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AI Pine Script generator for TradingView strategies and indicators.
Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Free tool that auto-generates conversational, browsable documentation for any public GitHub repo, from the makers of Devin.
Side-by-side arena to compare AI coding models and build multi-file apps, with a public leaderboard and battle mode.
No public pricing
No public pricing
- ✦AI-powered Pine Script code generation
- ✦Custom strategy and indicator creation
- ✦Error correction and code optimization
- ✦TradingView integration
- ✦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
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦AI-generated documentation for GitHub repos
- ✦Conversational Q&A about a codebase
- ✦Browsable index of popular repositories
- ✦Deep code indexing via Devin
- ✦Head-to-head model comparison
- ✦Battle mode matchups
- ✦Public model leaderboard
- ✦Multi-file app generation
- ✦File uploads as input
- →Generating custom trading strategies for backtesting on TradingView
- →Creating custom indicators for technical analysis
- →Automating the process of writing Pine Script code
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Understanding an unfamiliar codebase quickly
- →Onboarding to open-source projects
- →Answering questions about repo internals
- →Choosing the best coding model
- →Benchmarking AI code quality
- →Prototyping small apps