skill-router

name	skill-router
description	自动帮你在已安装的 200+ 技能中找到最合适的一个。说一句话，它替你挑 skill——写论文、查 GitHub、读文献、做 PPT，自动匹配。支持多技能串联/并行编排，找不到还能自动搜索 skills.sh 安装。所有路由行为带 [skill-router] 审计前缀。
triggers	["route","路由","不知道用什么技能","有什么skill","which skill","skill推荐","skill routing","自动匹配技能","帮我找skill","推荐skill"]

Skill Router — LIFECYCLE (MUST FOLLOW)

CRITICAL: This is a meta-skill. It does NOT do work itself. It routes.

HUMAN-IN-THE-LOOP: Every routing decision requires user confirmation. skill-router does NOT auto-execute anything. It proposes, user disposes. At every decision point — load a skill, run a pipeline, install from network — skill-router presents the plan and waits for explicit user approval.

User: "帮我写论文"
  → skill-router: 检测到 paper-reading (0.92)，加载吗？
  → User: 加载
  → skill-router: 加载 paper-reading，开始工作
  → skill-router: 完成，结果满意吗？
  → User: 满意 / 不满意（重新路由）

Every output line from this skill MUST be prefixed with [skill-router]. This makes the audit trail grep-able across sessions. grep '\[skill-router\]' in any transcript to see what fired.

[skill-router] ┌─ ENTRY GUARD ─→ SCAN ─→ MATCH ─→ LOAD GUARD ─→ Load skill ─→ VERIFY HOOK ─→ CONTROL HOOK ─┐
[skill-router] └────────────────────────── persistent loop ────────────────────────────────────────────────┘

Works across Claude Code, WorkBuddy, OpenCode, Gemini CLI, Codex, OpenClaw, Cursor, and any platform that uses SKILL.md.

---

1. ENTRY GUARD — ROUTE OR CHAT?

FIRST thing you do when this skill is loaded. Before any scan, any match — decide: does this user message need routing at all?

If the user is clearly just chatting:

• Greetings ("你好", "hello")
• Simple factual questions ("Python 怎么排序", "今天天气")
• Casual conversation → Exit router. Do NOT prefix anything. Reply normally.

If the user describes a task, names a domain, or asks "帮" + verb: → Enter SCAN phase.

Rule: When in doubt, route. False positives waste 5 seconds. False negatives miss the right skill entirely.

---

2. SCAN — DISCOVER ALL INSTALLED SKILLS

This is mandatory. You MUST NOT skip this phase.

Read every SKILL.md you can find. Extract name, description, and triggers from YAML frontmatter.

Check these locations in order:

Priority	Level	Paths
1st	Project	.claude/skills/*/SKILL.md, .workbuddy/skills/*/SKILL.md, .opencode/skills/*/SKILL.md, .gemini/skills/*/SKILL.md, .codex/skills/*/SKILL.md, .openclaw/skills/*/SKILL.md, .cursor/skills/*/SKILL.md, .agents/skills/*/SKILL.md
2nd	User	~/.claude/skills/*/SKILL.md, ~/.workbuddy/skills/*/SKILL.md, ~/.config/opencode/skills/*/SKILL.md, ~/.gemini/skills/*/SKILL.md, ~/.codex/skills/*/SKILL.md, ~/.openclaw/skills/*/SKILL.md, ~/.agents/skills/*/SKILL.md

Rules:

• Same-name skills: project-level wins over user-level.
• Missing dir: skip silently.
• No frontmatter: dir name as fallback.
• Do NOT scan hidden dirs (.git/, __pycache__/, etc.).
• Report: [skill-router] Scanned {N} skills across {M} platforms: {list}.

---

3. MATCH — COMPARE AGAINST USER INTENT

Compare the user's request against each scanned skill's name, description, and triggers.

Level	Condition	Action
High (≥0.85)	Exact trigger match or unambiguous semantic match	Load immediately. Do NOT ask.
Medium (0.5–0.85)	Semantic match, not exact	Show ≥2 options with scores. Let user pick.
Low (<0.5)	Multiple partial matches	Show all. Ask clarifying questions.
No match	Nothing relevant	Go to network fallback.

Cross-Domain Detection (run after scoring)

Before presenting results, check for multi-intent signals:

Linguistic signals (user expresses ≥2 intents):

• Chinese: "又...又...", "既要...又要...", "和", "还有", "然后", "之后"
• English: "and also", "plus", "then", "after that", "first...then"

Candidate signals (matches span different domains):

• ≥2 candidates with scores in [0.5, 0.85] range
• OR ≥2 High candidates from different domains
• Candidate tags have NO intersection → different domains

Decision:

• cross_domain = true → BOTH signal types present
• cross_domain = possible → only linguistic signal detected
• Record candidate list for Section 4

CRITICAL: Do NOT invent skills. Do NOT guess. If not found → fallback.

---

4. LOAD GUARD — VERIFY BEFORE LOADING

After match, do NOT load anything yet. Pass through this guard. Every path requires user confirmation.

Match	Guard action
High	Announce + ask once: [skill-router] 匹配到 {skill} ({score})，加载这个 skill 吗？
Medium	Present options with scores. User MUST pick.
Medium + cross_domain=true	Present options + pipeline/compose suggestion (Section 9).
Low	Ask clarifying. Re-match.
None	Network fallback.

User declines high match → Ask: "要不要试试其他候选？" or exit routing. If user says no to all: exit gracefully. [skill-router] Control: no skill selected — user declined.

If error during loading: call VERIFY HOOK → failure path.

