[{"data":1,"prerenderedAt":808},["ShallowReactive",2],{"categories-init":3,"stack-kiro-dev-stack":4,"stack-res-kiro-dev-stack":807},true,{"stack_id":5,"slug":6,"name":7,"tagline":8,"long_description":9,"key_features":10,"use_cases":18,"pros":24,"cons":30,"cover_image_url":36,"scores":37,"options":51,"additions":359,"addition_groups":638,"option_groups":654,"multi_select_option_types":655,"tools_by_category":656,"related_stacks":708,"faqs":763,"pricing":779,"system_requirements":36,"experience_level":802,"project_type":36,"stack_type_slug":715,"stack_type_icon_url":716,"published_date":434,"last_updated_date":36,"seo_meta":803},252,"kiro-dev-stack","Kiro Dev Stack","AWS's spec-driven IDE, planning features before the agent codes, on Claude, GPT, or open-weight models.","Kiro is AWS's agentic IDE, built on VS Code's open-source core, and its agent is part of the editor rather than a plugin. What sets it apart is **spec-driven development**: for a feature, the agent first writes the requirements as user stories with acceptance criteria, then a technical design, then a task list, each saved as a file in the repository and approved before the next step. It then works through the tasks, running independent ones in parallel. Smaller changes skip the plan and go through chat, with every edit shown as a diff and checkpoints to roll back. Steering files hold the project's rules, hooks run the agent when files change, and powers load MCP servers and skills when a task needs them.\n\nModels come from Kiro's own picker and are paid for in **Kiro credits**, with no separate API keys. Claude is the default here and the family Kiro leads with; OpenAI's GPT-5.6 models sit beside it for demanding work, and open-weight models from DeepSeek, Qwen, GLM, and MiniMax cost a fraction of the credits for routine tasks. An Auto setting picks a model per request. The free plan covers the open-weight models and one Claude Sonnet model, and the paid plans add the rest.\n\nKiro runs on your own computer by default, which has to stay on while the agent works there. For work that should continue with the laptop closed, paid plans add **cloud sessions**: the same agent runs in an isolated sandbox in Kiro's cloud against a GitHub or GitLab repository and opens a pull request when it's done. A session can start in the IDE, the Kiro CLI, or Kiro Web in a browser, and be picked up from any of them, or from an iOS app that's still in early access. Developers who prefer their own hardware can run the Kiro CLI headless on a server.\n\nGitHub is the default for version control, with GitLab supported in cloud sessions too. Claude Code, Codex, or OpenCode can optionally run beside Kiro's agent, and an AI code reviewer, CI\u002FCD, and Docker are common additions.",[11,12,13,14,15,16,17],"Feature specs that write requirements, a design, and a task list as files in the repository before any code","Bugfix specs that diagnose a defect before the agent edits anything","Claude by default, with GPT-5.6 and open-weight DeepSeek, Qwen, GLM, and MiniMax models in one picker","Cloud sessions that keep working in a sandbox with the laptop closed and open a pull request","The same agent and .kiro configuration in the IDE, the Kiro CLI, and Kiro Web","Steering files, agent hooks, and powers that bundle MCP servers and skills","Open VSX extensions and imported VS Code settings, so an existing setup carries over",[19,20,21,22,23],"Planning a multi-file feature as reviewable requirements and a design before the agent writes code","Giving reviewers the spec files alongside the pull request so they can check the code against the plan","Handing a task to a cloud session at the end of the day and reviewing the pull request in the morning","Stretching monthly credits by running routine edits on an open-weight model and hard ones on Claude","Diagnosing a production bug with a bugfix spec before any code changes",[25,26,27,28,29],"Specs put the plan in writing, so a large change can be checked before code exists","One subscription covers Claude, GPT, and open-weight models, with no API keys to manage","Cloud sessions on GitHub or GitLab, started from the editor, the terminal, or a browser","Low-multiplier open-weight models make routine work cheap within the plan's credits","Built on VS Code's core, so settings and most extensions carry over",[31,32,33,34,35],"Credit use per request varies with the model and the task, so monthly cost is hard to predict","The free plan's 50 credits cover only a few real sessions, and cloud sessions need a paid plan","Writing a spec costs time and credits that a small fix doesn't need","Extensions come from Open VSX, which lacks some Microsoft ones such as the official Remote SSH and Pylance","A separate agent like Claude Code or Codex needs its own subscription on top of Kiro's",null,{"popularity":38,"learning_curve":41,"flexibility":44,"performance":47,"portability":49},{"score":39,"reasoning":40},3,"AWS backing and a broad set of surfaces make Kiro a well-known name among AI IDEs, though its user base trails Cursor and VS Code.",{"score":42,"reasoning":43},2,"Anyone who has used VS Code can work in chat on day one; writing and approving specs, steering files, and hooks is a workflow that takes a few projects to get right.",{"score":45,"reasoning":46},4,"Six model families in one picker, Open VSX extensions, MCP, hooks, and powers, plus optional third-party agents, within a closed-source editor whose models are reached only through Kiro's credits.",{"score":45,"reasoning":48},"Parallel task waves and cloud sessions move long work off the local machine, though spec generation adds steps before any code appears and results track the chosen model.",{"score":39,"reasoning":50},"Projects stay plain files and git history, and the specs are Markdown any agent can read, but models, credits, and cloud sessions are tied to a Kiro account.",{"agent_framework":52,"vector_db":56,"database":60,"orm":64,"authentication":68,"analytics":72,"model_inference":76,"coding_agent":80,"llm":84,"language":273,"frontend_framework":277,"cms":281,"hosting":285,"reverse_proxy":289,"self_hosted_paas":293,"version_control":297},{"name":36,"tools":53,"descriptions":54,"aliases":55,"see_all":36},[],{},{},{"name":36,"tools":57,"descriptions":58,"aliases":59,"see_all":36},[],{},{},{"name":36,"tools":61,"descriptions":62,"aliases":63,"see_all":36},[],{},{},{"name":36,"tools":65,"descriptions":66,"aliases":67,"see_all":36},[],{},{},{"name":36,"tools":69,"descriptions":70,"aliases":71,"see_all":36},[],{},{},{"name":36,"tools":73,"descriptions":74,"aliases":75,"see_all":36},[],{},{},{"name":36,"tools":77,"descriptions":78,"aliases":79,"see_all":36},[],{},{},{"name":36,"tools":81,"descriptions":82,"aliases":83,"see_all":36},[],{},{},{"name":85,"tools":86,"descriptions":262,"aliases":269,"see_all":270},"LLM",[87,127,149,186,209,232],{"tool_id":88,"name":89,"slug":90,"tooltip_description":91,"logo_url":92,"logo_bg":93,"pricing_model":94,"learning_curve_score":42,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":100,"subcategory":103,"categories":107,"subcategories":110,"flexibility_score":45,"performance_score":98,"portability_score":39,"is_featured":112,"tags":113,"score_reasonings":119,"published_date":125,"last_updated_date":126},153,"Claude","claude","Anthropic's family of AI models, from fast Haiku to frontier Fable, available through the Claude API, Amazon Bedrock, Google Vertex AI, Microsoft Foundry, and claude.ai, known for long context, tool use, and adaptive thinking.