter Adaptive Interview (Step 0.2)
Step 0.2: Adaptive Interview (2-5 rounds)
Read references/interview-flow.md NOW for: interview rules (B1-B6), round-by-round questions, recursive search pattern, and convergence check.
Summary: Each round uses option-first questions (AskUserQuestion, 3 strong + Other) + behavioral probing. After each round: update element checklist, ≥4 clear → proceed to Phase 1. Max 5 rounds.
Phase 1: Creation
Step 1: Write Description FIRST
Format: "\x3CWhat it does>. Invoke when \x3Cspecific user actions/phrases>. Do NOT use for \x3Cexclusions>."
Truncation: Core trigger keywords MUST be in first 200 chars. Tail gets cut at ~250.
Step 2: Write 4-module content
任务: Lock down boundary. State both DOES and DOES NOT.
输出格式: Fix output structure. Every field must have concrete format. Never write vague instructions.
规则: 3-5 rules only. Must pass Intern Test: if an intern can't directly execute it, delete it.
Delete useless rules: "语言简洁" / "保持客观" / "排版整齐" / "代码清晰" / "遵循最佳实践" / "确保输出准确"
示例: One complete input-output pair. Input MUST cover edge cases. One good example > 10 abstract rules.
Step 3: Create directory and file
mkdir -p .trae/skills/\x3Cskill-name>
Step 4: Self-Validation Pipeline
Step 4a: Schema Check — Frontmatter name+description ✅ | Description \x3C200 chars ✅ | Trigger keywords first ✅ | Do NOT scope ✅ | 4 modules ✅ | Intern Test ✅ | \x3C150 lines ✅ | Edge case in example ✅
Step 4a+1: Security Red Line Check — Scan created SKILL.md for these RED FLAGS. 🚨 If ANY found → REJECT and remove immediately:
- curl/wget to unknown URLs or sends data to external servers
- Requests credentials/tokens/API keys without clear reason
- Reads ~/.ssh, ~/.aws, ~/.config, MEMORY.md, USER.md, IDENTITY.md
- Uses base64 decode / eval() / exec() with external input
- Modifies system files outside workspace or requests sudo permissions
- Obfuscated code (compressed, encoded, minified)
- Accesses browser cookies/sessions or credential files If clean → proceed to Step 4b. If any red flag → remove, re-validate from Step 4a.
Step 4b: Trigger Test — AI generates 3 pos + 3 neg fake questions. Pos not triggering → add keywords. Neg triggering → add Do NOT.
Step 4c: Dogfood Simulation — Run example input through rules/format. Check: format match ✅ | rules compliance ✅ | edge cases handled ✅
Max 3 iterations. After 3, suggest "ship V1 and iterate."
Phase 2: SkillHub Peer Benchmarking
Read references/benchmarking-guide.md for the complete benchmarking methodology. Summary below.
Step 5a: Search & Rank
Call SkillHub API: https://api.skillhub.cn/api/v1/search?q=\x3Ckeywords>. Rank by: downloads × 0.4 + installs × 0.3 + stars × 0.3. Take Top 3. CLI fallback if API unavailable.
Step 5b: Tencent Manual Compliance Comparison
Compare our Skill against Top 3 peers on 9 Tencent Manual dimensions: Description trigger precision / keyword frontloading / Do NOT scope / one-job focus / 4-module structure / output format concreteness / Intern Test rules / edge case coverage / size control.
Step 5c: Differentiation & Gap Analysis
- Duplicate → recommend installing existing Skill
- Different → document differentiation clearly
- Blind spot → list with Tencent Manual justification
Step 5d: User Decision
Present results. User chooses: adopt fixes / keep as-is / install existing. User's decision is final.
References
references/interview-flow.md— Read when entering Step 0.2 (adaptive interview). Contains B1-B6 rules, round templates, recursive search pattern, convergence check.references/interview-methods.md— Read when you need deeper methodology on behavioral probing, bias detection, option design.references/benchmarking-guide.md— Read when entering Phase 2 (SkillHub benchmarking). Contains API usage, quality ranking formula, Tencent 9-dimension comparison template.references/meeting-action-extractor-example.md— Read when creating Step 2 content. Full example of a well-crafted Skill.
- 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-forge-ai - 安装完成后,直接呼叫该 Skill 的名称或使用
/skill-forge-ai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 Forge AI 是什么?
MANDATORY tool for creating SKILLs - MUST be invoked IMMEDIATELY when user wants to create/add any skill. Forges skills through adaptive interview, recursive... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 41 次。
如何安装 Skill Forge AI?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install skill-forge-ai」即可一键安装,无需额外配置。
Skill Forge AI 是免费的吗?
是的,Skill Forge AI 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Skill Forge AI 支持哪些平台?
Skill Forge AI 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 Forge AI?
由 AI花生(@edwardwason)开发并维护,当前版本 v3.3.0。