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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.
Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
AI prototyping tool that generates UI matching your design system, letting product teams test features fast.
Local desktop app that assembles code-context prompts for LLMs, with API integrations, token tracking, and prompt saving.
No public pricing
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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
- ✦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
- ✦150+ recommendations across 50+ AWS services
- ✦Zombie and unused resource cleanup
- ✦Over-provisioned rightsizing
- ✦Idle-resource scheduler
- ✦SpotBot for ECS Fargate spot/on-demand switching
- ✦AWS console extension with Slack/Teams alerts
- ✦AI UI generation from prompts
- ✦Match existing styling and design systems
- ✦Rapid, high-fidelity prototyping
- ✦Live team editing and sharing
- ✦Enterprise security and compliance
- ✦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
- →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
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
- →Prototype new product features
- →Test designs with customers
- →Build design-system-consistent mockups
- →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