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Independent project, not affiliated with Anthropic
glebis avatar

Doctorg

glebis/claude-skills
243 installs345 stars
Summary

This is a health research assistant that searches tiered medical sources and grades evidence strength using a GRADE-inspired scale. It has three depth modes: quick uses WebSearch for basic questions, deep adds Tavily for nuanced topics, and full includes Firecrawl for controversial subjects requiring primary sources. It prioritizes PubMed and Cochrane over Mayo Clinic over quality journalism, and pulls your Apple Health data to personalize answers unless you flag it not to. The evidence grading is the useful part here: claims get rated Strong, Moderate, Weak, Minimal, or Contested so you know when you're looking at meta-analyses versus expert opinion. Always disclaims it's not medical advice, which is the only responsible way to build something like this.

Install to Claude Code

npx -y skills add glebis/claude-skills --skill doctorg --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.mdView on GitHub

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

LevelFlagToolsTimeUse When
Quick(default)WebSearch~30sSimple factual questions
Deep--deepWebSearch + Tavily~90sCompeting claims, nuanced topics
Full--fullWebSearch + Tavily + Firecrawl~3minControversial 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:

RatingMeaningBased On
StrongConsistent evidence from systematic reviews/meta-analyses or multiple large RCTsLevel I-II evidence
ModerateSupported by well-designed studies but some inconsistency or limitationsLevel II-III evidence
WeakLimited evidence, small studies, or conflicting resultsLevel III-IV evidence
MinimalExpert opinion, case reports, or preliminary/animal studies onlyLevel V evidence
ContestedActive scientific debate with credible evidence on both sidesMixed 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
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Categories
Data Science & ML
First SeenJun 3, 2026
View on GitHub

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