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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
AI screenplay-coverage tool returning structured coverage reports and development notes per script in minutes.
Local desktop app that assembles code-context prompts for LLMs, with API integrations, token tracking, and prompt saving.
Agentic coding platform (Cosmos) that runs software-dev agents at org scale, using a codebase context engine to cut token cost.
Free tool that auto-generates conversational, browsable documentation for any public GitHub repo, from the makers of Devin.
Free trial available
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- ✦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
- ✦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)
- ✦Source-code context and prompt management
- ✦Custom and formatting instructions
- ✦BYOK API integrations (OpenAI, Claude, Gemini, etc.)
- ✦Token-limit tracking
- ✦Code-edit feature with visual diffs and backups
- ✦Local, offline prompt generation
- ✦Context Engine for codebase understanding
- ✦Agents across the full SDLC
- ✦Model routing / bring-your-own-keys
- ✦Automated code review and test coverage
- ✦CLI, MCP and native tool integrations
- ✦Enterprise security (SOC 2, ISO 42001, SSO)
- ✦AI-generated documentation for GitHub repos
- ✦Conversational Q&A about a codebase
- ✦Browsable index of popular repositories
- ✦Deep code indexing via Devin
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Getting screenplay coverage quickly
- →Development notes before rewrites
- →Evaluating scripts for production
- →Iterating affordably on drafts
- →Building context-rich prompts for AI coding
- →Comparing model outputs on the same task
- →Reusing saved prompts across tech stacks
- →Keeping code private during prompt creation
- →Automating PR code review
- →Raising test coverage
- →Incident investigation and remediation
- →Large-scale migrations and onboarding
- →Understanding an unfamiliar codebase quickly
- →Onboarding to open-source projects
- →Answering questions about repo internals