agentleFS
glebisglebis/claude-skills/doctorg/SKILL.md

doctorg

Skill400 starsChanged 4 months agoMITView on GitHub

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.

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 7 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Search sources in priority order.

    line 49
  2. Distinctive:

    All Quick searches PLUS:

    line 74
  3. Distinctive:

    All Deep searches PLUS:

    line 82
  4. Distinctive:

    NEVER give medical diagnoses or replace professional advice

    line 161
  5. Distinctive:

    ALWAYS include disclaimer: "This is research synthesis, not medical advice"

    line 162
  6. Distinctive:

    When evidence is Weak or Minimal, explicitly say so

    line 163
  7. Distinctive:

    When claims are Contested, present both sides fairly

    line 164
  8. Distinctive:

    Prefer recent sources (last 5 years) over older ones

    line 165

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.