Skill: zfanmy/skill-from-memory (version 0.1.2)

--- name: skill-from-memory description: Convert memory, conversation history, or completed tasks into publishable OpenClaw skills. Use when (1) A task or workflow should be reusable, (2) Extracting lessons from memory to create tools, (3) Packaging solved problems as skills for future use, (4) Publishing skills to GitHub and ClawHub registry. --- # Skill from Memory Transform your work into reusable skills. Extract workflows, solutions, and patterns from conversation history or memory files, package them as skills, and publish to GitHub and ClawHub. ## Overview This skill automates the complete workflow: 1. **Extract** - Parse conversation history or memory for reusable patterns 2. **Design** - Structure as a proper skill with SKILL.md and resources 3. **Create** - Generate skill files and scripts 4. **Publish** - Push to GitHub and publish to ClawHub ## Quick Start ### Create Skill from Recent Conversation ```bash # Analyze last conversation and create skill draft ./scripts/extract-from-history.sh /path/to/session.jsonl ./my-new-skill # Or specify a time range ./scripts/extract-from-history.sh /path/to/session.jsonl ./my-new-skill --since "2026-02-03" --pattern "backup" ``` ### Create Skill from Memory File ```bash # Extract from memory markdown ./scripts/extract-from-memory.sh /path/to/memory/2026-02-04.md ./my-new-skill ``` ### Full Auto-Create and Publish ```bash # One command: extract, create, and publish ./scripts/create-and-publish.sh \ --source /path/to/session.jsonl \ --skill-name "my-automation" \ --github-repo "user/my-skills" \ --clawhub-slug "my-automation" ``` ## Workflow Steps ### Step 1: Extract Requirements Identify from conversation/memory: - **Task Pattern**: What workflow was solved? - **Inputs/Outputs**: What goes in, what comes out? - **Scripts/Tools**: What code was written? - **Key Decisions**: What choices were made? ### Step 2: Design Skill Structure Decide resource types: - `scripts/` - For reusable code - `references/` - For documentation - `assets/` - For templates/files ### Step 3: Create Skill Files Generate: - `SKILL.md` with frontmatter and instructions - Scripts in `scripts/` - Any reference files ### Step 4: Publish Push to GitHub and publish to ClawHub: ```bash ./scripts/publish.sh ./my-skill \ --github "user/repo" \ --clawhub-slug "my-skill" \ --version "1.0.0" ``` ## Scripts Reference ### extract-from-history.sh Parse conversation JSONL for skill content. ```bash ./scripts/extract-from-history.sh <session.jsonl> <output-dir> [options] Options: --since DATE Only extract from DATE onwards --pattern REGEX Filter messages matching pattern --tools-only Only extract tool usage patterns ``` ### extract-from-memory.sh Parse memory markdown files. ```bash ./scripts/extract-from-memory.sh <memory.md> <output-dir> ``` ### create-skill.sh Generate skill structure from extracted content. ```bash ./scripts/create-skill.sh <extracted-content-dir> <skill-name> Options: --description "..." Skill description --type workflow Skill type (workflow|tool|reference) ``` ### publish.sh Complete publish workflow. ```bash ./scripts/publish.sh <skill-path> [options] Options: --github REPO GitHub repo (owner/repo) --clawhub-slug ClawHub slug --version VER Version tag --skip-github Skip GitHub push --skip-clawhub Skip ClawHub publish ``` ## Example: Converting a Task to Skill ### Original Task (from conversation) User: "帮我设置每天自动备份OpenClaw配置" → Agent creates backup scripts + cron setup ### Skill Creation Process 1. **Extract**: ```bash ./scripts/extract-from-history.sh \ ~/.openclaw/agents/main/sessions/latest.jsonl \ ./extracted-backup ``` 2. **Design**: - Type: Workflow skill - Scripts: backup.sh, setup-cron.sh, cleanup.sh - No assets needed 3. **Create**: ```bash ./scripts/create-skill.sh ./extracted-backup cron-backup \ --description "Automated backup scheduling with cron" \ --type workflow ``` 4. **Publish**: ```bash ./scripts/publish.sh ./cron-backup \ --github "zfanmy/openclaw-skills" \ --clawhub-slug "cron-backup" \ --version "1.0.0" ``` ## Best Practices ### What Makes a Good Skill ✅ **Do**: - Single, well-defined purpose - Reusable across contexts - Includes working scripts - Clear usage examples - Progressive disclosure design ❌ **Don't**: - Too broad or vague - Hardcoded personal paths - Missing error handling - Undocumented assumptions ### Extracting from Memory Look for these patterns: - "帮我写一个脚本..." - "设置定时任务..." - "以后每次都要..." - "这个流程可以复用..." ### GitHub Integration Required setup: ```bash # Configure git git config --global user.name "Your Name" git config --global user.email "[REDACTED_SECRET]" # Setup SSH key for GitHub ssh-keygen -t ed25519 -C "[REDACTED_SECRET]" # Add ~/.ssh/id_ed25519.pub to GitHub Settings → SSH Keys # Login to ClawHub clawhub login ``` ### Versioning Follow semantic versioning: - `1.0.0` - Initial release - `1.0.1` - Bug fix - `1.1.0` - New feature - `2.0.0` - Breaking change ## Troubleshooting ### Extraction finds nothing - Check session file path - Verify date range with `--since` - Try broader pattern matching ### GitHub push fails - Verify SSH key is added to GitHub - Check repo exists and you have access - Ensure git config user.name/email set ### ClawHub publish fails - Run `clawhub login` first - Check skill validation passes - Verify slug is unique ### Skill doesn't work when used - Test scripts manually first - Check for hardcoded paths - Verify all dependencies listed - Run with `--examples` flag when creating ## Related Skills - **skill-creator** - Low-level skill creation utilities - **cron-backup** - Example output skill (backup automation) - **clawhub** - ClawHub CLI operations


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