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36K visits/mo
DeepWiki logo
DeepWiki
✓ verifiedFree

Free tool that auto-generates conversational, browsable documentation for any public GitHub repo, from the makers of Devin.

1.2M visits/mo
Kilo Code logo
Kilo Code
✓ verifiedFreemium

Open-source AI coding agent for VS Code, JetBrains, CLI and cloud, with 500+ models at zero inference markup and BYOK.

10K visits/mo57K saves
389K visits/mo
PromptLayer logo
PromptLayer
✓ verifiedFree

Prompt engineering, management, and LLM observability platform.

212K visits/mo
Pricing

No public pricing

No public pricing

Free: $0 (open source; AI usage billed separately)
Teams: $15/user/mo (14-day free trial)
KiloClaw hosting: from $55/mo

Free trial available

Pay-as-you-go: 42.8% platform fee for corporate, 33.3% for academic/non-profit (no monthly fee)
Participant payment: minimum $8.00/hr, recommended $12.00/hr

No public pricing

Core features
  • Coding education platform for beginners
  • Curriculum on Next.js, Vercel, and AI
  • AI-powered app development
  • Live events and hackathons
  • Coding community
  • AI-centric platform for software engineers
  • Nia AI for code understanding
  • Context management and codebase understanding tools
  • AI-generated documentation for GitHub repos
  • Conversational Q&A about a codebase
  • Browsable index of popular repositories
  • Deep code indexing via Devin
  • 500+ AI models at zero inference markup
  • Bring-your-own-keys and local model support
  • MIT-licensed, fully open source
  • Works in VS Code, JetBrains, CLI and cloud
  • Agent modes (Code, Architect)
  • Parallel isolated worktrees
  • Slack code reviewer and gateway
  • Access to a verified and engaged participant pool
  • Self-serve platform for easy task setup and launch
  • Tools for AI training and evaluation
  • Fair compensation for participants
  • Audience checker
  • Prompt management
  • Prompt evaluations
  • LLM observability
  • Team collaboration
  • Version control for prompts
  • A/B testing of prompts
  • Prompt Registry
  • Historical backtests
  • Regression tests
  • Usage monitoring
Use cases
  • Learning to code and build AI-powered applications
  • Developing AI agents that can work with code safely and effectively
  • Empowering developers to orchestrate AI agents across the software lifecycle
  • Improving context management and codebase understanding for AI agents
  • Understanding an unfamiliar codebase quickly
  • Onboarding to open-source projects
  • Answering questions about repo internals
  • Writing and refactoring production code with AI
  • Planning features before implementation
  • Running agents across multiple IDEs and the CLI
  • Academic research
  • AI training and evaluation
  • Market research
  • User research & testing
  • Data annotation
  • Training & alignment
  • Evaluation & safety
  • Scaling customer support automation with LLMs
  • Empowering non-technical teams with prompt engineering
  • Building personalized AI interactions
  • Debugging LLM agents
  • Improving content creation processes
  • Managing and monitoring prompts with a team
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