04-26 16:00 · 开源,加密货币,数据分析,桌面工具,趋势检测
Crypto AI Analytics is a sophisticated desktop tool designed for data-driven crypto market analysis and intelligent trend detection.
📈 Crypto AI Analytics
Crypto AI Analytics is a sophisticated desktop tool designed for data-driven crypto market analysis and intelligent trend detection. Built for serious researchers and developers, it utilizes AI models to parse complex market datasets, identify patterns, and provide insightful visualizations for your trading strategies. With an intuitive dashboard and secure data handling, it allows you to optimize your research workflow without compromising your personal API credentials.
Whether you are performing technical analysis, testing historical scenarios, or exploring machine learning-based price predictions, Crypto AI Analytics provides the powerful workspace you need to analyze the market smarter. 🚀
👥 Who Is Crypto AI Analytics For?
Crypto AI Analytics is ideal for users interested in quantitative finance and market research:
📊 Market Researchers studying volatility, sentiment, and historical patterns
💡 Quantitative Analysts developing new data-backed trading logic
🖥️ Developers building custom connectors for cryptocurrency exchange data
🧑🏫 Technical Traders seeking advanced visual indicators beyond standard charting
🧪 Backtesting Enthusiasts simulating and analyzing various financial scenarios
🎯 What Can You Use It For?
Crypto AI Analytics helps you turn raw exchange data into clear insights:
🔍 Trend Analysis – leverage neural networks to detect shifts in market momentum
📑 Automated Reporting – track your custom assets with AI-generated summary reports
🧪 Historical Simulation – simulate strategy outcomes based on past market data
🌐 Exchange Aggregation – view and analyze data across multiple providers
🤖 Strategy Prototyping – fine-tune your logic using real-time market inputs
✨ Key Features
Crypto AI Analytics includes a professional-grade toolset for market research:
🛡️ Zero-Credential Policy – secure integration using your own read-only API keys stored locally
⚡ Optimized Data Pipeline – high-performance architecture for processing live data streams
📊 Visual Dashboard – clear, professional-grade charts for identifying anomalies
🔄 Adaptive Learning – utilizes ML algorithms that evolve with incoming market inputs
🧩 Custom Plugins – support for user-defined Python or JS strategies and custom indicators
📂 Offline Export – save your entire research session, data exports, and logs for review
⚙️ Installation
To install Crypto AI Analytics, simply go to the Releases section of this repository and download the latest available version for your operating system. After downloading, extract the archive if necessary and run the installer file. Follow the installation steps to complete the setup.
👉 Download the latest version here:
💻 System Requirements
🖥️ OS: Windows 10 / 11, macOS, or Linux
🧠 RAM: 8 GB minimum (16 GB recommended for historical backtesting)
🌐 Connection: High-speed internet required for live market data
💾 Storage: At least 5 GB of free space for database and logs
⭐ Support the Project
If you find this project useful, consider giving the repository a Star ⭐ on GitHub.
Your support helps the project grow and improve!
(Disclaimer: This tool is designed for educational and analytical purposes. Financial market activity involves significant risk; this software does not guarantee results. Users are responsible for their own trades and data management.)
