Fitness Analyzer
huifer/WellAlly-health
分析运动数据、识别运动模式、评估健身进展，并提供个性化训练建议。支持与慢性病数据的关联分析. An agent skill from huifer/WellAlly-health.
Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings.
Install Doctorg
$ npx skills add glebis/claude-skills --skill doctorg -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install glebis/claude-skills doctorg --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/doctorg .claude/skills/doctorg && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "doctorg" agent skill from https://github.com/glebis/claude-skills/tree/main/doctorg into .claude/skills/doctorg/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doctorg", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/glebis/claude-skills/tree/main/doctorgType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add glebis/claude-skills --skill doctorg -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install glebis/claude-skills doctorg --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/doctorg .agents/skills/doctorg && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "doctorg" agent skill from https://github.com/glebis/claude-skills/tree/main/doctorg into .agents/skills/doctorg/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doctorg", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add glebis/claude-skills --skill doctorg -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install glebis/claude-skills doctorg --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/doctorg .cursor/skills/doctorg && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "doctorg" agent skill from https://github.com/glebis/claude-skills/tree/main/doctorg into .cursor/skills/doctorg/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doctorg", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/glebis/claude-skills.git --path doctorg--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add glebis/claude-skills --skill doctorg -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install glebis/claude-skills doctorg --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/doctorg .gemini/skills/doctorg && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "doctorg" agent skill from https://github.com/glebis/claude-skills/tree/main/doctorg into .gemini/skills/doctorg/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doctorg", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install glebis/claude-skills doctorgInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add glebis/claude-skills --skill doctorg -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/doctorg .github/skills/doctorg && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "doctorg" agent skill from https://github.com/glebis/claude-skills/tree/main/doctorg into .github/skills/doctorg/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doctorg", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add glebis/claude-skills --skill doctorg -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install glebis/claude-skills doctorg --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/doctorg .opencode/skills/doctorg && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "doctorg" agent skill from https://github.com/glebis/claude-skills/tree/main/doctorg into .opencode/skills/doctorg/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doctorg", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
doctorg- GitHub stars
- 389
- Token cost
- ~1.6k tokens
- SKILL.md length
- 439 words
- Files
- 4 (incl. references)
- Skills in repo
- 91
- Repo updated
- First seen
- Licence
- MIT
At a glance
Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings.
- Works in 6 steps: Parse Query & Detect Topic Category → Search Evidence Sources (Tiered) → Pull Personal Health Context (unless… → …
- User asks health
- SKILL.md covers Usage, Depth Levels, How It Works and Examples, plus 1 more section
- Calls python
What it does
Doctorg is an agent skill from glebis/claude-skills. 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.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `.claude-plugin/plugin.json`, `instructions.md` and `references/sources.md`).
It sits in Productivity & Automation, covering Health and fitness tracking. The repository describes itself as: Collection of Claude Code skills for enhanced AI workflows. The licence is MIT.
When your agent uses it
- User asks health
- Wellness questions
Example prompts
- “/doctorg”
Requirements
- Python 3
Workflow steps
6 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 7524dff. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Doctorg loads about 1.6k tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 60 tokens; SKILL.md has 439 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from glebis/claude-skills at commit 7524dff, republished under its MIT licence (© glebis). 439 words, ~1,641 tokens.
Download SKILL.mdSave it as
.claude/skills/doctorg/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- doctorg
- description
- 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.
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 painDepth 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 30Select 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
Show full SKILL.md (193 more words)Show less
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 trainingFull (controversial topic)
/doctorg --full Safety profile of long-term melatonin supplementationIntegration 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
© glebis, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (references) in doctorg of glebis/claude-skills.
- SKILL.md
- .claude-plugin/plugin.json
- instructions.md
- references/sources.md
Open the folder on GitHubat commit 7524dff
Compare with similar skills
Doctorg next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Doctorg this skillglebis/claude-skills | 389 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Fitness Analyzerhuifer/WellAlly-health | 961 | 6 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Coachfelixrieseberg/claude-coach | 196 | 1 repos | ~4.9k | Automated safety check: Pass | MIT | |
| GhealthGoogle-Health-API/google-health-cli | 266 | 1 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Master Ajahn Chahxr843/Master-skill | 447 | 1 repos | ~2k | Automated safety check: Pass | CC-BY-NC-SA-4.0 | |
| Mental Health Analyzerhuifer/WellAlly-health | 961 | 6 repos | ~3.2k | Automated safety check: Pass | MIT |
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Mental Health Analyzer
huifer/WellAlly-health
分析心理健康数据、识别心理模式、评估心理健康状况、提供个性化心理健康建议。支持与睡眠、运动、营养等其他健康数据的关联分析。
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分析营养数据、识别营养模式、评估营养状况，并提供个性化营养建议。支持与运动、睡眠、慢性病数据的关联分析. An agent skill from huifer/WellAlly-health.
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Related
Categories
Questions about Doctorg
What does Doctorg do?
Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings. Doctorg is an agent skill from glebis/claude-skills. Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings.
When should I use Doctorg?
Doctorg fits situations like: user asks health; wellness questions.
How do I install Doctorg in Claude Code?
Run `npx skills add glebis/claude-skills --skill doctorg -a claude-code`. Or copy the skill folder (doctorg in glebis/claude-skills) into .claude/skills/doctorg in your project. Claude Code loads it when a task matches its description.
How do I install Doctorg in Codex?
Run `npx skills add glebis/claude-skills --skill doctorg -a codex`. Or copy the skill folder (doctorg in glebis/claude-skills) into .agents/skills/doctorg in your project. Codex loads it when a task matches its description.
Can I use Doctorg in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add glebis/claude-skills --skill doctorg -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/doctorg, .gemini/skills/doctorg, .github/skills/doctorg and .opencode/skills/doctorg in your project.
What does Doctorg need to run?
Going by SKILL.md and its folder, Doctorg needs the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Doctorg access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Doctorg safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Doctorg use?
Doctorg is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Doctorg use?
About 1.6k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.7k tokens, read only when the agent opens those files.
What are the alternatives to Doctorg?
Skills that share tags, products or a category with Doctorg: Fitness Analyzer (huifer/WellAlly-health, 961 stars), Coach (felixrieseberg/claude-coach, 196 stars), Ghealth (Google-Health-API/google-health-cli, 266 stars) and Master Ajahn Chah (xr843/Master-skill, 447 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Doctorg?
glebis (a GitHub user) maintains it in glebis/claude-skills, which has 389 GitHub stars. The repository holds 91 skills in this directory. The repository was last updated on September 26, 2026.
Source: glebis/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.