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fclaude.svg","dark",{"slug":95,"display_name":96,"description":97},"usage_based","Usage-Based","Pricing scales with consumption: API calls, data volume, compute time, or similar metered units.",5,"open",{"category_id":101,"name":85,"slug":102},19,"llm",{"subcategory_id":104,"name":105,"slug":106},51,"Proprietary","proprietary",[108],{"category_id":101,"name":85,"slug":102,"is_primary":3,"display_order":109},0,[111],{"subcategory_id":104,"name":105,"slug":106,"category_id":101,"is_primary":3,"display_order":109},false,[114],{"tag_id":115,"name":116,"slug":117,"tag_type":118},40,"Web","web","platform",{"learning_curve":120,"flexibility":121,"performance":122,"popularity":123,"portability":124},"The Anthropic API follows the standard messages array pattern familiar from other LLM providers. Python and TypeScript SDKs are well-documented. Basic integration takes under an hour.","Supports tool use, vision, extended thinking, prompt caching, batch processing, streaming, and system prompts. No fine-tuning and no image output limits the ceiling. Multi-cloud availability adds operational flexibility.","Claude 4 Opus and Sonnet 4 are at the frontier of reasoning and coding benchmarks as of 2025. Extended thinking mode significantly improves accuracy on hard problems. Competitive with GPT-4o and Gemini Ultra across most evaluation suites.","Claude is one of the two or three most-referenced LLMs in developer communities worldwide. Massive adoption via Claude.ai, API, Bedrock, and Vertex AI. Powers Claude Code, Cursor (optional model), and many third-party AI products.","Anthropic API uses its own message format and tool-calling schema — not OpenAI-compatible. Migrating to\u002Ffrom Claude requires prompt and schema rewrites. Available on Bedrock and Vertex AI reduces infrastructure lock-in but does not eliminate model lock-in.","2026-05-29","2026-10-02",{"tool_id":128,"name":129,"slug":130,"tooltip_description":131,"logo_url":132,"logo_bg":133,"pricing_model":134,"learning_curve_score":42,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":135,"subcategory":136,"categories":137,"subcategories":139,"flexibility_score":39,"performance_score":98,"portability_score":42,"is_featured":112,"tags":141,"score_reasonings":143,"published_date":125,"last_updated_date":126},155,"OpenAI","openai","OpenAI's API platform for the GPT-6 family (Astra, Sol, Luna), plus real-time voice, image generation, transcription, and embeddings, with built-in tools, structured outputs, and agent-building APIs.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fopenai.svg","white",{"slug":95,"display_name":96,"description":97},{"category_id":101,"name":85,"slug":102},{"subcategory_id":104,"name":105,"slug":106},[138],{"category_id":101,"name":85,"slug":102,"is_primary":3,"display_order":109},[140],{"subcategory_id":104,"name":105,"slug":106,"category_id":101,"is_primary":3,"display_order":109},[142],{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"performance":144,"popularity":145,"portability":146,"learning_curve":147,"flexibility":148},"Leads or co-leads industry benchmarks across coding (SWE-bench), reasoning (MATH, GPQA), and instruction-following. o3 and GPT-5 are best-in-class for their respective task types as of 2026.","The most-used LLM API in the world by developer count, third-party integrations, and mindshare. ChatGPT's cultural reach directly drives API adoption. Virtually every developer tool, no-code platform, and enterprise software suite lists OpenAI as a primary integration.","Entirely cloud-bound; no self-hosted option. The API is proprietary — migrating to a different provider requires rewriting prompt logic, tool schemas, and API call structure. Azure and Bedrock availability reduces cloud lock-in but not provider lock-in.","The Chat Completions API is one of the most beginner-friendly interfaces in software — a single POST request with a messages array returns a completion. Official SDKs for Python and Node ship with comprehensive docs and hundreds of cookbook examples. The main learning curve is choosing the right model family and managing costs rather than the API mechanics themselves.","OpenAI offers genuine breadth — five model families, fine-tuning (supervised + reinforcement), function calling, structured outputs, and real-time audio. However, all inference is cloud-only and proprietary; you cannot swap the underlying model weights, run locally, or choose your hardware. Compared to open-weight alternatives, customisation stops at fine-tuning.",{"tool_id":150,"name":151,"slug":152,"tooltip_description":153,"logo_url":154,"logo_bg":93,"pricing_model":155,"learning_curve_score":39,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":159,"subcategory":160,"categories":164,"subcategories":166,"flexibility_score":98,"performance_score":98,"portability_score":98,"is_featured":112,"tags":168,"score_reasonings":179,"published_date":125,"last_updated_date":185},161,"DeepSeek","deepseek","Chinese open-weight LLM family under the MIT license, led by DeepSeek-V4.1-Flash, offering frontier-level results at very low API prices, with full self-hosting through vLLM, SGLang, and Ollama.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fdeepseek.svg",{"slug":156,"display_name":157,"description":158},"freemium","Freemium","A free tier is available; additional features, usage limits, or managed hosting require a paid plan.",{"category_id":101,"name":85,"slug":102},{"subcategory_id":161,"name":162,"slug":163},52,"Open-weight","open-weight",[165],{"category_id":101,"name":85,"slug":102,"is_primary":3,"display_order":109},[167],{"subcategory_id":161,"name":162,"slug":163,"category_id":101,"is_primary":3,"display_order":109},[169,174,178],{"tag_id":170,"name":171,"slug":172,"tag_type":173},11,"Open Source","open-source","feature",{"tag_id":175,"name":176,"slug":177,"tag_type":173},12,"Self-hostable","self-hostable",{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":180,"popularity":181,"portability":182,"flexibility":183,"performance":184},"The DeepSeek API (OpenAI-compatible) is trivial to call for developers already using OpenAI. Running distilled models via Ollama is also beginner-friendly. The steep part is self-hosting the full 671B V3\u002FR1 models — that requires multi-GPU infrastructure, tensor parallelism configuration in vLLM, and knowledge of quantisation trade-offs.","One of the fastest open-source repository growth stories in GitHub