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04-26 16:00 · 开源项目,AI自动化,内容生成,微信生态,GitHub Trending
Codex/CLaude/Gemini compatible skill: collect AI trends, write WeChat Official Account articles, generate images, publish to drafts
自动采集 AI 热点，撰写公众号文章，生成配图并发布到微信公众号草稿箱。
本仓库已移除所有硬编码的密钥/Token/本地路径；你需要通过环境变量自行配置（见下文）。
把整个目录放到你的 Skills 目录下（任选其一）：
~/.codex/skills/wechat-ai-publisher/
$CODEX_HOME/skills/wechat-ai-publisher/
~/.claude/skills/wechat-ai-publisher/
（Claude Code / Cloud Code）~/.gemini/skills/wechat-ai-publisher/
（Gemini：建议约定此路径，具体以你的工具为准）~/.openclaw/workspace/skills/wechat-ai-publisher/
（OpenClaw 默认 workspace）~/.openclaw/skills/wechat-ai-publisher/
（OpenClaw 全局 skills）
- 复制配置模板：
cp .env.example .env
- 在
.env
填入以下变量：
WECHAT_APPID
/WECHAT_SECRET
：公众号后台获取（用于换取access_token
）。REPLICATE_API_KEY
：用于生成配图（Replicate）。WECHAT_AUTHOR
（可选）：文章作者字段（默认：田威 AI
）。DEFAULT_COVER_URL
（可选）：图片生成失败时的兜底封面 URL。
- 让环境变量生效（示例）：
set -a
source .env
set +a
辅助脚本 scripts.sh
需要以下命令可用：
bash
,curl
,jq
Skill 运行环境（采集内容）依赖你已配置好对应工具/API：
mcp__tavily__tavily-search
/mcp__tavily__tavily-extract
mcp__exa__web_search_exa
本仓库不包含这些服务的 API Key，你需要在自己的 Agent/IDE/CLI 工具里按其官方方式配置。
注意：
scripts.sh
只是便捷脚本；Skill 本体逻辑在SKILL.md
。
示例文章（科普/护理/科技风格）：examples/nursing-tech-article.md
加载脚本：
source ./scripts.sh
常用函数：
get_wechat_token
generate_image "<prompt>" ["16:9"]
upload_to_r2 <local_path> <remote_path>
publish_article "<title>" "<content_html>" "<cover_prompt>" "<digest>"
参数建议：content_html
尽量从文件读取，避免 shell 引号/换行转义问题：
content_html=$(cat ./content.html)
publish_article "标题" "$content_html" "封面图 prompt" "摘要"
- 不要把
.env
提交到仓库；本仓库已通过.gitignore
忽略它。 - 任何线上发布前，建议在公众号后台/接口调用白名单中配置好服务器 IP（如有要求）。
OpenClaw 自带 Cron（需要你的 OpenClaw Gateway 常驻运行）。
推荐做法：把「默认配置」固定在 Skill 里，Cron 只负责每天触发一次；当你想改主题/风格/口吻时，再在触发消息里追加说明即可。
默认配置（可在 SKILL.md
里改）：
- 主题：AI工具
- 风格：github
- 配图：封面 + 3 张
- 作者：田威 AI
示例：每天 09:00（上海时区）触发一次发布（使用默认配置）：
openclaw cron add \
--name "wechat-ai-daily" \
--cron "0 9 * * *" \
--tz "Asia/Shanghai" \
--session isolated \
--message "发布AI热点；不要提问，直接执行"
临时覆盖默认配置（只要把需求“说出来”即可）：
openclaw cron add \
--name "wechat-ai-daily" \
--cron "0 9 * * *" \
--tz "Asia/Shanghai" \
--session isolated \
--message "发布AI热点；主题=护理；风格=purple；配图=仅封面；写得更科普一些；不要提问，直接执行"
查看/管理：
openclaw cron list
openclaw cron delete --name "wechat-ai-daily"
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04-26 16:00 · 科技,GitHub
AI-powered content pipeline: trend discovery → research → social publishing. Built with Claude Agent SDK + MCP.
AI-powered content pipeline: from trend discovery to social publishing.
Built with Claude Agent SDK + MCP (Model Context Protocol), featuring 3 integrated MCP servers for real-time trends, web scraping, and research automation.
Three clear entry points — no complex menus, just pick and go:
Watch Claude work in real-time — tool calls shown as collapsible blocks with MCP server badges:
- trend-pulse (green) — 20 real-time trend sources, zero auth
- cf-browser (blue) — Cloudflare Browser Rendering for JS pages
- notebooklm (purple) — Research + artifact generation (podcast/slides/video)
- studio — Built-in publishing + history tools
Full markdown rendering with syntax highlighting, clickable file path previews, cost/duration tracking, and inline images:
Full support for Traditional Chinese, English, and Japanese — all UI, system prompts, and pipeline cards adapt:
Built-in Threads publishing via native fetch()
— no Python dependency. Every post is checked against Meta's patent-based 5-dimension scoring:
Quality gates: Overall >= 70, Conversation Durability >= 55.
Supported post types: text, image, video, carousel (2-20 items), poll, GIF, link preview, text attachment, spoiler (media blur + text), ghost (24hr ephemeral), quote post, reply control, topic tag, alt text, link-comment auto-reply.
