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AI Pine Script generator for TradingView strategies and indicators.
Undetectable desktop AI assistant that feeds real-time answers during coding and technical interviews.
Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Open-source, plugin-based ChatGPT command-line toolkit for AI commit messages, shell commands and translation in the terminal.
Spreadsheet-style Python data tool inside Jupyter that generates code via AI so analysts and data scientists can skip hand-coding.
No public pricing
No public pricing
No public pricing
- ✦AI-powered Pine Script code generation
- ✦Custom strategy and indicator creation
- ✦Error correction and code optimization
- ✦TradingView integration
- ✦Real-time AI answers during technical interviews
- ✦Invisible to screen sharing and recording
- ✦Hidden from dock, tray and activity monitor
- ✦Click-through overlay
- ✦Live audio capture and transcription
- ✦Lifetime unlimited access license
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦npm-installable ChatGPT CLI
- ✦AI-generated Git commit messages
- ✦Natural-language to shell commands
- ✦AI translation plugin
- ✦Extensible plugin system
- ✦Build custom AI CLI workflows
- ✦Spreadsheet interface inside Jupyter notebooks
- ✦AI-generated Python code from spreadsheet actions
- ✦Runs on customer infrastructure (no data sent to Mito)
- ✦Bring-your-own LLM API keys
- ✦Excel-to-Python conversion
- ✦Compatible with existing Jupyter extensions
- →Generating custom trading strategies for backtesting on TradingView
- →Creating custom indicators for technical analysis
- →Automating the process of writing Pine Script code
- →Getting live help on coding interview problems
- →Answering technical questions in real time
- →Avoiding detection during screen-shared interviews
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Writing commit messages automatically
- →Turning plain English into terminal commands
- →Translating text from the command line
- →Creating personal AI CLI tools
- →Analysts automating Excel-style reports without hand-writing code
- →Data scientists speeding up exploratory data analysis
- →ML engineers iterating on feature engineering in notebooks
- →Enterprises needing private, self-hosted AI coding assistance