history. DeepSeek-R1 reached ~92K stars within weeks; total deepseek-ai org stars exceeded 170K by end of 2025. Massive developer adoption, significant industry impact, and strong Hugging Face download counts.","MIT license, Hugging Face weights, Ollama\u002FvLLM\u002FLM Studio support, and availability on Amazon Bedrock, Fireworks, Together AI, and OpenRouter. No lock-in whatsoever.","Open MIT weights with no use restrictions, publishable on any infrastructure, fine-tuneable with standard tools, and accessible via multiple APIs (direct, Bedrock, Together AI, Fireworks). Maximum possible flexibility for an LLM.","DeepSeek-V3 and R1 match or exceed GPT-4o on coding (HumanEval, SWE-bench), math (AIME, MATH-500), and reasoning benchmarks. R1 matches OpenAI o1. V4-Pro (2026) rivals the world's top closed models. Exceptional especially on coding tasks.","2026-09-27",{"tool_id":187,"name":188,"slug":189,"tooltip_description":190,"logo_url":191,"logo_bg":93,"pricing_model":192,"learning_curve_score":42,"popularity_score":45,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":193,"subcategory":194,"categories":195,"subcategories":197,"flexibility_score":98,"performance_score":98,"portability_score":98,"is_featured":112,"tags":199,"score_reasonings":203,"published_date":125,"last_updated_date":185},162,"Qwen","qwen","Alibaba's LLM family, from sub-1B models to a 2.4-trillion-parameter flagship, covering reasoning, coding, vision, and long context, mostly under Apache 2.0 open weights with a hosted API on Alibaba Cloud.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fqwen.svg",{"slug":156,"display_name":157,"description":158},{"category_id":101,"name":85,"slug":102},{"subcategory_id":161,"name":162,"slug":163},[196],{"category_id":101,"name":85,"slug":102,"is_primary":3,"display_order":109},[198],{"subcategory_id":161,"name":162,"slug":163,"category_id":101,"is_primary":3,"display_order":109},[200,201,202],{"tag_id":170,"name":171,"slug":172,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"tag_id":175,"name":176,"slug":177,"tag_type":173},{"learning_curve":204,"flexibility":205,"performance":206,"popularity":207,"portability":208},"Open weights + OpenAI-compatible API means onboarding is straightforward for any developer familiar with the OpenAI SDK. Ollama makes local inference a one-command setup. Navigating the large model family and choosing the right variant adds some complexity, but the barrier is low overall.","Apache 2.0 licence, sizes from 0.6B to 480B+, dense and MoE architectures, specialised coding and vision variants, toggleable reasoning mode, and multiple access paths (self-hosted, DashScope, third-party APIs). Maximum flexibility for any use case.","Qwen3-Coder ranks among the very best open-weight coding models; Qwen3 MoE variants compete with GPT-4-class models on benchmarks; QwQ-32B rivals leading reasoning specialists; Qwen-VL leads vision-language open-weight benchmarks. Across all domains, Qwen is at or near the open-weight frontier.","Qwen3 repo has ~27K GitHub stars; Qwen3-Coder ~16K; QwenLM org collectively has tens of thousands of stars across repositories. Dominant in Chinese AI ecosystem and rapidly growing global adoption. Strong presence on Hugging Face, Ollama library, and all major inference providers.","Apache 2.0 weights on Hugging Face run on Ollama, vLLM, llama.cpp, LM Studio, and MLX with no licence restrictions. Same models available via DashScope and third-party APIs. Maximum portability — switch providers or go self-hosted any time.",{"tool_id":210,"name":211,"slug":212,"tooltip_description":213,"logo_url":214,"logo_bg":93,"pricing_model":215,"learning_curve_score":39,"popularity_score":39,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":216,"subcategory":217,"categories":218,"subcategories":220,"flexibility_score":45,"performance_score":45,"portability_score":45,"is_featured":112,"tags":222,"score_reasonings":226,"published_date":125,"last_updated_date":185},157,"GLM","glm","GLM is Z.ai's (formerly Zhipu AI) family of bilingual Chinese and English LLMs, with open weights on Hugging Face, an OpenAI-compatible API with free Flash models, and a flat-rate GLM Coding Plan for coding agents.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fglm.png",{"slug":156,"display_name":157,"description":158},{"category_id":101,"name":85,"slug":102},{"subcategory_id":161,"name":162,"slug":163},[219],{"category_id":101,"name":85,"slug":102,"is_primary":3,"display_order":109},[221],{"subcategory_id":161,"name":162,"slug":163,"category_id":101,"is_primary":3,"display_order":109},[223,224,225],{"tag_id":170,"name":171,"slug":172,"tag_type":173},{"tag_id":175,"name":176,"slug":177,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":227,"flexibility":228,"performance":229,"popularity":230,"portability":231},"The OpenAI-compatible API at open.bigmodel.cn is easy to adopt for any developer familiar with OpenAI. Ollama support (`ollama run glm-4.7`) makes local inference a one-command setup. The difficulty is in navigating the sprawling model family — GLM-4, GLM-4.5, GLM-4.6, GLM-4.7, GLM-Z1, GLM-5 — and the fact that much documentation is in Chinese first.","Apache 2.0 open weights for all major variants, multiple size options (9B to 32B self-hosted; up to 744B via API), reasoning-specialist (Z1), vision (GLM-4V), and all-tools variants, plus the managed API. Solid flexibility, though fewer self-hostable sizes above 32B and less third-party cloud availability than DeepSeek or Qwen.","GLM-4 All Tools benchmarks favourably against GPT-4 All Tools; GLM-Z1 reasoning models are strong at 32B; GLM-5.1 reportedly matched GPT-5.4 on coding benchmarks. However, independent Western benchmark coverage is sparser than for DeepSeek or Qwen, and the largest frontier models are proprietary.","ChatGLM-6B repo has 41k+ GitHub stars, making it one of the most-starred Chinese LLM repos. However, globally GLM has lower mindshare than DeepSeek (92k+ stars on R1) or Qwen. Dominant within the Chinese developer community; growing but limited international adoption.","Apache 2.0 weights on Hugging Face under zai-org\u002F, supported by Ollama, vLLM, SGLang, GGUF\u002Fllama.cpp — solid portability for the open-weight sizes. However, no major Western managed cloud (Bedrock, Azure) support as of mid-2026, and the frontier models are API-only with China-hosted infrastructure.",{"tool_id":233,"name":234,"slug":235,"tooltip_description":236,"logo_url":237,"logo_bg":93,"pricing_model":238,"learning_curve_score":39,"popularity_score":39,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":239,"subcategory":240,"categories":241,"subcategories":243,"flexibility_score":45,"performance_score":98,"portability_score":45,"is_featured":112,"tags":245,"score_reasonings":256,"published_date":185,"last_updated_date":36},212,"MiniMax","minimax","MiniMax is a Chinese AI lab whose M3 open-weight model offers a 1M-token context, native multimodal input, and strong agentic coding, available as self-hosted weights, a low-cost API, and a Token Plan subscription.