- Multiple Threads accounts with independent personas
- Per-account style (e.g., "tech-educator", "futurist")
- Per-account persona prompt for tone adaptation
- Matrix publishing: same topic → unique content per account
Cron-based task scheduling with per-account targeting:
- Define prompt templates with cron schedules
- Target specific social accounts
- Quality gate enforcement (min score threshold)
- Auto-publish or manual review mode
- Execution history with cost/duration tracking
- Reduced tool set for unattended safety (no Bash/Read/Write)
NotebookLM integration for auto-generating visuals:
- Image cards — slides PDF as single-page visual cards
- Carousel — multi-page slides split into carousel images
- Podcast — AI-generated audio discussion
- Video — slides + podcast combined via ffmpeg
- Mind maps, reports, flashcards, study guides
All downloads stay within the workspace directory.
Browse and preview workspace files directly in the UI:
- Directory tree with depth control
- Text file preview (syntax-highlighted)
- Binary file preview (images, PDFs, audio, video)
- Clickable file paths in chat responses
- Workspace-contained — no access outside project folder
Content integrity enforced at the system level:
- Read original sources — Never write from titles/metadata alone. 1+ primary source per topic, 2+ for controversial.
- Timeline verification — Every fact gets a verified timestamp. Time words mapped by age.
- No AI filler — System prompt blocks generic phrases ("in today's world" / "it's worth noting").
- Multiple concurrent sessions with independent workspaces
- Session resume on app restart (conversation history preserved)
- Idle session eviction (30min TTL)
- Query cancellation via interrupt button or CLI
System/light/dark theme with persistent preference across sessions.
Full CJK input method support — Enter during Chinese/Japanese character composition does not trigger send. Shift+Enter for newline.
- AI agent operates within session workspace only
- No access to ~/Downloads, ~/Desktop, ~/Documents, or system paths
- Credentials stored in local SQLite — never searched from filesystem
- Publishing via built-in MCP tool only (no external scripts)
- Session workspace validated at creation (blocks system paths)
- File API restricted to workspace root (symlink-safe realpath check)
┌─────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ React UI │────▶│ Express + WS │────▶│ Claude Agent │
│ (Vite) │◀────│ Server │◀────│ SDK │
└─────────────┘ └──────────────────┘ └────────┬────────┘
│
┌──────────────────────────┤
│ │ │
┌──────▼──┐ ┌──────▼───┐ ┌─────▼──────┐
│ trend- │ │ cf- │ │ notebooklm │
│ pulse │ │ browser │ │ │
│ (MCP) │ │ (MCP) │ │ (MCP) │
└─────────┘ └──────────┘ └────────────┘
20 sources Cloudflare Podcast/Slides
zero auth Browser /Video/Report
- Node.js >= 18
- Claude Code CLI installed and authenticated (
npm install -g @anthropic-ai/claude-code
) - Python 3.10+ (for MCP servers — or use
uvx
for zero-config setup)
Five ways to install — pick the one that fits your workflow:
Download the latest .dmg
from GitHub Releases, open it, and drag to Applications.
- Double-click to launch — server starts automatically
- No terminal, no Node.js install needed
- MCP servers auto-detected via uvx (install uv first)
- All desktop features included: Web UI + MCP + Publishing
Requires: macOS (Apple Silicon). Intel Mac build available on request.
npm install -g @claude-world/studio
# Set up MCP servers (one-time, auto-cached via uvx)
npx @claude-world/studio setup-mcp
# Start
studio serve
# Web UI: http://localhost:5173
# API: http://127.0.0.1:3001
After install, both studio
and claude-world-studio
commands are available
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04-26 16:00 · 开源项目,AI内容生成,自动化流程,趋势追踪,技术威胁
-
Research trending topics and generate ready-to-post social media content — as a Hermes/OpenClaw skill.
trendingcontent is a two-phase AI agent skill:
- Research phase — scrapes Reddit, X/Twitter, YouTube, TikTok, HackerNews, Bluesky and Brave Search to surface the most engaging content about your topic over a configurable time window (7, 15, 30, or up to 90 days).
- Content generation phase — uses the research findings to generate platform-specific social media copy: Twitter/X threads, LinkedIn posts, and Instagram captions.
