skills/25-HosungYou-Diverga/skills/doctor/SKILL.md
System diagnostics and health checks for Diverga plugin. OpenClaw-style Check-Report-Fix pattern with 5-layer diagnostics. Triggers: /diverga:doctor, diverga doctor, system check, diagnose, 진단
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research doctorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Version: 11.1.0
Trigger: /diverga:doctor
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.
When user invokes /diverga:doctor, execute all 7 diagnostic layers sequentially and display results.
Check plugin registration:
~/.claude/plugins/installed_plugins.jsondiverga@diverga entry existsCheck config JSON validity:
~/.claude/plugins/diverga/config/diverga-config.jsonversion, human_checkpoints, languageReport 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:
Check skill counts match between plugin and local cache:
~/.claude/plugins/diverga/skills/*/SKILL.md~/.claude/skills/diverga-*/SKILL.md (exclude diverga-diverga prefix duplication — count unique skill names)Check for missing skills in local cache:
diverga-{name} exists in local skillsReport format:
SKILL SYNC
Plugin skills: [count] skills in plugin directory
Local skills: [count] skills in local cache
Sync status: [PASS - all synced | WARN - X skills missing locally]
Missing: [list of missing skill names, if any]
Fix if WARN:
Check that the plugin cache matches the installed version:
~/.claude/plugins/diverga/plugin.json → extract version~/.claude/plugins/cache/diverga/diverga/*/plugin.json → list cached versionshooks/hooks.jsonReport format:
PLUGIN CACHE
Installed version: [11.1.0 | FAIL - plugin.json missing]
Cached version: [11.1.0 | WARN - stale cache: 8.0.1 | FAIL - no cache found]
Cache has hooks: [PASS - hooks.json present | FAIL - hooks missing from cache]
Cache has agents: [PASS - agents/ present | WARN - agents/ missing]
Fix if WARN/FAIL:
REPO="/Volumes/External SSD/Projects/Diverga/Diverga-core"
CACHE="$HOME/.claude/plugins/cache/diverga/diverga/11.1.0"
rm -rf "$HOME/.claude/plugins/cache/diverga/diverga/8.0.1"
mkdir -p "$CACHE"
cp -R "$REPO"/{skills,agents,config,hooks,mcp,CLAUDE.md,AGENTS.md,README.md} "$CACHE/"
cp "$REPO/.claude-plugin/plugin.json" "$CACHE/"
Check hook configuration:
~/.claude/plugins/diverga/hooks/hooks.json → verify it exists and has PreToolUse entries~/.claude/settings.json → check if hooks are also configured at global levelecho '{"tool_name":"Skill","tool_input":{"skill":"diverga:c1"}}' | node ~/.claude/plugins/diverga/hooks/prereq-enforcer.mjs → verify it returns valid JSON with continue fieldReport format:
HOOK ENFORCEMENT
Plugin hooks.json: [PASS - exists with Agent+Skill matchers | FAIL - missing or wrong matchers]
Global hooks: [PASS - configured in settings.json | WARN - not in settings.json (relies on plugin)]
Hook executable: [PASS - returns valid JSON | FAIL - execution error]
Matcher check: [PASS - uses "Agent" | FAIL - uses stale "Task" matcher]
Fix if issues found:
Deep validation of diverga-config.json:
~/.claude/plugins/diverga/config/diverga-config.jsonversion field matches "11.1.0"human_checkpoints object exists and has enabled (boolean) and required (array)language is one of: "en", "ko", "auto"model_routing has high, medium, low keys if presentReport format:
CONFIG VALIDITY
Version field: [PASS - 11.1.0 | WARN - version mismatch: found X.Y.Z]
Checkpoints: [PASS - configured | FAIL - missing or malformed]
Language: [PASS - "en" | WARN - unexpected value: "XX"]
Model routing: [PASS - configured | SKIP - not set (using defaults)]
Fix if issues found:
Check 8 environment variables using Bash tool (echo $VAR_NAME):
| Variable | Purpose | Required? |
|----------|---------|-----------|
| GROQ_API_KEY | LLM screening (recommended) | Recommended |
| ANTHROPIC_API_KEY | Claude API | Recommended |
| OPENAI_API_KEY | OpenAI screening | Optional |
| GEMINI_API_KEY | Gemini visualization | Optional |
| SEMANTIC_SCHOLAR_API_KEY | Paper retrieval | Optional |
| OPENALEX_EMAIL | OpenAlex polite pool | Optional |
| SCOPUS_API_KEY | Scopus access | Optional |
| WOS_API_KEY | Web of Science | Optional |
For each variable, use Bash: echo "${VAR_NAME:+configured}" — if output is "configured", it's set; if empty, it's not set.
Report format:
API STATUS
Groq: [configured | NOT SET -> export GROQ_API_KEY=your_key]
Anthropic: [configured | NOT SET -> export ANTHROPIC_API_KEY=your_key]
OpenAI: [configured | not set (optional)]
Gemini: [configured | not set (optional)]
Semantic Scholar: [configured | not set (optional)]
OpenAlex: [configured | not set (optional)]
Scopus: [configured | not set (optional)]
Web of Science: [configured | not set (optional)]
Fix if NOT SET (recommended keys):
export VAR_NAME=your_key_here for each missing recommended keyCheck for active research project:
.research/project-state.yaml exists in current working directoryproject_name, current_stage).research/ directory exists with expected subdirectoriesReport format:
PROJECT STATE
Active project: [project name | No active project]
State file: [PASS - valid | WARN - invalid YAML | SKIP - no project]
Research dir: [PASS - structure intact | WARN - missing subdirs | SKIP - no project]
Fix if issues:
After all 7 layers, display overall status:
══════════════════════════════════════════════
DIVERGA SYSTEM DIAGNOSTICS v11.1.0
══════════════════════════════════════════════
[Layer 1-7 results as shown above]
------------------------------------------
OVERALL: [HEALTHY | X WARNING(S) | X ERROR(S)]
[If issues found, numbered list:]
1. [Issue description] -> [Fix command]
2. [Issue description] -> [Fix command]
...
[If healthy:]
All systems operational. Diverga is ready to use.
Run /diverga:help to see all 24 agents and commands.
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development
Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.
development
Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.
testing
Performs placebo-in-time sensitivity analysis with hierarchical null model and optional Bayesian assurance. Use when checking model robustness, verifying lack of pre-intervention effects, or estimating study power.
data-ai
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware custom priors.