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fminimax.svg",{"slug":156,"display_name":157,"description":158},{"category_id":101,"name":85,"slug":102},{"subcategory_id":161,"name":162,"slug":163},[242],{"category_id":101,"name":85,"slug":102,"is_primary":3,"display_order":109},[244],{"subcategory_id":161,"name":162,"slug":163,"category_id":101,"is_primary":3,"display_order":109},[246,247,251,255],{"tag_id":175,"name":176,"slug":177,"tag_type":173},{"tag_id":248,"name":249,"slug":250,"tag_type":173},13,"Free Tier","free-tier",{"tag_id":252,"name":253,"slug":254,"tag_type":173},16,"AI-powered","ai-powered",{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":257,"flexibility":258,"performance":259,"popularity":260,"portability":261},"Using the hosted API is as simple as any OpenAI-compatible endpoint, while self-hosting via vLLM\u002FSGLang or GGUF quantization requires the same infrastructure familiarity as any other large open-weight model.","Deployable via a hosted API, self-hosted through vLLM\u002FSGLang, or run locally through GGUF quantizations on llama.cpp\u002FOllama\u002FLM Studio, with native multimodal input across text, image, audio, and video.","Leads the August 2026 open-weight intelligence-index ranking and scores 69.4% on SWE-Bench Verified for the M2 line, on par with proprietary frontier models on coding tasks specifically.","A fast-iterating model line (M2 through M3 within 2026) with growing recognition, but still behind the Western developer mindshare of more established open-weight labs like DeepSeek and Qwen.","Self-hostable via vLLM\u002FSGLang and widely available as GGUF quantizations, though the custom minimax-community license is a real consideration for portability compared to a fully permissive MIT\u002FApache license.",{"claude":263,"openai":264,"deepseek":265,"qwen":266,"glm":267,"minimax":268},"Claude is the default here and the family Kiro leads with. Sonnet 5.5 costs 1.3 times the Auto rate in credits and suits most spec and chat work; Opus 5.5 at 2 times takes the hardest multi-file changes, and Haiku 4.5 at 0.4 times quick edits. The free plan includes Claude Sonnet 4.5.","OpenAI's GPT-5.6 family sits in the same picker on paid plans, billed in Kiro credits: Sol at 4.4 times the Auto rate for the most demanding work, Terra at 2.2 times as a balanced pick, and Luna at 0.6 times for fast, cheap edits. Useful as a second opinion when Claude gets stuck on a task.","DeepSeek 3.2 runs at a quarter of the Auto rate in credits, on the free plan as well as the paid ones, which makes it a cheap choice for routine edits, tests, and refactors while a Claude or GPT model handles the planning and the harder spec tasks.","Qwen3 Coder Next is the cheapest model in Kiro's picker at 0.05 times the Auto rate, open-weight and tuned for coding. It stretches a small plan, or the free plan's 50 credits, furthest on simple, well-scoped tasks, though it trails Claude on long multi-file changes.","GLM-5 from Z.ai runs at half the Auto rate in credits, an open-weight model with strong agentic coding results that sits between the budget models and Claude in price. Available on the free plan, and a reasonable default for teams watching credits closely.","MiniMax M2.5 runs at a quarter of the Auto rate, and the older M2.1 at 0.15 times, both open-weight models built for agentic coding and tool use. A low-cost pick for long task lists in a spec, where many steps are routine and credits add up.",{},{"kind":271,"slug":102,"name":85,"href":272},"category","\u002Ftools\u002Fcategories\u002Fllm",{"name":36,"tools":274,"descriptions":275,"aliases":276,"see_all":36},[],{},{},{"name":36,"tools":278,"descriptions":279,"aliases":280,"see_all":36},[],{},{},{"name":36,"tools":282,"descriptions":283,"aliases":284,"see_all":36},[],{},{},{"name":36,"tools":286,"descriptions":287,"aliases":288,"see_all":36},[],{},{},{"name":36,"tools":290,"descriptions":291,"aliases":292,"see_all":36},[],{},{},{"name":36,"tools":294,"descriptions":295,"aliases":296,"see_all":36},[],{},{},{"name":298,"tools":299,"descriptions":355,"aliases":358,"see_all":36},"Version Control",[300,332],{"tool_id":301,"name":302,"slug":303,"tooltip_description":304,"logo_url":305,"logo_bg":133,"pricing_model":306,"learning_curve_score":39,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":307,"subcategory":311,"categories":314,"subcategories":316,"flexibility_score":45,"performance_score":39,"portability_score":42,"is_featured":112,"tags":318,"score_reasonings":326,"published_date":125,"last_updated_date":185},151,"GitHub","github","The largest Git hosting platform, where well over 100 million developers collaborate, review code, and manage projects through pull requests, issues, and a large integration ecosystem.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fgithub.svg",{"slug":156,"display_name":157,"description":158},{"category_id":308,"name":309,"slug":310},8,"Development Tools","development-tools",{"subcategory_id":312,"name":298,"slug":313},50,"version-control",[315],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[317],{"subcategory_id":312,"name":298,"slug":313,"category_id":308,"is_primary":3,"display_order":109},[319,324,325],{"tag_id":320,"name":321,"slug":322,"tag_type":323},36,"CI\u002FCD","ci-cd","use_case",{"tag_id":248,"name":249,"slug":250,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":327,"flexibility":328,"performance":329,"popularity":330,"portability":331},"GitHub's UI is intuitive, but mastering Git concepts (rebasing, merge conflicts, branching strategies) and collaborative pull request workflows takes meaningful time — rated moderate difficulty.","Highly customisable branch protection, review policies, webhooks, and an extensive API\u002Fapp ecosystem. Some advanced governance features are gated behind paid tiers.","Generally reliable with 99.9% SLA for Enterprise, but the platform experienced capacity-related reliability incidents in 2025–2026 driven by AI agent traffic, pulling uptime below target.","Dominant market leader with ~70% SCM market share, 180M+ registered developers, 92% adoption among Fortune 100 companies. Effectively the industry default.","High vendor lock-in: GitHub Actions workflows, Projects, Packages, and Advanced Security are proprietary. Migrating a Git repo is easy; migrating the full workflow is not.",{"tool_id":333,"name":334,"slug":335,"tooltip_description":336,"logo_url":337,"logo_bg":133,"pricing_model":338,"learning_curve_score":42,"popularity_score":45,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":339,"subcategory":340,"categories":341,"subcategories":343,"flexibility_score":98,"performance_score":39,"portability_score":98,"is_featured":112,"tags":345,"score_reasonings":349,"published_date":125,"last_updated_date":185},152,"GitLab","gitlab","An open-source, all-in-one DevSecOps platform offering Git hosting, code review, issue tracking, and built-in CI\u002FCD — available as a SaaS service or fully self-hosted.