Built on top of last30days by @mvanhorn, extended with:
- Variable time windows (not just 30 days)
- Multi-platform content generation (Twitter, LinkedIn, Instagram)
- Tone control (professional, casual, educational, viral)
- Multilingual output (English, Spanish, Portuguese)
- Hermes/OpenClaw skill standard compatibility
git clone https://github.com/gabogabucho/trendingcontent-agent.git
cd trendingcontent-agent
pip install -r requirements.txt
export SCRAPECREATORS_API_KEY="your_key" # required
export BRAVE_API_KEY="your_key" # optional but recommended
Or add them to your .env
file.
Get a ScrapeCreators API key at scrapecreators.com. Get a Brave Search API key at brave.com/search/api.
python scripts/trendingcontent.py "artificial intelligence" --days=7 --platform=all
python scripts/trendingcontent.py <topic> [options]
Options:
--days=N Time window: 7-90 days (default: 30)
--platform twitter | linkedin | instagram | all (default: all)
--tone professional | casual | educational | viral (default: professional)
--lang en | es | pt (default: en)
--sources=S1,S2 Only use these sources (reddit,twitter,youtube,tiktok,bluesky,hackernews,brave)
--disable=S1,S2 Disable specific sources
--list-sources Show all available sources
--quick Fewer sources, faster
--deep More sources, thorough
--research-only Output research only, skip content generation
# AI trends last 7 days → all platforms
python scripts/trendingcontent.py "artificial intelligence" --days=7
# Web3 → LinkedIn post in Spanish, professional tone
python scripts/trendingcontent.py "web3" --days=15 --platform=linkedin --lang=es
# Climate tech → viral Twitter thread
python scripts/trendingcontent.py "climate tech" --days=30 --platform=twitter --tone=viral
# Niche topic — only Reddit and YouTube (no HackerNews)
python scripts/trendingcontent.py "sourdough bread" --sources=reddit,youtube,brave
# Disable sources that don't fit your topic
python scripts/trendingcontent.py "fintech" --disable=hackernews,tiktok
# See all available sources
python scripts/trendingcontent.py --list-sources
# Research only, no content
python scripts/trendingcontent.py "LLMs" --days=14 --research-only
This repository follows the Hermes skill standard. To install as a skill:
# Copy to your Hermes skills directory
cp -r . /path/to/hermes-agent/skills/social-media/trendingcontent/
# Add API keys to your Hermes .env
echo "SCRAPECREATORS_API_KEY=your_key" >> ~/.hermes/.env
echo "BRAVE_API_KEY=your_key" >> ~/.hermes/.env
The agent will automatically discover the skill via SKILL.md
.
═══════════════════════════════════════════════
TRENDINGCONTENT — CONTENT GENERATION BRIEF
═══════════════════════════════════════════════
Topic: artificial intelligence
Period: Last 7 days
Language: English
Tone: Professional
Platforms: Twitter, LinkedIn, Instagram
───────────────────────────────────────────────
RESEARCH SUMMARY
───────────────────────────────────────────────
[ranked trending content with titles, scores, URLs]
───────────────────────────────────────────────
CONTENT INSTRUCTIONS
───────────────────────────────────────────────
[platform-specific format specs + tone guidance]
- Python 3.9+
yt-dlp
— YouTube transcript extractionrequests
— HTTP calls- ScrapeCreators API key (required)
- Brave Search API key (optional)
- Original research engine: last30days-skill by @mvanhorn — MIT License
- Social media generation layer & Hermes skill packaging: @gabogabucho
MIT License — see LICENSE for details.
