skill-router

Context-based skill auto-routing + federated skill composition. Analyzes user input to auto-select single or multiple skills and execute in order. First gateway for all requests. Use on every request to determine optimal skill combination.

Meta system that analyzes natural language input to auto-select appropriate skill(s), determine order, and chain execution.

🚀 v2 Architecture: Low-level Call Protocol

Execution Flow

text

1. Scan only skills/*/SKILL.md frontmatter (trigger matching)
   - Quick match with description + trigger fields
   - No full body reading → 83% token savings
   
2. Check run field of matched skill for script path
   - run: "./run.sh" → skills/{name}/run.sh
   - run: "./run.js" → skills/{name}/run.js
   
3. Direct script execution with exec
   WORKSPACE=$HOME/.openclaw/workspace \
   EVENTS_DIR=$WORKSPACE/events \
   MEMORY_DIR=$WORKSPACE/memory \
   bash $WORKSPACE/skills/{name}/run.sh [args]
   
4. Agent processes stdout result
   - Parse if JSON
   - Pass through if text
   - Check stderr on error
   
5. Generate events based on events_out
   - Create events/{type}-{date}.json file
   - Subsequent skills consume via events_in
   
6. Check hooks → trigger subsequent skills
   - post: ["skill-a", "skill-b"] → auto-execute
   - on_error: ["notification-hub"] → notify on error

Skill Metadata Scan

bash

# Extract only frontmatter from all skills
for skill in skills/*/SKILL.md; do
  yq eval '.name, .description, .trigger, .run' "$skill"
done

Execution Example

bash

# User: "daily report"
# → trigger match: daily-report
# → Execute:
cd $HOME/.openclaw/workspace
WORKSPACE=$PWD \
EVENTS_DIR=$PWD/events \
MEMORY_DIR=$PWD/memory \
bash skills/daily-report/run.sh today

# Agent formats stdout result and delivers to user

Token Savings Effect

• Before: SKILL.md 3000 chars × 40 = 120KB (~30K tokens)
• v2: SKILL.md 500 chars × 40 = 20KB (~5K tokens)
• Savings: 83% token reduction

Core Concept

OpenClaw already selects 1 skill via description matching, but this skill:

1. Detect complex intent: "Analyze competitors and make card news" → competitor-watch + copywriting + cardnews + insta-post
2. Context-based auto-hooks: Auto-determine subsequent skills when a skill executes
3. Skill chain templates: Pre-define frequently used combinations

Intent Classification Matrix

Single Skill Mapping (1:1)

• "commit/push/git" → git-auto
• "DM/instagram message" → auto-reply
• "cost/tokens/how much" → tokenmeter
• "translate/to English" → translate
• "invoice/quote" → invoice-gen
• "code review/PR" → code-review
• "system status/health" → health-monitor
• "trends" → trend-radar
• "performance/reactions/likes" → performance-tracker
• "daily report" → daily-report
• "SEO audit" → seo-audit
• "brand tone" → brand-voice

Complex Skill Chains (1:N) — Core Pipelines

Trigger Pattern	Skill Chain	Description
"create content/post"	seo-content-planner → copywriting → cardnews → insta-post	Full content pipeline
"analyze competitors and report"	competitor-watch → daily-report → mail	Research→report
"summarize this video as card news"	yt-digest → content-recycler → cardnews → insta-post	Video→content conversion
"weekly review"	self-eval + tokenmeter + performance-tracker → daily-report	Comprehensive review
"recycle content"	performance-tracker → content-recycler → cardnews	Repackage successful content
"review idea and execute"	think-tank(brainstorm) → decision-log → skill-composer	Ideation→decision→execution
"market research"	competitor-watch + trend-radar + data-scraper → daily-report	Full research
"release"	code-review → git-auto → release-discipline	Safe deployment
"morning routine"	health-monitor → tokenmeter → notification-hub → daily-report	Morning auto-check

Context-based Auto-chain Rules

Skill A execution complete → analyze results → auto-determine next skill:

Auto-chain Rules (if → then)

• IF competitor-watch detects important change → THEN notification-hub(urgent) + include in daily-report
• IF tokenmeter exceeds $500/month → THEN notification-hub(urgent)
• IF code-review detects HIGH severity → THEN block commit + notification-hub
• IF think-tank conclusion has "immediate execution" action → THEN auto-record in decision-log
• IF cardnews generation complete → THEN confirm "post with insta-post?" (approval required)
• IF self-eval detects repeated mistake → THEN trigger learning-engine
• IF performance-tracker finds successful content → THEN suggest content-recycler
• IF trend-radar detects hot trend → THEN auto-suggest seo-content-planner
• IF mail detects important email → THEN notification-hub(important)
• IF health-monitor detects anomaly → THEN attempt auto-recovery + notification-hub(urgent)

Execution Engine Protocol

text

1. Receive user input
2. Classify intent (single vs complex)
3. If single → execute skill immediately
4. If complex → compose skill chain
   a. Skills without dependencies execute in parallel (sessions_spawn)
   b. Skills with dependencies execute sequentially (pass previous results via events/)
5. Check auto-chain rules on each skill completion
6. Auto-trigger additional skills if needed (or request approval)
7. Synthesize final results and respond

Auto-hook Registration

When skill-router activates, for all skills:

• pre-hook: Input validation + security check
• post-hook: Generate events/ event + check chain rules
• on-error: Error log + notification-hub

Skill Dependency Graph

text

[User Input]
    ↓
[skill-router] ← Intent classification
    ↓
┌─────────────────────────────────────────┐
│  TIER 1: Data Collection                │
│  competitor-watch, data-scraper,        │
│  trend-radar, tokenmeter, yt-digest     │
└─────────────┬───────────────────────────┘
              ↓ events/
┌─────────────────────────────────────────┐
│  TIER 2: Analysis/Thinking              │
│  think-tank, self-eval, seo-audit,      │
│  code-review, performance-tracker       │
└─────────────┬───────────────────────────┘
              ↓ events/
┌─────────────────────────────────────────┐
│  TIER 3: Production                     │
│  copywriting, cardnews, content-recycler,│
│  translate, invoice-gen                  │
└─────────────┬───────────────────────────┘
              ↓ events/
┌─────────────────────────────────────────┐
│  TIER 4: Deployment/Execution           │
│  insta-post, mail, git-auto,            │
│  release-discipline                     │
└─────────────┬───────────────────────────┘
              ↓ events/
┌─────────────────────────────────────────┐
│  TIER 5: Tracking/Learning              │
│  daily-report, decision-log,            │
│  learning-engine, notification-hub      │
└─────────────────────────────────────────┘

Safety Mechanisms

• Always require approval before external actions (email send, SNS post, payment)
• Prevent infinite loops: Stop after same skill chain repeats 3 times
• Cost limit: Max 5 subagents per chain
• Graceful stop on error + save partial results

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🐧 Built by 무펭이 — Mupengism ecosystem skill