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fgitlab.svg",{"slug":156,"display_name":157,"description":158},{"category_id":308,"name":309,"slug":310},{"subcategory_id":312,"name":298,"slug":313},[342],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[344],{"subcategory_id":312,"name":298,"slug":313,"category_id":308,"is_primary":3,"display_order":109},[346,347,348],{"tag_id":248,"name":249,"slug":250,"tag_type":173},{"tag_id":175,"name":176,"slug":177,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":350,"flexibility":351,"performance":352,"popularity":353,"portability":354},"Feature breadth is GitLab's biggest onboarding challenge — new users face pipelines, boards, security dashboards, and compliance tools all at once. Rated steep.","Highly flexible: customisable CI\u002FCD pipelines, branch protection, merge request approvals, REST\u002FGraphQL APIs, and full self-hosting. One of the most configurable platforms in its class.","Cloud performance is solid but not best-in-class; complex pipelines and large self-hosted deployments can lag. Rated average for its category.","16% SCM market share — firmly the second-largest platform globally, Gartner Magic Quadrant leader for DevOps, but well behind GitHub's ~70% dominance.","Open-source MIT licence with fully self-hostable CE and FOSS mirror. No vendor lock-in — highest portability score in its category.",{"github":356,"gitlab":357},"GitHub is the default here, where most repositories and AI reviewers already live. Kiro's cloud sessions clone a GitHub repository, work on a branch, and open a pull request, and they can start from an issue as well as from a prompt.","GitLab bundles source control, merge requests, and CI\u002FCD in one platform you can self-host. Kiro's cloud sessions connect to GitLab projects with a personal access token and open merge requests, and one session can change repositories on GitHub and GitLab together.",{},{"coding_agent":360,"code_review":444,"ci_cd":526,"containerization":599},{"name":361,"tools":362,"descriptions":435,"aliases":439,"preface":440,"see_all":441},"Coding Agent",[363,389,411],{"tool_id":252,"name":364,"slug":365,"tooltip_description":366,"logo_url":92,"logo_bg":93,"pricing_model":367,"learning_curve_score":39,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":371,"subcategory":372,"categories":376,"subcategories":378,"flexibility_score":98,"performance_score":45,"portability_score":45,"is_featured":112,"tags":380,"score_reasonings":382,"published_date":125,"last_updated_date":388},"Claude Code","claude-code","Claude Code is Anthropic's agentic coding tool that runs in your terminal and IDEs, reads your entire codebase, edits files, runs commands, and handles git workflows through natural language. It supports multi-agent orchestration, MCP integrations, and custom automation via CLAUDE.md and hooks.",{"slug":368,"display_name":369,"description":370},"paid","Paid","No meaningful free tier — a subscription or one-time purchase is required to use the tool.",{"category_id":308,"name":309,"slug":310},{"subcategory_id":373,"name":374,"slug":375},49,"AI Coding Agents","ai-coding-agents",[377],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[379],{"subcategory_id":373,"name":374,"slug":375,"category_id":308,"is_primary":3,"display_order":109},[381],{"tag_id":252,"name":253,"slug":254,"tag_type":173},{"learning_curve":383,"performance":384,"flexibility":385,"portability":386,"popularity":387},"Agentic CLI workflow is new for most developers; hooks, context, and permissions take time.","Lightweight terminal CLI; very responsive with no significant overhead beyond API latency.","Hooks, custom slash commands, MCP servers, and the Agent SDK provide deep extensibility.","CLI tool with standard terminal workflow; hooks and commands are reasonably portable.","The most widely discussed AI coding agent as of 2025\u002F2026; very high developer mindshare.","2026-09-30",{"tool_id":390,"name":391,"slug":392,"tooltip_description":393,"logo_url":394,"logo_bg":93,"pricing_model":395,"learning_curve_score":39,"popularity_score":45,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":396,"subcategory":397,"categories":398,"subcategories":400,"flexibility_score":39,"performance_score":98,"portability_score":42,"is_featured":112,"tags":402,"score_reasonings":405,"published_date":125,"last_updated_date":388},150,"Codex","codex","OpenAI's AI coding agent that builds features, fixes bugs, reviews code, and runs tests, either in cloud sandboxes or locally, through ChatGPT, an open-source CLI, a desktop app, and IDE extensions.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fcodex.svg",{"slug":156,"display_name":157,"description":158},{"category_id":308,"name":309,"slug":310},{"subcategory_id":373,"name":374,"slug":375},[399],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[401],{"subcategory_id":373,"name":374,"slug":375,"category_id":308,"is_primary":3,"display_order":109},[403,404],{"tag_id":248,"name":249,"slug":250,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":406,"flexibility":407,"performance":408,"popularity":409,"portability":410},"Basic task creation via natural language is straightforward, but designing effective multi-step agent workflows, debugging sandbox failures, and managing parallel task coordination requires real practice. Score 3.","Cloud-first architecture limits self-hosting; task environments can be customised via setup scripts and env vars, but core agent behaviour is proprietary and not deeply configurable. Score 3.","Powered by codex-1 (o3-based), which leads SWE-bench and real-world coding benchmarks. Parallel execution eliminates sequential bottlenecks. Best-in-class for agentic coding tasks as of 2026. Score 5.","67K GitHub stars on the open-source Codex CLI within its first year; reported 2M+ weekly active users across ChatGPT plans. Strong enterprise adoption but newer than incumbents like Cursor. Score 4.","Task execution is entirely cloud-bound on OpenAI infrastructure. Generated code and PR diffs are portable, but the agent itself cannot be self-hosted or migrated to another provider. Score 2.",{"tool_id":412,"name":413,"slug":414,"tooltip_description":415,"logo_url":416,"logo_bg":133,"pricing_model":417,"learning_curve_score":39,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":418,"subcategory":419,"categories":420,"subcategories":422,"flexibility_score":98,"performance_score":45,"portability_score":98,"is_featured":112,"tags":424,"score_reasonings":428,"published_date":185,"last_updated_date":434},192,"OpenCode","opencode","Open-source, model-agnostic AI coding agent for the terminal, desktop, and IDE, built by Anomaly. Connects to 75+ providers or your existing Copilot or ChatGPT subscription, with no lock-in to one model vendor.