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04-26 15:59 · 科技,GitHub
全球技术热点，AI 精选速递。（Global tech trends, fast-picked by AI）
全球技术热点，AI 精选速递。
聚合 GitHub Trending、Hacker News、Product Hunt，用 AI 精选和解读全网最值得关注的技术项目。
Trending AI 是一款使用 Kotlin Multiplatform (KMP) 构建的跨平台应用。聚合 GitHub Trending、Hacker News、Product Hunt 三大技术信息源，通过 AI 智能摘要和每日精选，帮你高效发现全网最值得关注的技术项目。
- 🌐 多源聚合：GitHub Trending、Hacker News、Product Hunt 一站浏览。
- 🤖 AI 智能摘要：每个项目自动生成 AI 分析，快速了解核心价值。
- ⭐ 每日精选：AI 从全网筛选最值得关注的技术项目。
- 📅 历史回溯：查看任意日期的趋势榜单，不错过每一天。
Kotlin Multiplatform | Compose Multiplatform | Ktor | Material 3
本项目采用 MIT 协议开源 - 详情请参阅 LICENSE 文件。
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04-25 13:57 · 开源,AI工具,文档处理,PDF编辑,OCR
Download Acrobat AI Assistant PDF Editor Desktop Windows 11 Acrobat DC 2026 Full Version Electronic Signature Tool OCR PDF to Word Document Cloud Sync PDF Security Redaction Tool Fill and Sign Profess
Adobe Acrobat Desktop 2026 is the industry-standard environment for professional PDF management, digital document security, and AI-driven insights. This 2026 optimized build features the Acrobat AI Assistant, allowing users to summarize complex documents, extract cross-file data, and generate intelligent responses via natural language processing. Engineered for Windows 11 and high-performance workstation environments, it provides a seamless bridge between local desktop editing and Adobe Document Cloud synchronization. Master your workflow with 70+ advanced features: including AI-powered OCR, secure electronic signatures (E-Sign), professional redaction tools, and high-fidelity file conversion for the modern digital office.
- Acrobat AI Assistant: Generative AI for document summaries, citations, and intelligent Q&A.
- Advanced PDF Editing: Full-text reflow, image manipulation, and vector asset integration.
- High-Fidelity OCR: AI-enhanced optical character recognition for searchable 8K scans.
- Electronic Signature Suite: Legally binding e-signatures with real-time tracking and audit trails.
- Document Cloud Sync: Seamless transition between Desktop, Web, and Mobile environments.
- Professional Security: AES-256 encryption, sensitive data redaction, and certificate-based protection.
- Batch Processing: High-speed conversion, merging, and organization of multi-document datasets.
MIT License – shared for educational, software administration, and enterprise workflow preservation.
If Adobe Acrobat Desktop 2026 improved your document workflow or simplified your AI analysis — please star the repository! It helps the professional community discover the most efficient PDF tools. ❤️
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04-23 09:20 · 数据可视化,开源,教育分析,仪表盘,Power BI
Interactive Power BI Dashboard analyzing NYC Graduation Results (Cohorts 2012-2019). Includes 5 objectives: Graduation Trend, Borough Comparison, Student Outcomes, Dropout Risk Map, and Advanced Regen
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04-09 08:19 · 科技,GitHub
A sports card analysis system with real-time price tracking, market trend insights, and smart alerts. It monitors marketplaces, detects value changes, and notifies users of buy/sell opportunities, helping collectors and investors make data-driven decisions.
This tool helps analyse and visualise recently created smart contracts on the Ethereum blockchain.
- Install dependencies
poetry install
- Initialize the database
poetry run invoke build
- Start the app with:
poetry run invoke start
Run test battery
poetry run invoke test
Generate coverage report
poetry run invoke coverage-report
Check code accuracy
poetry run invoke lint
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04-09 08:19 · 开源工具,加密货币,量化交易,市场监控,金融科技
Tracks funding rates across all Hyperliquid perp pairs and alerts on extreme deviations, sustained trends, and cross-pair carry arbitrage opportunities.
Tracks funding rates across all Hyperliquid perpetual pairs in real time. Alerts on extreme funding deviations, cross-pair funding arbitrage opportunities, and sustained funding trends that indicate crowded positioning.
Last updated: March 2026
Hyperliquid Funding Monitor continuously reads funding rates for every perpetual pair on Hyperliquid and compares each rate against its own historical baseline. When a pair's funding rate deviates significantly from its norm, it means one side of the market has become crowded - longs are paying shorts (positive funding) or shorts are paying longs (negative funding).
Extreme positive funding on a pair means leveraged longs are dominant. If price has not moved proportionally, this often resolves by either price catching up or longs getting squeezed. Extreme negative funding means leveraged shorts are dominant. The monitor tracks both conditions and alerts when deviation crosses a configurable threshold.
