doctorg
Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings. Integrates Apple Health data for personalized context. Use when user asks health, nutrition, exercise, sleep, or wellness questions.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/glebis/claude-skills --skill doctorg- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads doctorg automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Doctor G -- Evidence-Based Health Research
Answer health and wellness questions using only trusted, evidence-based sources with explicit evidence strength ratings.
Usage
# Quick answer (WebSearch only, ~30s)
/doctorg Is creatine safe for daily use?
# Deep research (WebSearch + Tavily, ~90s)
/doctorg --deep Huberman vs Attia on fasted training
# Full investigation (WebSearch + Tavily + Firecrawl, ~3min)
/doctorg --full What does current evidence say about GLP-1 agonists for non-diabetic weight loss?
# Without personal health context
/doctorg --no-personal Best stretching protocol for lower back pain
Depth Levels
| Level | Flag | Tools | Time | Use When |
|---|---|---|---|---|
| Quick | (default) | WebSearch | ~30s | Simple factual questions |
| Deep | --deep | WebSearch + Tavily | ~90s | Competing claims, nuanced topics |
| Full | --full | WebSearch + Tavily + Firecrawl | ~3min | Controversial topics, need primary sources |
How It Works
1. Parse Query & Detect Topic Category
Classify the question into one of:
- Nutrition/Supplements (examine.com gets priority)
- Exercise/Training (PubMed + ACSM get priority)
- Sleep (focus sleep-specific databases)
- Disease/Condition (condition-specific orgs + clinical guidelines)
- Medication/Treatment (FDA, EMA, Cochrane get priority)
- Mental Health (APA, mental health orgs)
- General Wellness (broad search across all tiers)
2. Search Evidence Sources (Tiered)
Search sources in priority order. See references/sources.md for complete domain list.
Tier 1 -- Primary Research (highest weight):
- PubMed/PMC, Cochrane Library, WHO, ClinicalTrials.gov
Tier 2 -- Clinical/Institutional (high weight):
- Mayo Clinic, Hopkins Medicine, Cleveland Clinic, Harvard Health
- Condition-specific: AHA, ACS, ADA, Alzheimer's Association
Tier 3 -- Expert Analysis (medium weight):
- Examine.com, STAT News, Health News Review
- Consensus.app, Epistemonikos
Tier 4 -- Quality Journalism (context/framing):
- The Atlantic, NYT, NPR, Guardian, FiveThirtyEight
Search Strategy by Depth
Quick (default):
WebSearch(query, allowed_domains=[Tier 1 + Tier 2 domains])
WebSearch(query + "systematic review OR meta-analysis", allowed_domains=[Tier 1])
Deep (--deep): All Quick searches PLUS:
tavily-search(query, include_domains=[Tier 1-3])
WebSearch(query + "expert opinion OR position statement", allowed_domains=[Tier 2-3])
WebSearch(query + "risks OR side effects OR contraindications")
Full (--full): All Deep searches PLUS:
firecrawl-research for top 2-3 most relevant results from Tier 1
WebSearch for competing/contrarian viewpoints
WebSearch(query + "retracted OR debunked OR misleading")
3. Pull Personal Health Context (unless --no-personal)
Query Apple Health database for relevant metrics:
python ~/ai_projects/claude-skills/health-data/scripts/health_query.py --format json vitals
python ~/ai_projects/claude-skills/health-data/scripts/health_query.py --format json daily
python ~/ai_projects/claude-skills/health-data/scripts/health_query.py --format json sleep --days 7
python ~/ai_projects/claude-skills/health-data/scripts/health_query.py --format json workouts --days 30
Select ONLY metrics relevant to the query:
- Exercise question -> recent workouts, activity, resting HR, VO2 max
- Sleep question -> sleep data, HRV
- Nutrition question -> weight trends, activity level
- Heart question -> HR, HRV, resting HR, blood pressure
4. Synthesize with Evidence Grading
Rate each claim using simplified GRADE scale:
| Rating | Meaning | Based On |
|---|---|---|
| Strong | Consistent evidence from systematic reviews/meta-analyses or multiple large RCTs | Level I-II evidence |
| Moderate | Supported by well-designed studies but some inconsistency or limitations | Level II-III evidence |
| Weak | Limited evidence, small studies, or conflicting results | Level III-IV evidence |
| Minimal | Expert opinion, case reports, or preliminary/animal studies only | Level V evidence |
| Contested | Active scientific debate with credible evidence on both sides | Mixed levels |
5. Format Output
# [Topic Title]
**Short answer**: [1-2 sentence direct answer]
## [Expert/Position A] (if comparing viewpoints)
- Key claim 1
- Key claim 2
- Has **evolved stance**: [if applicable]
## [Expert/Position B]
- Key claim 1
- Key claim 2
## Where They Actually Agree (if comparing)
- Agreement point 1
- Agreement point 2
## What Research Shows
| Claim | Evidence Strength |
|-------|------------------|
| Claim 1 | **Strong** |
| Claim 2 | **Weak** (reason) |
| Claim 3 | **Contested** |
## For You Specifically (if --personal context available)
[Personalized interpretation based on user's health data]
[Specific actionable recommendation]
## Sources
- [Source 1 title](url) -- Tier, year
- [Source 2 title](url) -- Tier, year
## Limitations
- [Any caveats about the evidence or this analysis]
Output rules:
- NEVER give medical diagnoses or replace professional advice
- ALWAYS include disclaimer: "This is research synthesis, not medical advice"
- When evidence is Weak or Minimal, explicitly say so
- When claims are Contested, present both sides fairly
- Prefer recent sources (last 5 years) over older ones
- Flag if key studies have been retracted or challenged
- Include the "For You Specifically" section only when health data adds meaningful context
6. Disclaimer (always append)
---
*Research synthesis, not medical advice. Consult a healthcare provider for personal decisions.*
Examples
Quick
/doctorg Is 10000 steps a day backed by science?
Deep (comparing experts)
/doctorg --deep Huberman vs Attia on fasted training
Full (controversial topic)
/doctorg --full Safety profile of long-term melatonin supplementation
Integration with Other Skills
- health-data: Pulls Apple Health metrics for personalization
- tavily-search: Deep research at Tier 1-3 sources
- firecrawl-research: Full-text extraction from primary sources
- fact-checker: Can be chained for verification of specific claims
FAQ
What does the doctorg skill do?
Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings. Integrates Apple Health data for personalized context. Use when user asks health, nutrition, exercise, sleep, or wellness questions.
How do I install doctorg?
Run npx skills add https://github.com/glebis/claude-skills --skill doctorg in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/doctorg/ (personal) or .claude/skills/doctorg/ (project).
Which AI agents can use doctorg?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is doctorg safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains doctorg?
It is published by glebis in glebis/claude-skills. It has 258 recorded installs.
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