toolspool

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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 saves
devActivity logo
devActivity
✓ verifiedFreemium

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

52K visits/mo
Pixels2Flutter logo
Pixels2Flutter
✓ verifiedFree

Turns UI screenshots into working Flutter code.

12K saves
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SQLAI.ai
✓ verifiedPaid

AI SQL toolkit for analysts and developers to generate, optimize, validate, format and explain queries across 30+ database engines.

26K visits/mo2.7K saves
Debugg AI logo
Debugg AI
✓ verifiedFreemium

Zero-config AI browser testing that auto-runs end-to-end tests on every GitHub PR and posts results as comments.

3.0K visits/mo6.3K saves
Pricing

No public pricing

Free: $0/contributor (up to 7 contributors, 90-day retention)
Premium: $10/contributor (unlimited contributors, AI insights)

No public pricing

Hobby: $4/mo (50 queries/month)
Starter: $6/mo (200 queries/month)
Explorer: $10/mo (1,000 queries/month)
Pro: $20/mo (3,000 queries/month)

Free trial available

Free: $0 (public repos, 100 tests/mo)
Pro: $20/mo (private repos, 1,000 tests/mo)
Grow: $40/mo (5,000 tests/mo)
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)
  • 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
  • Natural-language to SQL/NoSQL query generation
  • AI-driven query optimization with rewrite suggestions
  • Syntax validation with automated error fixes
  • Query formatting and cross-engine conversion
  • Schema-aware data source connections with autosuggest
  • Rule-based guardrails per connected data source
  • Support for large schemas with 900+ tables
  • No-config automated browser testing
  • GitHub-native PR testing with inline results
  • Fully managed cloning, build, and tunneling
  • AI app mapping and targeted test generation
  • Recorded, replayable test sessions
  • MCP server for Claude and Codex
Use cases
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
  • Automating developer performance reviews
  • Spotting delivery bottlenecks
  • Generating retrospective insights
  • Motivating teams via gamification
  • Analysts writing SQL without deep query-syntax knowledge
  • Developers debugging and optimizing slow queries
  • Teams standardizing SQL formatting across a codebase
  • Migrating queries between database engines
  • Learners wanting plain-language explanations of SQL statements
  • Catch UI regressions before merge
  • Test user flows automatically on each PR
  • Validate flows against a local dev server
  • Replace hand-written Playwright/Selenium suites
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