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GitHub

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

♥ 5.2K

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✓ verifiedFreemium

Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.

👁 775K/mo

GitLoop

✓ verifiedFree trial

AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.

👁 11K/mo♥ 2.7K

SQLAI.ai

✓ verifiedPaid

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

👁 26K/mo♥ 2.7K

Kiro AI

✓ verifiedFreemium

Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.

👁 3.8M/mo

Pricing

No public pricing

Free trial available

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/mo (50 credits)

Pro: $20/user/mo (1,000 credits)

Pro+: $40/user/mo (2,000 credits)

Pro Max: $100/user/mo (5,000 credits)

Power: $200/user/mo (10,000 credits)

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)

✦Open-source AI code assistant
✦Customizable autocomplete
✦In-editor AI chat
✦Community-built coding agent

✦Chat with your repositories
✦Natural-language codebase search
✦Fast code indexing
✦AI pull-request and commit review
✦Automated documentation generation
✦AI unit-test generation

✦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

✦Spec-driven development (requirements, design, tasks)
✦Parallel agents, local or cloud
✦Property-based and correctness testing
✦Works in IDE, CLI, web and mobile
✦Multiple models (Claude, open-weight, Auto)
✦Headless CLI for CI/CD
✦Context from tools like Figma and Terraform

Use cases

→Creating and manipulating datasets
→Training small machine learning models
→Implementing advanced training and inference logic
→Building applications that require tensor computations

→Get AI code completions while coding
→Ask questions about code in the editor
→Build on an open-source coding-agent foundation

→Onboard new developers to a codebase
→Resolve bugs faster
→Generate docs and tests automatically
→Review pull requests with AI

→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

→Turning prompts into maintainable, spec-matched code
→Catching bugs unit tests miss
→Reviewing PRs and fixing bugs in CI/CD

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