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fopencode.svg",{"slug":156,"display_name":157,"description":158},{"category_id":308,"name":309,"slug":310},{"subcategory_id":373,"name":374,"slug":375},[421],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[423],{"subcategory_id":373,"name":374,"slug":375,"category_id":308,"is_primary":3,"display_order":109},[425,426,427],{"tag_id":170,"name":171,"slug":172,"tag_type":173},{"tag_id":248,"name":249,"slug":250,"tag_type":173},{"tag_id":252,"name":253,"slug":254,"tag_type":173},{"learning_curve":429,"flexibility":430,"performance":431,"popularity":432,"portability":433},"Getting a first session running is a quick `npm install` plus an API key, but making full use of Build\u002FPlan modes, MCP\u002FLSP integration, and choosing among 75+ providers involves more configuration surface than a single-model vendor tool.","Bring-your-own-model architecture, custom tools and plugins, configurable permissions\u002Fkeybinds\u002Fformatters, and MCP\u002FLSP support give it wide-open extensibility with essentially no imposed workflow.","Output quality tracks whichever underlying model is configured rather than a fixed baseline — with a strong model (e.g. Claude or GPT) selected, it performs competitively with leading vendor agents, but there's no single benchmark number the way there is for a single-model product.","Roughly 198K GitHub stars and 900+ contributors as of mid-2026, reported 7.5M+ monthly users — the most-starred project in the open-source AI coding agent space, ahead of every other independent (non-vendor) entrant.","MIT-licensed, installable via npm\u002FHomebrew\u002FDocker, no code stored on OpenCode's servers, and not tied to any single model provider — among the least locked-in options in the subcategory.","2026-10-12",{"claude-code":436,"codex":437,"opencode":438},"Add Claude Code when you want Anthropic's agent on a task beside Kiro's: its official extension is published on Open VSX, so it installs in Kiro's sidebar, or the CLI runs in the integrated terminal. It needs its own Claude plan, from $20\u002Fmo, since Kiro's credits don't cover it.","Add Codex when you want OpenAI's agent alongside Kiro's: the official Codex extension installs from Open VSX, and it runs on a ChatGPT plan you may already have, including the free tier. Kiro's spec files are plain Markdown, so Codex can read them as context too.","Add OpenCode in Kiro's integrated terminal when you want an open-source agent that runs any provider's model with your own API key, or a local model, outside Kiro's credit system.",{},"Add a separate coding agent when you want another vendor's agent working alongside the one built into the editor, either through its own extension or in the integrated terminal.",{"kind":442,"slug":375,"name":374,"href":443},"subcategory","\u002Ftools\u002Fcategories\u002Fdevelopment-tools\u002Fai-coding-agents",{"name":445,"tools":446,"descriptions":520,"aliases":524,"preface":525,"see_all":36},"Code Review",[447,474,498],{"tool_id":448,"name":449,"slug":450,"tooltip_description":451,"logo_url":452,"logo_bg":93,"pricing_model":453,"learning_curve_score":454,"popularity_score":45,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":455,"subcategory":456,"categories":460,"subcategories":462,"flexibility_score":45,"performance_score":39,"portability_score":39,"is_featured":112,"tags":464,"score_reasonings":468,"published_date":185,"last_updated_date":36},284,"CodeRabbit","coderabbit","AI code reviewer that comments on every pull request in GitHub, GitLab, Bitbucket, and Azure DevOps, combining language-model review with more than 40 static analyzers. The same reviews also run in IDE extensions and a CLI.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fcoderabbit.svg",{"slug":156,"display_name":157,"description":158},1,{"category_id":308,"name":309,"slug":310},{"subcategory_id":457,"name":458,"slug":459},73,"AI Code Review","ai-code-review",[461],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[463],{"subcategory_id":457,"name":458,"slug":459,"category_id":308,"is_primary":3,"display_order":109},[465,466,467],{"tag_id":248,"name":249,"slug":250,"tag_type":173},{"tag_id":252,"name":253,"slug":254,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"flexibility":469,"learning_curve":470,"performance":471,"popularity":472,"portability":473},"Path-specific instructions, learnings from PR replies, custom pre-merge checks, and four Git hosts plus IDE and CLI surfaces give teams a lot of control over what gets reviewed and how. The underlying models are chosen by CodeRabbit, not the user.","Setup is installing a Git app and picking repositories; the first review arrives on the next pull request with no configuration. The YAML config and path instructions are optional refinements.","Reviews arrive within minutes and PR summaries are widely praised, but independent bug-catch benchmarks put its detection rate well behind Greptile and some other reviewers, and noisy comments are a common complaint.","The most-installed AI app on the GitHub Marketplace, with over two million connected repositories, more than 17,000 customers, and a $1.5B valuation. Well known among developers who work with pull requests, though AI code review is still a young category many developers have not adopted.","Works across GitHub, GitLab, Bitbucket, and Azure DevOps and sits outside the codebase, so switching reviewers is an app uninstall. It is a hosted SaaS, and learnings and configuration do not carry over to other tools.",{"tool_id":475,"name":476,"slug":477,"tooltip_description":478,"logo_url":479,"logo_bg":93,"pricing_model":480,"learning_curve_score":42,"popularity_score":39,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":481,"subcategory":482,"categories":483,"subcategories":485,"flexibility_score":45,"performance_score":45,"portability_score":45,"is_featured":112,"tags":487,"score_reasonings":492,"published_date":185,"last_updated_date":36},285,"Greptile","greptile","AI code reviewer that indexes the whole repository into a code graph and uses it to review pull requests, catching bugs that span several files. Supports GitHub, GitLab, and Bitbucket, with self-hosting on Enterprise.