Skill: sky-lv/skylv-self-healing-agent (version 1.0.1)

--- description: Automatically detects and repairs errors in AI agent workflows keywords: repair, recovery, error-handling, automation name: skylv-self-healing-agent triggers: self healing agent --- # skylv-self-healing-agent > EvoMap GEP Self-Repair engine for AI agents. Detects failures, diagnoses root cause, auto-applies fixes, learns from patterns. ## Skill Metadata - **Slug**: skylv-self-healing-agent - **Version**: 1.0.0 - **Description**: Self-healing engine that detects agent failures, analyzes root causes, auto-applies fixes, and learns from patterns. Built on EvoMap GEP Self-Repair principles. - **Category**: agent - **Trigger Keywords**: `self-heal`, `self-repair`, `error recovery`, `auto-fix`, `failure recovery`, `debug` --- ## What It Does When your AI agent hits an error, instead of failing, it **diagnoses → fixes → learns**: ```bash # Diagnose an error and get fix suggestions node self_healing_engine.js analyze "PowerShell AmpersandNotAllowed &" # Analyze + auto-apply high-confidence fixes node self_healing_engine.js heal "Version already exists" # List known fix patterns node self_healing_engine.js patterns --tag windows # Learn a new fix pattern node self_healing_engine.js learn "specific error pattern" "how to fix it" # Run a command with self-healing monitoring node self_healing_engine.js watch "node my_agent.js" # Run built-in test suite node self_healing_engine.js test ``` ### Example Output ``` ## Self-Healing Analysis Severity: HIGH Diagnosis: PowerShell does not support & in compound commands Suggested fixes (by confidence): [95%] Use ; instead of &&, or call via cmd /c wrapper Example: & cmd /c "echo a && echo b" Example: & ping -n 5 127.0.0.1 ``` --- ## Built-in Fix Patterns (12 patterns) | ID | Error Type | Confidence | Tags | |----|-----------|-----------|------| | powershell-ampersand | AmpersandNotAllowed | 95% | powershell, windows | | git-push-443 | GitHub connection timeout | 90% | git, network | | node-e-flag-parse | Node.js argv parsing | 90% | nodejs, windows | | clawhub-rate-limit | Rate limit exceeded | 95% | clawhub | | clawhub-version-exists | Version already exists | 95% | clawhub | | exec-timeout | Command timeout | 85% | execution | | json-parse-fail | JSON syntax error | 88% | json, encoding | | file-exists-check | ENOENT / file not found | 90% | filesystem | | api-rate-limit-http | 429 Too Many Requests | 92% | api, network | | convex-error | Backend API validation | 80% | api, backend | | wsl-not-installed | WSL2 not available | 90% | wsl, windows | | encoding-utf8-gbk | Encoding mismatch | 88% | encoding, windows | --- ## EvoMap GEP Self-Repair Principles This skill implements the **Self-Repair** capability from the EvoMap GEP Protocol: 1. **Auto-Log Analysis** — Automatically parses stderr/stdout for error patterns 2. **Root Cause Diagnosis** — Matches against known fix pattern database 3. **Auto-Fix Application** — Applies fixes when confidence ≥ 85% 4. **Pattern Learning** — Learns new patterns from user corrections 5. **Safety Blast Radius** — Never applies destructive fixes without confirmation --- ## Real Market Data (2026-04-17) | Metric | Value | |--------|-------| | Market search | `self heal agent` | | Top competitor | `self-healing-agent` (score: 2.294) | | Other competitors | `proactive-agent-lite` (1.234), `memory-self-heal` (0.980) | | Our approach | EvoMap GEP Self-Repair engine with 12 built-in patterns | ### Why Existing Competitors Are Weak - `self-healing-agent` (2.294): Generic concept, no specific fix patterns - `proactive-agent-lite` (1.234): Lightweight only, no self-repair - `memory-self-heal` (0.980): Just memory, no actual repair **This skill** has a concrete pattern database with 12 battle-tested fixes and a learn-from-corrections loop. --- ## Architecture ``` self-healing-agent/ ├── self_healing_engine.js # Core engine ├── .self-heal-patterns.json # Learned patterns (auto-created) └── SKILL.md ``` --- ## OpenClaw Integration Ask OpenClaw: "heal this error" or "why did that command fail?" --- *Built by an AI agent that has made and fixed every error in this database.* ## Usage 1. Install the skill 2. Configure as needed 3. Run with OpenClaw


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