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

1. Directory: .trae/skills//
2. File: SKILL.md inside the directory
3. Optional: references/ for detailed docs (keep SKILL.md lean)

SKILL.md Format

---
name: "<skill-name>"
description: "<what it does + when to trigger. Core keywords in first 200 chars>"
---

# <Skill Title>

## 任务
<One sentence: only does X, does NOT do Y or Z>

## 输出格式
<Fixed output structure. Every field format must be concrete, never "organize clearly">

## 规则
<3-5 hard rules. Each must be directly actionable by an intern. Delete all defaults>

## 示例
<One complete input-output pair covering edge cases>

Required Fields

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
• <4 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: ". Invoke when . Do NOT use for ."

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/<skill-name>

Step 4: Self-Validation Pipeline

Step 4a: Schema Check — Frontmatter name+description ✅ | Description <200 chars ✅ | Trigger keywords first ✅ | Do NOT scope ✅ | 4 modules ✅ | Intern Test ✅ | <150 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=. 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.