---

5. NETWORK FALLBACK

If no installed skill matches:

1. npx skills find "<describe need in 5-10 English words>"
2. Present up to 3 options with name + description + install command.
3. User confirms → npx skills add <owner/repo@skill> -g -y
4. After install, skill is immediately available.

If npx not available → suggest skills.sh or GitHub.

---

6. VERIFY HOOK — CHECK EXECUTION RESULT

After the loaded skill finishes, ask the user for feedback:

[skill-router] {skill} 执行完成。结果满意吗？

• User confirms (✅) → Move to CONTROL HOOK.
• User rejects (❌ or "不行", "不对") → [skill-router] Unloading {skill}. 重新匹配... → Return to SCAN for next candidate. → If 2 consecutive failures: ask user to clarify their request.

Success: Skill ran without errors (user will decide relevance). Failure: Skill errored or produced empty output. → [skill-router] Verify: ❌ {skill} — execution error → Unload. Return to SCAN for next candidate.

CRITICAL: The user, not the system, decides whether the result is acceptable. Do NOT skip the satisfaction check even if the skill "looks correct."

---

7. CONTROL HOOK — PERSISTENT SESSION WITH BOUNDARY GUARD

After route + execution, the router stays active — but does not re-route silently. A BOUNDARY GUARD runs on each new user message:

New message
    │
    ▼
┌──────────────────────────────────────────┐
│  BOUNDARY GUARD                          │
│  Match msg ↔ current skill domain        │
├──────────────────────────────────────────┤
│  ≥0.85  → stay silent, pass thru         │
│  <0.85  → is user asking for a skill?    │
│    ├ YES (帮/找/推荐skill/which/路由) → ask│
│    └ NO → stay silent, pass thru         │
└──────────────────────────────────────────┘

Critical: BOUNDARY GUARD is silent by default. It only speaks when the user literally asks for routing help. This avoids wasting context turns on "do you need a skill?" noise in long-running sessions.

Rules:

• ≥0.85 (same thread) → Stay silent. Pass through. Never mention routing.
• <0.85 + user asks for skill ("帮我找 sdkill", "推荐 skill", "有XX技能吗", "which skill", "路由") → Ask once: [skill-router] 需要我帮你找合适的 skill 吗？
  • Confirms → Enter SCAN → MATCH → LOAD GUARD.
  • Declines → Pass through. This session's BOUNDARY GUARD is suppressed.
• <0.85 + user does NOT ask for skill → Stay silent. Pass through. Do NOT ask.
• CRITICAL: Do NOT re-route automatically. Do NOT ask unprompted. The BOUNDARY GUARD is a listener with a hotkey, not a greeter.

---

8. OUTPUT FORMAT — GREP-ABLE CONTRACT

Every route step MUST prefix with [skill-router]. Example:

[skill-router] Entry: wants routing — task detected
[skill-router] Scan: 46 skills across 3 platforms
[skill-router] Match: paper-reading (high ~0.92) — trigger "论文" matches
[skill-router] Load Guard: Passed (≥0.85)
[skill-router] Verify: ✅ paper-reading completed correctly
[skill-router] Control: waiting — thread active

Failure format:

[skill-router] Match: no match found
[skill-router] Fallback: searching skills.sh...
[skill-router] Found "thesis-writer" (write academic papers). Install?

Multi-skill format:

[skill-router] Entry: wants routing — multi-domain
[skill-router] Scan: 46 skills
[skill-router] Match: pipeline detected — paper-reading → thesis-writing
[skill-router] Load Guard: Proposing pipeline to user

---

9. MULTI-SKILL ROUTING

When to propose (triggered from Section 4 when cross_domain=true):

Present user with a concise choice in 1 round:

[skill-router] 检测到多领域需求，请选择执行方式：
  1. Pipeline（顺序执行）：A 完成后，将结果传给 B
  2. Compose（组合执行）：A 和 B 同时使用，各自处理任务的不同部分
  3. 单独执行某个技能（{list individual skills}）

Patterns:

Pattern	When to use	Execution
Pipeline (A → B)	User says "先...再...", "然后", "step by step"	Load A → run → capture output → load B with output → VERIFY at end
Compose (A + B)	User says "同时", "一起", domains are independent	Load both → run together → merge outputs → VERIFY
Parallel (A ∥ B)	User wants independent results merged	Load both → run independently → merge → VERIFY

Execution rules:

1. Execute ONE skill at a time (no parallel API calls)
2. Pass context explicitly: "A 的输出是：{output}. 现在用 B 处理。"
3. After all skills run → VERIFY HOOK with combined output
4. If user picks "单独执行" → fall back to normal single-skill load

CRITICAL: Never auto-execute multi-skill without user confirmation. Always present the plan first.

---

10. LOGGING (OPT-IN)

If the user has given explicit consent: Append a JSONL line to ~/.skill-router/log.jsonl after each route:

{"ts":"2026-05-07T09:00:00","prompt":"帮我写论文","matched":"paper-reading","score":0.92,"verify":"success"}

Do NOT log without asking the user first. When asked, explain: "This logs routing outcomes locally to measure accuracy. No data leaves your machine. Opt in?"

---

11. COMPLIANCE CHECKLIST

#	Check	Pass
1	Did I pass ENTRY GUARD (route or chat)?	☐
2	Did I SCAN actual directories (not guess)?	☐
3	Did I compare against ALL scanned skills?	☐
4	Did I ask user before loading (even high match)?	☐
5	Did I prefix every output with [skill-router]?	☐
6	Did I ask user satisfaction after skill execution?	☐
7	Did I run BOUNDARY GUARD before re-routing or staying silent?	☐
8	Did I get user confirmation before any external action (install/network)?	☐

If any box is unchecked, you skipped a step. Fix it.