toolspool

Compare tools

Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

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

5.2K
Pixels2Flutter
✓ verifiedFree

Turns UI screenshots into working Flutter code.

12K
CodeGPT
✓ verifiedFreemium

IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.

👁 262K/mo
Code Autopilot
✓ verifiedFreemium

AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.

Anima
✓ verifiedFreemium

AI design-to-code tool that converts Figma designs or cloned websites into HTML/React and builds apps with vibe coding.

👁 321K/mo1.3K
Pricing

No public pricing

No public pricing

Free: $0/mo (BYOK, 30 free interactions)
AutoComplete Add-on / BYOK Pro: $8/mo per seat ($6.67 annual)

No public pricing

Free: $0/mo (5 code generations/day, 5 imports)
Enterprise: from $500/mo billed annually (SSO, SLAs)
Core features
  • 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)
  • BYOK access to 15+ model providers
  • Agentic planning-then-build mode
  • AI autocomplete
  • MCP connections to external systems
  • Custom rules and live context tracking
  • Local models via Ollama/LM Studio
  • VS Code and JetBrains plugins
  • Chat inside GitHub issues and PRs
  • Task-to-implementation plans with code
  • Automatic bug-fix suggestions
  • Pull-request summaries for faster review
  • Full-codebase context
  • GitHub-native integration
  • Figma-to-code (HTML/React)
  • Clone any or private website to code
  • AI website and app builder
  • Figma agent (Buddy) and design agent
  • Anima MCP server and API
  • Adobe XD support
Use cases
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
  • Code generation, refactoring and debugging
  • Control AI spend with your own keys
  • Switch between frontier models per task
  • Keep code private and data-sovereign
  • Speeding up pull-request reviews
  • Implementing features from task descriptions
  • Debugging with AI-proposed solutions
  • Answering questions about a repo
  • Boosting a solo developer's output
  • Converting Figma designs to code
  • Cloning sites as starting points
  • Building web apps with AI
  • Automating design-to-code in dev workflows
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