skills/botlearn-ai/botlearn-skills/botlearn-healthcheck

botlearn-healthcheck

SKILL.md

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
DATA.skills scripts/collect-skills.sh Installed skills, broken deps, file integrity
DATA.health openclaw health --json Gateway reachability, endpoint latency, service status
DATA.precheck scripts/collect-precheck.sh Built-in openclaw doctor check results
DATA.channels scripts/collect-channels.sh Channel registration, config status
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 device listing (no content)
DATA.gateway_err_log tail -200 $OPENCLAW_HOME/logs/gateway.err.log Recent gateway errors (redacted)
DATA.memory_stats find/du on $OPENCLAW_HOME/memory/ File count, total size, type breakdown
DATA.heartbeat direct read $OPENCLAW_HOME/workspace/HEARTBEAT.md Last heartbeat timestamp + content
DATA.models direct read $OPENCLAW_HOME/agent/models.json Model contextWindow, maxTokens per model
DATA.cache openclaw cache stats Cache size, history count, index size
DATA.workspace_identity direct read $OPENCLAW_HOME/workspace/{agent,soul,user,identity,tool}.md Presence + word count + content depth of 5 identity files

On any failure: set DATA.<key> = null, continue — never abort collection.


Phase 2 — Domain Analysis

For Full Check: run all 5 domains in parallel. For Targeted: run only the named domain.

Each domain independently produces: status (✅/⚠️/❌) + score (0–100) + findings + fix hints. Read the corresponding check_*.md file for complete scoring tables, edge cases, and output format. Read openclaw_knowledge.md for platform defaults (gateway address, latest version, CLI commands).

# Domain Data Sources Key Checks Pass/Warn/Fail Reference
1 Hardware Resources DATA.env Memory, Disk, CPU, Node.js, OS ≥80 / 60–79 / <60 check_hardware.md
2 Configuration Health DATA.config, DATA.health, DATA.channels, DATA.tools, DATA.openclaw_json, DATA.status CLI validation, config structure, gateway, agents, channels, tools, consistency, security posture ≥75 / 55–74 / <55 check_config.md
3 Security Risks DATA.security, DATA.gateway_err_log, DATA.identity, DATA.config Credential exposure, file permissions, network bind, CVEs, VCS secrets ≥85 / 65–84 / <65 check_security.md
4 Skills Completeness DATA.skills Built-in tools, install capability, count & coverage, skill health, botlearn ecosystem ≥80 / 60–79 / <60 check_skills.md
5 Autonomous Intelligence DATA.precheck, DATA.heartbeat, DATA.cron, DATA.memory_stats, DATA.workspace_audit, DATA.doctor_deep, DATA.logs, DATA.status, DATA.workspace_identity Heartbeat, cron, memory, doctor, services, agents, logs, workspace identity → Autonomy Mode ≥80 / 60–79 / <60 check_autonomy.md

Common rules:

  • Base score = 100, subtract impacts per check failure
  • If data source is null: use fallback score noted in each check_*.md
  • Privacy: NEVER print credential values — report type + file path only
  • Output: domain labels and summaries in REPORT_LANG; metrics, commands, field names in English

Phase 3 — Report Generation

Generate persistent health report documents (MD + HTML) from domain analysis results. Save to $OPENCLAW_HOME/memory/health-reports/healthcheck-YYYY-MM-DD-HHmmss.{md,html}.

Read flow_report.md for: output location, file naming, MD/HTML content templates, generation protocol.


Phase 4 — Report Analysis

Present analysis results to the user with layered output (one-line status → domain grid → issue table → deep analysis). Compare with historical reports for trend tracking.

Read flow_analysis.md for: output layer formats (L0–L3), historical trend comparison, follow-up prompts. Reference fix_cases.md for real-world diagnosis patterns and root cause analysis.


Phase 5 — Fix Cycle

If any issues found, guide user through fix execution with confirmation at every step. Show fix command + rollback command → await confirmation → execute → verify.

Never run any command that modifies system state without explicit user confirmation.

Read flow_fix.md for: safety rules, per-fix protocol, batch mode, scope limits. Reference fix_cases.md for proven fix steps, rollback commands, and prevention strategies.


Phase 6 — Fix Summary

After fix cycle, generate a final summary: actions taken, score changes, remaining issues. Append fix results to the previously generated report files.

Read flow_summary.md for: summary content, post-fix verification, report update, closing message.


Key Constraints

  1. Scripts First — Use scripts/collect-*.sh for structured data; read files directly for raw content.
  2. Evidence-Based — Every finding must cite the specific DATA.<key>.<field> and its actual value.
  3. Privacy Guard — Redact all API keys, tokens, and passwords before any output or storage.
  4. Safety Gate — Show fix plan and await explicit confirmation before any system modification.
  5. Language Rule — Instructions in this file are in English. All output to the user must be in REPORT_LANG.
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