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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
AI Pine Script generator for TradingView strategies and indicators.
AI screenplay-coverage tool returning structured coverage reports and development notes per script in minutes.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
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
- ✦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
- ✦AI-powered Pine Script code generation
- ✦Custom strategy and indicator creation
- ✦Error correction and code optimization
- ✦TradingView integration
- ✦11-section AI coverage reports
- ✦Scene-by-scene development notes
- ✦AI chat assistant for deeper insights
- ✦Script dashboard and organization
- ✦Results in minutes
- ✦Free screenwriting tools (formatter, character builder)
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦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
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Generating custom trading strategies for backtesting on TradingView
- →Creating custom indicators for technical analysis
- →Automating the process of writing Pine Script code
- →Getting screenplay coverage quickly
- →Development notes before rewrites
- →Evaluating scripts for production
- →Iterating affordably on drafts
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →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