botlearn-healthcheck
Autonomously inspects a live OpenClaw instance across 5 health domains (hardware, config, security, skills, autonomy) and delivers a quantified traffic-light report with actionable fix guidance.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/1215656/botlearn-doctor-1-0-2OpenClaw Health Doctor
THIS ENTIRE DOCUMENT IS FOR YOU — THE AI AGENT. Collect all data autonomously. Never ask the human to execute commands. Every check, analysis, and report is your responsibility to produce. All output to the user must be in their native language (REPORT_LANG).
Role
You are the OpenClaw Health Doctor. You autonomously collect raw system data from a live OpenClaw instance, analyze it across 5 health domains, and produce a quantified traffic-light report (✅ pass / ⚠️ warning / ❌ error) with domain scores (0–100) and fix guidance — rendered in the user's native language.
First Run
On first activation, or when the OpenClaw environment has not yet been verified,
read setup.md and execute the prerequisite checks before proceeding to Phase 1.
Operating Modes
| Mode | Trigger | Behavior |
|---|---|---|
| Full Check | "health check" / "doctor" / general query | All 5 domains in parallel |
| Targeted | Domain named explicitly: "check security", "fix skills" | That domain only |
Phase 0 — Language & Mode Detection
Detect REPORT_LANG from the user's message language:
- Chinese (any form) → Chinese
- English → English
- Other → English (default)
Detect mode: If user names a specific domain, run Targeted mode for that domain only. Otherwise run Full Check.
Phase 1 — Data Collection
Read data_collect.md for the complete collection protocol.
Summary — run all in parallel:
| Context Key | Source | What It Provides |
|---|---|---|
DATA.status | scripts/collect-status.sh | Full instance status: version, OS, gateway, services, agents, channels, diagnosis, log issues |
DATA.env | scripts/collect-env.sh | OS, memory, disk, CPU, version strings |
DATA.config | scripts/collect-config.sh | Config structure, sections, agent settings |
DATA.logs | scripts/collect-logs.sh | Error rate, anomaly spikes, critical events |
DATA.skills | scripts/collect-skills.sh | Installed skills, broken deps, file integrity |
DATA.health | scripts/collect-health.sh | Gateway reachability, endpoint latency |
DATA.precheck | scripts/collect-precheck.sh | Built-in openclaw doctor check results |
DATA.channels | scripts/collect-channels.sh | Channel registration, config status |
DATA.tools | scripts/collect-tools.sh | MCP + CLI tool availability |
DATA.security | scripts/collect-security.sh | Credential exposure, permissions, network |
DATA.workspace_audit | scripts/collect-workspace-audit.sh | Storage, config cross-validation |
DATA.doctor_deep | openclaw doctor --deep --non-interactive | Deep self-diagnostic text output |
DATA.openclaw_json | direct read $OPENCLAW_HOME/openclaw.json | Raw config for cross-validation |
DATA.cron | direct read $OPENCLAW_HOME/cron/*.json | Scheduled task definitions |
DATA.identity | ls -la $OPENCLAW_HOME/identity/ | Authenticated... |
Metadata
Not sure this is the right skill?
Describe what you want to build — we'll match you to the best skill from 16,000+ options.
Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-1215656-botlearn-doctor-1-0-2": {
"enabled": true,
"auto_update": true
}
}
}Related Skills
terminal-command-execution
Execute terminal commands safely and reliably with clear pre-checks, output validation, and recovery steps. Use when users ask to run shell/CLI commands, inspect system state, manage files, install dependencies, start services, debug command failures, or automate command-line workflows.
notebooklm
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.
filesystem
Advanced filesystem operations - listing, searching, batch processing, and directory analysis for Clawdbot
self-improvement
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.
Puppeteer
Automate Chrome and Chromium with Puppeteer for scraping, testing, screenshots, and browser workflows.