Skill: mupengi-bot/learning-engine (version 1.0.1)

--- name: learning-engine description: Auto-analyze mistake and success patterns and reflect in skills author: 무펭이 🐧 --- # learning-engine System records mistakes and successes, automatically learns patterns to improve skills. Automates "don't repeat same mistake" principle. ## Learning Sources ### 1. memory/errors/ Extract failure patterns from error logs ```markdown # memory/errors/2026-02-14.md ## 10:30 - insta-post failure - Cause: PNG file upload → "Problem occurred" error - Fix: Retry after JPG conversion → Success - Lesson: Always convert to JPG before Instagram upload ``` ### 2. self-eval Results Extract improvement points from weekly self-evaluation ```markdown # memory/self-eval/2026-W07.md ## This Week's Mistakes - Too many browser snapshots (token waste) - → Improvement: Call API directly via exec ## This Week's Successes - 95% token savings with insta-cli v2 DM check ``` ### 3. performance Data Learn successful/unsuccessful patterns from performance tracking ```json { "insight": "Posts at 7-9 PM get +30% likes", "rule": "Instagram posts recommended 19:00-21:00" } ``` ## Auto Rule Generation Convert learned patterns to rules: **Location**: `memory/learned-rules/` ``` memory/ learned-rules/ instagram-posting.md browser-automation.md api-usage.md error-recovery.md ``` ### Rule Format ```markdown # Instagram Posting Rules ## Rule #1: Always Convert to JPG - **Situation**: Upload image to Instagram - **Failure Pattern**: PNG file → "Problem occurred" - **Solution**: `convert input.png -quality 92 output.jpg` - **Evidence**: 2026-02-10, 2026-02-14 error logs - **Applied Skills**: insta-post, cardnews, social-publisher ## Rule #2: 1:1 Ratio Required - **Situation**: Instagram card news - **Failure Pattern**: 16:9 horizontal → Cropped in feed - **Solution**: Generate as 1024x1024 square - **Evidence**: 2026-02-13 feedback - **Applied Skills**: cardnews, nano-banana-pro ``` ## Inject Rules into Skills Auto-add learned rules to relevant skill SKILL.md: **Location**: `skills/{skill-name}/SKILL.md` ```markdown # insta-post ... ## Learned Lessons ### Image Processing - ✅ Always convert to JPG (PNG causes errors) - ✅ 1:1 ratio required (1024x1024 recommended) - ✅ File size < 8MB ### Timing - ✅ Posts at 19:00-21:00 get +30% engagement - ❌ Avoid early morning posts ### Automation - ✅ Call API via exec (0 snapshots) - ❌ Minimize browser automation ``` ## Weekly Learning Report Auto-generated every Monday: **Location**: `memory/learning/weekly-YYYY-Www.md` ```markdown # 2026-W07 Learning Report ## New Learnings (5) 1. **Instagram PNG Ban** - 3 mistakes → Rule created - Applied: insta-post, cardnews 2. **Token Saving: exec > Browser** - v1: 5 snapshots → v2: 1 exec - 95% savings 3. **Optimal Posting Time** - 19:00-21:00 +30% likes 4. **Brand Tone Effect** - 무펭이 tone +40% engagement 5. **Auto Error Recovery** - browser-dependent failure → Browser restart ## Applied Skills - insta-post (2 rules) - cardnews (1 rule) - performance-tracker (1 insight) ## Next Week Goals - [ ] Build A/B testing system - [ ] Add 3 auto-recovery patterns ``` ## Event Publishing Publish event when learning complete: **Location**: `events/lesson-learned-YYYY-MM-DD.json` ```json { "timestamp": "2026-02-14T23:00:00Z", "source": "learning-engine", "new_rules": 2, "updated_skills": ["insta-post", "cardnews"], "summary": "Learned 2 Instagram image rules" } ``` ## hook-engine Integration - **on-error hook**: Error occurs → Record to memory/errors/ → learning-engine analysis - **post-hook (self-eval)**: After weekly evaluation → Update learning rules - **post-hook (performance)**: After collecting performance data → Learn patterns - **scheduled hook**: Every Monday → Generate weekly learning report ## Learning Pipeline ``` Error occurs ↓ Record to memory/errors/ ↓ learning-engine analysis ↓ Extract patterns + Create rules ↓ Save to memory/learned-rules/ ↓ Auto-update relevant skill SKILL.md ↓ Publish event (lesson-learned) ↓ Reflect in weekly report ``` ## Trigger Keywords - "what did I learn" - "learning" - "lessons" - "mistake patterns" - "improvements" - "learning report" - "add rule" ## Usage Examples ``` "What did I learn this week?" → Generate weekly learning report "Organize Instagram posting mistake patterns" → Analyze memory/errors/ + Create rules "Learn from performance data" → Extract successful patterns + Update rules ``` ## Auto-improvement Examples ### Before (Pre-learning) ``` Instagram post fails → Manually convert to JPG → Retry (Repeat every time) ``` ### After (Post-learning) ``` Execute insta-post → Auto-check/convert JPG → Success (Rule injected into SKILL.md) ``` ## Meta Learning learning-engine itself also learns: - "Which rules are used most?" - "Which skills improve most?" - "Which areas have slow learning?" **Meta Learning Report**: `memory/learning/meta-YYYY-MM.md` ## Future Improvements - [ ] Rule conflict detection (Rule A vs Rule B) - [ ] Rule confidence score (based on usage frequency) - [ ] Auto A/B testing (rule validation) - [ ] Share learning with other agents --- > 🐧 Built by **무펭이** — [Mupengism](https://github.com/mupeng) ecosystem skill


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (HIGH)