The bot also scans for cross-pair funding divergence - cases where two correlated assets have significantly different funding rates. This creates a carry opportunity: long the negative-funding asset, short the positive-funding asset, collecting the funding spread while running a delta-neutral position.
All funding data is read from Hyperliquid's public REST API. No account or private key required.
The scanner compares funding rates across pairs grouped by asset class (BTC, ETH-correlated, SOL-correlated, HYPE). When two correlated pairs show a funding spread above the minimum threshold, it outputs the long/short pair combination, the spread in annualized percentage, and the estimated daily carry per $1,000 notional.
- Poll - fetches current funding rates for all Hyperliquid perp pairs on configurable interval
- Baseline - maintains rolling 7-day baseline for each pair's funding rate
- Evaluate - calculates deviation score and flags pairs above threshold
- Scan - checks cross-pair funding spreads within correlated asset groups
- Alert - sends Telegram alert with funding context, deviation, and carry details if applicable
[monitoring]
poll_interval_seconds = 60
deviation_threshold = 2.0 # Alert when funding is 2x the 7-day baseline
trend_window_hours = 6 # Hours of consistent direction to trigger trend alert
cumulative_24h_threshold = 0.3 # Alert when 24h cumulative funding exceeds 0.3%
[arbitrage]
enabled = true
min_spread_annualized_pct = 50 # Minimum annualized spread to flag as opportunity
[assets]
monitor = [] # Empty = all pairs
[alerts]
telegram_bot_token = ""
telegram_chat_id = ""
[api]
rest_endpoint = "https://api.hyperliquid.xyz"
{
"event": "funding_extreme",
"timestamp": "2026-03-19T16:00:00Z",
"asset": "SOL",
"funding_rate_8h": 0.0041,
"baseline_7d": 0.0011,
"deviation_multiple": 3.7,
"direction": "positive",
"annualized_rate_pct": 222.3,
"trend_hours": 8,
"alert_type": "extreme_positive"
}
Configuration used:
- Deviation threshold: 2x baseline
- Arb scanner: enabled, min 50% annualized
Extreme funding detected:
What is Hyperliquid Funding Monitor? It tracks funding rates for all Hyperliquid perp pairs and alerts when rates deviate significantly from historical norms. Extreme funding often precedes directional price moves as the crowded side gets squeezed.
What does extreme positive funding mean? Leveraged longs are paying shorts. This means LONG positions are dominant. If price has not moved upward proportionally, the crowded longs may get squeezed, causing a sharp downward move.
What is the funding arbitrage scanner? It looks for correlated pairs with significantly different funding rates. Going long the negative-funding pair and short the positive-funding pair collects the spread while maintaining approximate delta neutrality.
How is the baseline calculated? A 7-day rolling average of the funding rate for each pair. The deviation multiple is the current rate divided by this baseline.
How often does it poll? Every 60 seconds by default. Funding rates update every 8 hours on Hyperliquid, but the bot catches the change immediately when it occurs.
Does it track cumulative funding? Yes. It tracks the total funding paid or collected over 24 hours per pair and alerts when cumulative funding exceeds the configured threshold.
Can I monitor specific pairs only?
Yes. Populate the monitor
list in config with specific pair tickers. Leave empty to monitor all pairs.
Does it need a private key? No. The monitor is read-only and uses Hyperliquid's public API.
What is the trend alert? When funding for a pair has been moving in the same direction (increasing or decreasing) for a configurable number of hours, it triggers a trend alert indicating sustained crowded positioning.
How do I use the funding data for trading? Extreme positive funding = potential short setup (longs overpaying, squeeze risk). Extreme negative = potential long setup. The arbitrage scanner output is useful for funding carry strategies.
- Funding extreme alerts - catch pairs with unsustainably high or low
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04-07 01:22 · 开源,健康科技,数据分析,隐私保护,本地化AI
Free, open-source blood work dashboard — AI-powered PDF import, DNA raw data analysis (42 SNPs), trend charts, and personalized health insights for 287+ biomarkers. Local-first, no account required.
getbased is a free, open-source health dashboard that turns lab PDFs into interactive charts and AI-powered health insights. Track 287+ biomarkers over time, detect trends, and get personalized interpretations — all stored locally in your browser with no account required.
