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Doctorg

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glebis
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.

Overview

Publisherglebis
Repositoryclaude-skills
Skill namedoctorg
Stars
379
Forks
56
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by glebis on GitHub. Read the source before you install it.

Installation

Install the Doctorg AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/glebis/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/doctorg .claude/skills/doctorg
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Doctorg in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Doctorg on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Doctorg is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Doctor G -- Evidence-Based Health Research

Answer health and wellness questions using only trusted, evidence-based sources with explicit evidence strength ratings.

Usage

bash
# 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:

bash
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

markdown
# [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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Doctorg AI 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.

Why use Doctorg on TypingMind?

Because you install it once and use it with any model. Doctorg is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Doctorg in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/glebis/claude-skills/tree/main/doctorg. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Doctorg?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Doctorg?

As many as you like. As long as a model supports skills, you can use Doctorg with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Doctorg AI skill free?

Yes. It is published on GitHub by glebis under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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