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devActivity
✓ verifiedFreemium

GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.

👁 52K/mo

Thin 'Lingbot-map' agent listing on github.com with zero traffic; too thin to tell.

5.2K
Qoder
Freemium
👁 2.7M/mo32K
Pricing
Free: $0/contributor (up to 7 contributors, 90-day retention)
Premium: $10/contributor (unlimited contributors, AI insights)

No public pricing

No public pricing

No public pricing

Free trial available

Core features
  • Contribution and work-quality analytics
  • Automated, AI-powered performance reviews
  • Retrospective insights
  • Operational bottleneck alerts
  • Gamification with XP, levels and leaderboards
  • Uses Git metadata without accessing source code
  • Fast tensor operations
  • Differentiable tensors for gradient-based optimization
  • Network connectivity
  • Integration with Bun and Flashlight
  • Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
  • Enhanced Context Engineering for deep codebase analysis and adaptive memory
  • Intelligent Agents for autonomous planning, coding, and testing
  • Spec-Driven Development for clarifying requirements and automating execution
  • Intelligent Codebase Search and Advanced Repository Insight
  • Context-aware code completions and next-edit suggestions
  • Support for leading AI models (Claude, GPT, Gemini)
Use cases
  • Automating developer performance reviews
  • Spotting delivery bottlenecks
  • Generating retrospective insights
  • Motivating teams via gamification
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
  • Delegating complex software development tasks to AI agents for autonomous completion.
  • Performing multi-file code edits and refactoring through natural language chat.
  • Gaining deep architectural understanding of a codebase to resolve issues with precision.
  • Generating unit tests, code explanations, and uncovering codebase architecture.
  • Systematically tackling software development tasks from planning to testing.
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