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fgreptile.png",{"slug":156,"display_name":157,"description":158},{"category_id":308,"name":309,"slug":310},{"subcategory_id":457,"name":458,"slug":459},[484],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[486],{"subcategory_id":457,"name":458,"slug":459,"category_id":308,"is_primary":3,"display_order":109},[488,489,490,491],{"tag_id":175,"name":176,"slug":177,"tag_type":173},{"tag_id":248,"name":249,"slug":250,"tag_type":173},{"tag_id":252,"name":253,"slug":254,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":493,"flexibility":494,"performance":495,"popularity":496,"portability":497},"Connecting a Git host and indexing a repository is quick, but getting the most out of it means writing custom rules and understanding the credit model and when a TREX review is worth three credits.","Plain-language custom rules, a choice of standard or execution-backed reviews, an API, and on Enterprise a bring-your-own-model option give teams real control over how reviews run.","Independent comparisons put its raw bug-catch rate at the top of the mainstream AI reviewers, driven by the codebase graph, and TREX adds execution evidence that static reading cannot produce.","Well regarded among teams evaluating AI code review, with more than 2,000 customers and Benchmark backing, but far less widely known than CodeRabbit and largely unknown to developers outside that decision.","Supports GitHub, GitLab, and Bitbucket in the cloud and can be self-hosted or run air-gapped with a team's own models on Enterprise, which few rivals offer. Azure DevOps is the notable gap.",{"tool_id":499,"name":500,"slug":501,"tooltip_description":502,"logo_url":503,"logo_bg":93,"pricing_model":504,"learning_curve_score":454,"popularity_score":39,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":505,"subcategory":506,"categories":507,"subcategories":509,"flexibility_score":39,"performance_score":45,"portability_score":42,"is_featured":112,"tags":511,"score_reasonings":514,"published_date":185,"last_updated_date":36},286,"Cursor Bugbot","cursor-bugbot","Cursor's AI pull request reviewer, which runs as a GitHub or GitLab app and flags logic bugs, edge cases, and security issues on each PR. It works on any repository, whether or not the code was written in Cursor.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fcursor-bugbot.svg",{"slug":95,"display_name":96,"description":97},{"category_id":308,"name":309,"slug":310},{"subcategory_id":457,"name":458,"slug":459},[508],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[510],{"subcategory_id":457,"name":458,"slug":459,"category_id":308,"is_primary":3,"display_order":109},[512,513],{"tag_id":252,"name":253,"slug":254,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":515,"flexibility":516,"performance":517,"popularity":518,"portability":519},"Enabling it is a toggle in the Cursor dashboard plus a Git app install, and it reviews the next pull request with no rules written. BUGBOT.md files are optional context.","Nested BUGBOT.md rules, team rules, and effort levels let teams steer what it looks for, but the models and review style are Cursor's choice and it only covers GitHub and GitLab.","Reviews run automatically on each update and got about three times faster in a mid-2026 update; Cursor reports developers resolving around 80% of flagged bugs by merge, with the high effort setting finding more on complex changes.","The Cursor name is widely known and Bugbot reviews more than two million pull requests a month, but the reviewer itself is known mainly to Cursor users and teams comparing AI code review tools.","Works on any repository on GitHub or GitLab, but setup and billing are tied to a Cursor account, rules live in Cursor-specific BUGBOT.md files, and Autofix depends on Cursor's cloud agents.",{"coderabbit":521,"greptile":522,"cursor-bugbot":523},"Add CodeRabbit when pull requests from Kiro's cloud sessions should get a reviewer outside the agent: it installs as a GitHub or GitLab app, summarizes the diff, and leaves line-level comments, with a free tier for open-source repos.","Add Greptile when review should read the whole repository rather than only the diff: it indexes the codebase so its GitHub and GitLab comments carry wider context, and a self-hosted deployment keeps the code on your own infrastructure.","Add Cursor Bugbot when a bug-focused reviewer is enough: it reviews GitHub or GitLab pull requests whichever agent wrote them, though it bills through a Cursor plan rather than a subscription of its own.",{},"Add code review when you want an AI reading every pull request before it merges: it comments on the diff so bugs, security issues, and inconsistencies surface before a human has to catch them.",{"name":321,"tools":527,"descriptions":592,"aliases":595,"preface":596,"see_all":597},[528,566],{"tool_id":529,"name":530,"slug":531,"tooltip_description":532,"logo_url":533,"logo_bg":133,"pricing_model":534,"learning_curve_score":39,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":535,"subcategory":538,"categories":542,"subcategories":544,"flexibility_score":98,"performance_score":45,"portability_score":45,"is_featured":112,"tags":546,"score_reasonings":560,"published_date":125,"last_updated_date":185},164,"GitHub Actions","github-actions","GitHub's integrated CI\u002FCD platform that automates build, test, and deployment workflows using YAML-based configurations. Runs on GitHub-hosted or self-hosted runners with a rich marketplace of pre-built integrations.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fgithub-actions.svg",{"slug":156,"display_name":157,"description":158},{"category_id":175,"name":536,"slug":537},"DevOps & CI\u002FCD","devops-cicd",{"subcategory_id":539,"name":540,"slug":541},34,"CI\u002FCD Pipelines","cicd-pipelines",[543],{"category_id":175,"name":536,"slug":537,"is_primary":3,"display_order":109},[545],{"subcategory_id":539,"name":540,"slug":541,"category_id":175,"is_primary":3,"display_order":109},[547,548,549,550,551,555],{"tag_id":248,"name":249,"slug":250,"tag_type":173},{"tag_id":175,"name":176,"slug":177,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"tag_id":320,"name":321,"slug":322,"tag_type":323},{"tag_id":552,"name":553,"slug":554,"tag_type":173},24,"Docker Compatible","docker-compatible",{"tag_id":556,"name":557,"slug":558,"tag_type":559},45,"Declarative","declarative","paradigm",{"flexibility":561,"learning_curve":562,"performance":563,"popularity":564,"portability":565},"Self-hosted runner support across any OS or cloud, custom labels, matrix builds, Kubernetes scaling via Actions Runner Controller, and a marketplace of thousands of community-built actions give teams virtually unlimited configuration options for any workflow or environment.","Basic single-job workflows are accessible to any developer comfortable with YAML, and GitHub's documentation lowers the barrier further. However, advanced patterns — composite actions, reusable workflows, OIDC-based cloud auth, and conditional matrix strategies — involve non-obvious syntax and a complex permission model that requires meaningful time to master.","The platform handles massive scale reliably, but GitHub-hosted runner performance can vary between runs, making consistent benchmarking difficult. Teams running on self-hosted or larger hosted runners achieve stable, high throughput; the managed offering trades predictable latency for zero infrastructure overhead.","GitHub Actions is the dominant CI\u002FCD platform with tens of millions of repositories using it, thousands of marketplace actions, and widespread enterprise adoption. It is cited as the most-used CI\u002FCD solution in multiple developer surveys.","Self-hosted runners can run on any cloud or on-premises infrastructure, and the YAML workflow model is readable and auditable. The main constraint is tight coupling to GitHub events and APIs — moving workflows to another CI\u002FCD platform requires meaningful rewriting rather than a simple lift-and-shift.",{"tool_id":567,"name":568,"slug":569,"tooltip_description":570,"logo_url":337,"logo_bg":133,"pricing_model":571,"learning_curve_score":39,"popularity_score":45,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":572,"subcategory":573,"categories":574,"subcategories":576,"flexibility_score":98,"performance_score":39,"portability_score":39,"is_featured":112,"tags":578,"score_reasonings":586,"published_date":125,"last_updated_date":434},165,"GitLab CI\u002FCD","gitlab-cicd","GitLab's built-in CI\u002FCD system configured through .gitlab-ci.yml files stored in your repository. 