by h1papc11
ai agent healthcare vault for family that combines Obsidian templates, AI prompt workflows, and a TypeScript preprocessing pipeline for Apple Health exports
# Add to your Claude Code skills
git clone https://github.com/h1papc11/healthcare-ai-agent-vaultGuides for using ai agents skills like healthcare-ai-agent-vault.
healthcare-ai-agent-vault is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by h1papc11. ai agent healthcare vault for family that combines Obsidian templates, AI prompt workflows, and a TypeScript preprocessing pipeline for Apple Health exports. It has 60 GitHub stars.
healthcare-ai-agent-vault's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/h1papc11/healthcare-ai-agent-vault" and add it to your Claude Code skills directory (see the Installation section above).
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A local-first family health archive that combines Obsidian templates, AI prompt workflows, and a TypeScript preprocessing pipeline for Apple Health exports.
Your health data stays on your machine. AI assists with structuring and analysis — you control what leaves your device.
AI Health Vault is designed for families who want structured health records without surrendering privacy to commercial apps. Clone the repository, open the Obsidian vault, and use included prompts or Claude Code skills to transform photos, PDFs, and wearable exports into organized Markdown and CSV files.
Version 2 adds a production TypeScript runtime with strict typing, optional Redis-backed export job caching, structured logging, and a full build/lint/test pipeline.
| Capability | Description |
|---|---|
| Obsidian vault templates | Hub pages, member archives, tracking CSVs, and field standards |
| Eight AI workflows | Checkup extraction, medication recognition, trend analysis, visit prep, Apple Watch analysis, family-friendly summaries, follow-up calendar, daily health plan |
| Claude Code skills | Auto-loaded skill definitions mirroring the prompt library |
| Apple Health preprocessor | Streaming XML/ZIP parser that splits large exports into typed CSV files |
| Optional Redis cache | Persists export job metadata for repeated preprocessing runs |
| Strict TypeScript | Typed services, validated configuration, and comprehensive unit tests |
flowchart TB
subgraph Inputs
A[Photos / PDFs]
B[Apple Health Export]
C[Manual Notes]
end
subgraph Processing
D[AI Prompts & Skills]
E[Apple Health CLI]
F[(Redis Cache)]
end
subgraph Storage
G[Obsidian Vault]
H[CSV Tracking Files]
end
A --> D
B --> E
C --> G
D --> G
E --> H
E -. optional .-> F
G --> H
flowchart LR
subgraph Application
CLI[CLI Entry Point]
SVC[Apple Health Service]
CFG[Config Module]
LOG[Structured Logger]
end
subgraph Persistence
REDIS[Connection Manager]
CACHE[Export Job Cache]
end
CLI --> CFG
CLI --> SVC
CLI --> REDIS
SVC --> LOG
REDIS --> CACHE
SVC --> CACHE
flowchart TD
A[Clone repository] --> B[Open vault/ in Obsidian]
B --> C[Add family members to hub page]
C --> D[Capture health document]
D --> E[Send to AI with prompt or skill]
E --> F[Paste structured output into vault]
F --> G{More records?}
G -->|Yes| D
G -->|No| H[Review trends in tracking CSVs]
sequenceDiagram
participant User
participant CLI as Preprocessor CLI
participant Parser as SAX Parser
participant Redis as Redis Cache
participant Vault as Obsidian Vault
User->>CLI: export.zip + output directory
CLI->>Redis: Check cached job (optional)
alt Cache hit
Redis-->>CLI: Completed job metadata
else Cache miss
CLI->>Parser: Stream XML records
Parser-->>CLI: Typed CSV files
CLI->>Redis: Store job result (optional)
end
User->>Vault: Attach CSV summaries to member archive
ai-health-vault/
├── src/
│ ├── cli/ # Command-line entry points
│ ├── config/ # Environment configuration (Zod-validated)
│ ├── errors/ # Typed application errors
│ ├── logging/ # Structured JSON logger
│ ├── redis/ # Connection manager and export job cache
│ └── services/
│ └── apple-health/ # Streaming preprocessor implementation
├── tests/
│ ├── fixtures/ # Sample Apple Health XML
│ └── unit/ # Vitest unit tests
├── vault/ # Obsidian vault template
├── prompts/ # Portable AI prompt library
├── .claude/skills/ # Claude Code skill definitions
├── guides/ # Setup guides and FAQ
└── docs/internal/ # Engineering audit notes
Design decisions
src/services/ holds domain logic; infrastructure lives in src/redis/, src/config/, and src/logging/.vault/, prompts/, .claude/) remain separate from application code.src/ layout under tests/unit/.git clone https://github.com/runesleo/ai-health-vault.git
cd ai-health-vault
npm install
cp .env.example .env
Build and verify:
npm run validate
Open the vault:
vault/ directory健康管理中心.md with your family member namesCopy .env.example to .env and adjust values:
| Variable | Default | Description |
|---|---|---|
LOG_LEVEL |
info |
Logging verbosity: debug, info, warn, error |
REDIS_ENABLED |
false |
Enable Redis-backed export job caching |
REDIS_URL |
— | Redis connection URL (required when enabled) |
REDIS_KEY_PREFIX |
ai-health-vault: |
Key namespace prefix |
REDIS_MAX_RETRIES |
10 |
Maximum connection retry attempts |
REDIS_CONNECT_TIMEOUT_MS |
10000 |
Connection timeout in milliseconds |
REDIS_JOB_TTL_SECONDS |
86400 |
Export job cache TTL (24 hours) |
# Development (tsx)
npm run preprocess -- --input /path/to/export.xml --output ./csv-output
# Production build
npm run build
npx apple-health-preprocess --input export.zip --output ./csv-output --types heart_rate,step_count
Supported output types: heart_rate, resting_heart_rate, walking_heart_rate_average, heart_rate_variability_sdnn, oxygen_saturation, vo2max, step_count, sleep_analysis, workouts.
# Type check
npm run typecheck
# Lint
npm run lint
npm run lint:fix
# Format
npm run format:fix
# Run tests in watch mode
npm run test:watch
# Full validation pipeline
npm run validate
prompts/.claude/skills/vault/知识库/推荐字段标准.mdnpm test
Test suites cover:
Run the full pipeline before submitting changes:
npm run validate
The CLI refuses to write into a directory that already contains files. Provide a new path or clear the target directory first.
redis-cli ping should return PONGREDIS_URL matches your instanceREDIS_ENABLED=false to run without cachingrm -rf node_modules dist
npm install
npm run validate
Refer to vault/知识库/推荐字段标准.md and include it as context when prompting your AI assistant.
Use forward slashes or quoted paths:
npm run preprocess -- --input "D:/exports/export.xml" --output "./output"
npm run validate before committingSee CODE_OF_CONDUCT.md and SECURITY.md for community and security guidelines.
Do I need Redis? No. Redis is optional and only caches export job metadata.
Which AI tools work? Any model that accepts text prompts: Claude, ChatGPT, Gemini, or local models via Ollama or LM Studio.
Is my data sent to the cloud? Only if you paste it into a cloud AI service. The vault itself is local Markdown and CSV.
Can I use this without Obsidian? Yes. Prompts, skills, and CSV outputs work with any editor.
Where is the detailed setup guide? See guides/快速开始.md and guides/FAQ.md.
MIT — Copyright (c) Leo (@runes_leo)