doctor
System diagnostics and health checks for Diverga plugin. OpenClaw-style Check-Report-Fix pattern with 5-layer diagnostics.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill doctor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Diverga Doctor **Version**: 11.1.0 **Trigger**: `/diverga:doctor` ## Description System diagnostics for the Diverga plugin. Checks plugin health, skill sync, hook enforcement, configuration validity, API keys, and project state. Reports issues with actionable fix commands. Follows OpenClaw Check-Report-Fix pattern: every detected issue includes a fix recommendation. ## Instructions When user invokes `/diverga:doctor`, execute all 7 diagnostic layers sequentially and display results. ### Layer 1: Plugin Health **Check plugin registration:** - Read `~/.claude/plugins/installed_plugins.json` - Verify `diverga@diverga` entry exists - Extract version and install date **Check config JSON validity:** - Read `~/.claude/plugins/diverga/config/diverga-config.json` - Verify it parses as valid JSON - Check required fields exist: `version`, `human_checkpoints`, `language` **Report format:** ``` PLUGIN HEALTH Registration: [PASS - diverga@diverga v11.1.0 | FAIL - not found in installed_plugins.json] Config file: [PASS - valid JSON | FAIL - missing or invalid] Config fields: [PASS - all required fields present | WARN - missing: field1, field2] ``` **Fix if FAIL:** - Registration missing: "Run:
- Description
- Instructions
- Layer 1: Plugin Health
- Layer 2: Skill Sync
- Layer 3: Plugin Cache Sync
- Layer 4: Hook Enforcement
- Layer 5: Config Validity
- Layer 6: API Keys
- Layer 7: Project State
- Final Summary
- Implementation Notes
What does the doctor skill do?
System diagnostics and health checks for Diverga plugin. OpenClaw-style Check-Report-Fix pattern with 5-layer diagnostics.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill doctor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.