Overview
- Skill Key
- calvinxhk/botlearn-healthcheck
- Author
- calvinxhk
- Source Repo
- openclaw/skills
- Version
- 0.1.5
- Source Path
- skills/calvinxhk/botlearn-healthcheck
- Latest Commit SHA
- bebe2d43d8ad7dc39380d44f7cb959e1e60e6dc5
botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.
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0
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Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 botlearn-healthcheck 技能。 若已安装,则直接安装 botlearn-healthcheck 技能。
# OpenClaw 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 | | `D...
# @botlearn/botlearn-healthcheck
OpenClaw Autonomous Health Inspector — collects system data across 5 domains, produces traffic-light reports with scores and fix guidance, and walks the user through repairs.
## How It Works
The health check runs a 6-phase pipeline, fully autonomous:
```
Phase 0: Detect language + operating mode (full check or targeted domain)
Phase 1: Data Collection
→ Run 11 collection scripts in parallel
→ Read 10 config/state files directly
→ Store all data as DATA.* context keys
→ Any failure sets DATA.<key> = null, never aborts
Phase 2: Domain Analysis
→ Analyze 5 health domains (all in parallel for full check)
→ Each domain: base score 100, subtract per-check failures
→ Produce: status + score (0-100) + findings + fix hints
Phase 3: Report Generation
→ Save MD + HTML reports to $OPENCLAW_HOME/memory/health-reports/
Phase 4: Report Analysis
→ Present layered output: one-line status → domain grid → issues → deep analysis
→ Compare with historical reports for trend tracking
Phase 5: Fix Cycle
→ Show fix command + rollback → await user confirmation → execute → verify
→ Never modify system state without explicit confirmation
Phase 6: Fix Summary
→ Actions taken, score changes, remaining issues
```
## 5 Health Domains
| # | Domain | Score Thresholds | What It Checks |
|---|--------|-----------------|---------------|
| 1 | Hardware Resources | ≥80 / 60-79 / <60 | Memory, disk, CPU, Node.js version, cache pressure |
| 2 | Configuration Health | ≥75 / 55-74 / <55 | Config validation, gateway, agents, channels, tools, models, session, security posture |
| 3 | Security Risks | ≥85 / 65-84 / <65 | Credential exposure, file permissions, network bind, VCS secrets |
| 4 | Skills Completeness | ≥80 / 60-79 / <60 | Built-in tools, install capability, skill health, botlearn ecosystem |
| 5 | Autonomous Intelligence | ≥80 / 60-79 / <60 | Heartbeat, cron tasks, memory, doctor output, workspace identi...
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