Skylv Self Healing Agent
v1.0.1Automatically detects and repairs errors in AI agent workflows
Security Scan
Capability signals
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
OpenClaw
Suspicious
medium confidencePurpose & Capability
The name/description (self-healing agent) aligns with the included code: it parses errors, matches patterns, suggests fixes, and stores learned patterns. However the package omits declaring that Node.js is required even though both README and SKILL.md show usage as 'node self_healing_engine.js' and the code imports Node built-ins. That mismatch (no required binary declared) is an actionable inconsistency.
Instruction Scope
SKILL.md instructs running commands like 'watch "node my_agent.js"' and 'heal ...', and the code imports child_process.exec/execSync. The engine is intended to 'auto-apply fixes' when confidence >= 85%; the visible autoFix() returns a fix string but the file is truncated so it is unclear whether fixes are actually executed or just suggested. Because the code can run commands (watching a command, child_process present) this grants the skill the ability to execute arbitrary shell commands — coherent with the stated purpose but risky and underspecified (no explicit confirmation flow shown in the visible code). The skill also writes .self-heal-patterns.json to the working directory.
Install Mechanism
There is no remote install/download step (instruction-only + included JS file). That minimizes supply-chain risk of fetching arbitrary code. The code will run locally when invoked, and it will create a patterns file in the working directory; that's expected behavior for this type of tool.
Credentials
The skill declares no required environment variables or credentials and the visible code does not access external secrets. It writes a local .self-heal-patterns.json file (persistent data) but does not declare or request unrelated credentials. No network calls are visible in the provided snippet.
Persistence & Privilege
The skill does not request 'always: true' and is user-invocable. It persists learned patterns locally (.self-heal-patterns.json) which is within scope. However autonomous invocation combined with the skill's ability to run commands (if configured to run without interactive confirmation) increases blast radius — the SKILL.md's claim 'Never applies destructive fixes without confirmation' is not verifiable from the truncated code.
What to consider before installing
This skill appears to implement what it claims (error pattern matching, suggestions, learning), but it has a few things you should check before installing or running it on production systems:
- Node.js requirement: The README and SKILL.md use 'node ...' but the skill metadata does not declare Node as a required binary. Ensure a compatible Node.js runtime (Node 14+) is present.
- Confirm whether 'heal' or 'watch' actually execute shell commands: the code imports child_process (exec/execSync). Ask the author or inspect the remaining code to verify whether auto-applied fixes are only printed as suggestions or are executed automatically, and whether user confirmation is required before executing any change.
- Run in a sandbox first: because the tool can run monitored commands and may execute fixes, test it in an isolated, non-production environment and with non-privileged accounts.
- Review persisted files: it creates .self-heal-patterns.json in the working directory; ensure this file's location and contents are acceptable for your environment.
- Ask the maintainer/developer: (1) does heal execute commands or mutate system state? (2) what confirmation UI exists for auto-fixes? (3) will it make any network calls or require credentials in future versions? (4) where are learned patterns stored when run by an automated agent (path and permissions)?
If you cannot get clear answers or inspect the full code that performs fixes, treat this skill as untrusted and do not run it with high privileges or against production workloads.self_healing_engine.js:292
Shell command execution detected (child_process).
Patterns worth reviewing
These patterns may indicate risky behavior. Check the VirusTotal and OpenClaw results above for context-aware analysis before installing.Like a lobster shell, security has layers — review code before you run it.
latest
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:
# 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:
- Auto-Log Analysis — Automatically parses stderr/stdout for error patterns
- Root Cause Diagnosis — Matches against known fix pattern database
- Auto-Fix Application — Applies fixes when confidence ≥ 85%
- Pattern Learning — Learns new patterns from user corrections
- 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 patternsproactive-agent-lite(1.234): Lightweight only, no self-repairmemory-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
- Install the skill
- Configure as needed
- Run with OpenClaw
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