Live app · Documentation · Discord · Nostr
- AI-powered PDF import — drop any lab report (any format, language, or country) and AI extracts and maps results to 287+ known biomarkers automatically. Batch import, direct image import (JPG/PNG/WebP), auto image mode for scanned PDFs
- Biomarker trend charts — interactive line charts with proportional time scale, reference bands, optimal ranges, and trend detection across 16 categories
- AI chat — ask questions about your results with full health context, image attachments, multiple personalities, conversation threads
- DNA import — upload raw data from AncestryDNA, 23andMe, MyHeritage, FTDNA, or Living DNA. 42 curated SNPs across 10 categories (methylation, iron, lipids, vitamin D, etc.) with APOE haplotype resolution. Genetic factors shown on dashboard, detail modals, and in AI context
- Specialty lab adapters — OAT (165 markers), fatty acids (Spadia, ZinZino, OmegaQuant), Metabolomix+. Any other specialty test imports through the custom marker pipeline
- Biological age — PhenoAge (Levine 2018) + Bortz Age (Bortz 2023) combined into a unified Biological Age marker with component breakdown
- Calculated markers — HOMA-IR, BUN/Creatinine ratio, free water deficit, lipid ratios (TG/HDL, LDL/HDL, ApoB/ApoA-I), NLR, PLR, De Ritis ratio, hs-CRP/HDL cardiovascular risk ratio
- Trend alerts — sudden changes and linear regression flagged on the dashboard
- Correlation viewer — compare any two markers, heatmap view
- Compare dates — side-by-side comparison of any two lab dates
- Manual entry — add results without a PDF, create custom biomarkers
- Marker glossary — searchable reference for all markers with values and ranges
- Interpretive lens — frame AI analysis through specific scientific paradigms or experts
- 9 lifestyle context cards — diet & digestion, sleep, exercise, stress, light & circadian, environment, EMF assessment (Baubiologie SBM-2015), and more — each gets an AI health rating and enriches all interpretations
- Menstrual cycle tracking — phase-aware reference ranges, cycle phase bands on charts, perimenopause detection, symptom tracking
- Supplement & medication timeline — overlaid on charts to correlate with biomarker changes
- PDF reports — export a full health report as PDF
- Multi-profile — track multiple people, client list with search/sort/filter
- All data stored locally in your browser (localStorage + IndexedDB) — nothing on a server
- Personal info stripped from PDFs before AI processing (regex + streaming local AI obfuscation)
- AES-256-GCM encryption at rest
- Automatic backups (IndexedDB snapshots + daily folder backup via File System Access API)
- Venice AI end-to-end encryption option — prompts encrypted client-side (ECDH secp256k1 + AES-256-GCM), decrypted only inside a TEE. Nothing readable in transit or at rest on their servers
- Run a local AI server and nothing leaves your machine at all
- No account, no sign-up, no tracking
Opt-in feature that lets AI agents query your lab context — coding agents (Claude Code, Cursor), messenger bots (Hermes Agent, OpenClaw), or any MCP-compatible tool.
- Enable in Settings → Data → Agent Access to generate a read-only token
- Context is pushed to a lightweight gateway on every save and profile switch
- Per-profile: each profile's context is stored separately; agents can query any profile by ID
- Use getbased-mcp to connect Hermes Agent, OpenClaw, or any MCP-compatible agent
- Only the AI-readable context text is shared — never your mnemonic or raw lab data
- Token is revocable at any time from the same settings panel
Switch providers anytime. All non-AI features work without a provider configured.
git clone https://github.com/elkimek/get-based
cd get-based
node dev-server.js
Open http://localhost:8000
. You need an AI provider API key or local AI server for PDF import and chat. All other features work without one.
No build tools, no bundler, no package manager. Pure ES modules — 36 files under js/
.
- Chart.js for interactive charts
- pdf.js for PDF text extraction
- All dependencies vendored locally (
vendor/
) — no CDN calls - Installable as a PWA (works offline for non-AI features)
29 browser-based test files run headlessly:
./run-tests.sh
Starts a local server, runs all tests via Puppeteer, exits 0/1.
See CONTRIBUTING.md. Project board: planned features.
GPL-3.0. See LICENSE.
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