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However, the platform's breadth — runner executors, pipeline inheritance, CI\u002FCD Catalog, merge trains, and security scanning configuration — creates a long tail of advanced concepts that teams discover gradually over months.","Multiple runner executor types (Docker, Kubernetes, Shell, machine), unlimited self-hosted runner capacity, parent-child pipelines, reusable CI\u002FCD Components, and the ability to self-host the entire platform give teams complete control over their pipeline environment and infrastructure.","Pipeline performance depends heavily on runner configuration and caching strategy. Shared GitLab-hosted runners can experience queue delays during peak periods, and Docker+machine executors add startup overhead. Teams running optimized self-hosted Kubernetes runners with effective caching achieve significantly faster pipelines, but the default shared experience is average for the CI\u002FCD category.","GitLab CI\u002FCD is used by over 100,000 organizations and is particularly strong among enterprises and security-conscious DevOps teams. It consistently ranks among the top CI\u002FCD platforms in developer surveys, though GitHub Actions has overtaken it in raw adoption volume — especially among open-source and smaller team segments.","GitLab CE is fully open source and self-hostable on any infrastructure, which is a strong portability advantage. However, .gitlab-ci.yml pipelines are tightly coupled to GitLab's API and runner ecosystem — migrating pipeline definitions to another CI\u002FCD system (GitHub Actions, CircleCI, etc.) requires substantial rewriting rather than a simple port.",{"github-actions":593,"gitlab-cicd":594},"Add GitHub Actions when every push should run the tests, including the pull requests Kiro's cloud sessions open. The Kiro CLI's headless mode also fits a workflow step, authenticated with an API key.","Add GitLab CI\u002FCD when the project lives on GitLab: pipelines defined in a .gitlab-ci.yml file run the tests on every merge request, on GitLab's runners or your own.",{},"Add CI\u002FCD when you want a dedicated pipeline for running tests, linting, or multi-stage builds before a deploy goes out. Many hosting platforms already redeploy automatically on every push on their own — a CI\u002FCD tool adds the most value on top of that by gating the deploy on a passing test suite, and matters even more when the hosting choice does not auto-deploy at all, such as a self-hosted server.",{"kind":442,"slug":541,"name":540,"href":598},"\u002Ftools\u002Fcategories\u002Fdevops-cicd\u002Fcicd-pipelines",{"name":600,"tools":601,"descriptions":632,"aliases":634,"preface":635,"see_all":636},"Containerization",[602],{"tool_id":603,"name":604,"slug":605,"tooltip_description":606,"logo_url":607,"logo_bg":93,"pricing_model":608,"learning_curve_score":45,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":609,"subcategory":610,"categories":613,"subcategories":615,"flexibility_score":98,"performance_score":45,"portability_score":98,"is_featured":3,"tags":617,"score_reasonings":626,"published_date":125,"last_updated_date":185},72,"Docker","docker","Container platform for packaging applications and their dependencies into portable images that run the same on a laptop, in CI, and in production, with Docker Desktop, Compose, and Docker Hub.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fdocker.svg",{"slug":156,"display_name":157,"description":158},{"category_id":175,"name":536,"slug":537},{"subcategory_id":611,"name":600,"slug":612},33,"containerization",[614],{"category_id":175,"name":536,"slug":537,"is_primary":3,"display_order":109},[616],{"subcategory_id":611,"name":600,"slug":612,"category_id":175,"is_primary":3,"display_order":109},[618,619,620,621,622],{"tag_id":170,"name":171,"slug":172,"tag_type":173},{"tag_id":175,"name":176,"slug":177,"tag_type":173},{"tag_id":552,"name":553,"slug":554,"tag_type":173},{"tag_id":320,"name":321,"slug":322,"tag_type":323},{"tag_id":623,"name":624,"slug":625,"tag_type":118},43,"Cross-platform","cross-platform",{"learning_curve":627,"performance":628,"portability":629,"flexibility":630,"popularity":631},"Container images, networking, volumes, and multi-stage builds all need deliberate learning.","Container overhead is minimal; near-native performance for most workloads.","Open standard; containers built with Docker run on any container-compatible platform.","Any runtime, any architecture; multi-stage builds and Compose profiles support complex systems.","The standard for containerization; present in virtually every modern software project.",{"docker":633},"Add Docker when the project needs the same environment on a laptop, in CI, and in production, or when a new teammate should start with one docker compose up. Kiro's agent can write the Dockerfile and Compose file as tasks in a spec.",{},"Add containerization when you want the app packaged the same way across local development, staging, and production, or need to deploy somewhere that isn't a managed serverless platform.",{"kind":442,"slug":612,"name":600,"href":637},"\u002Ftools\u002Fcategories\u002Fdevops-cicd\u002Fcontainerization",[639,647],{"slug":640,"name":641,"description":642,"icon_url":643,"addition_types":644},"developer_workflow","Developer workflow","Where the agent runs, how you reach it, and the tools you work in alongside it.","https:\u002F\u002Fassets.tekyous.dev\u002Ficons\u002Faddition-groups\u002Fdeveloper_workflow.svg",[645,646],"coding_agent","code_review",{"slug":648,"name":649,"description":650,"icon_url":651,"addition_types":652},"build_deploy","Build and deploy","Testing, packaging, and shipping your code on every change.","https:\u002F\u002Fassets.tekyous.dev\u002Ficons\u002Faddition-groups\u002Fbuild_deploy.svg",[653,612],"ci_cd",{},[102],{"Development Tools":657,"LLM":696},[658,683],{"tool_id":659,"name":660,"slug":661,"tooltip_description":662,"logo_url":663,"logo_bg":93,"pricing_model":664,"learning_curve_score":39,"popularity_score":454,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":665,"subcategory":666,"categories":670,"subcategories":672,"flexibility_score":45,"performance_score":39,"portability_score":39,"is_featured":112,"tags":674,"score_reasonings":677,"published_date":125,"last_updated_date":434},64,"Kiro","kiro","Kiro is AWS's spec-driven coding agent, in a Code OSS-based IDE, a terminal CLI, and cloud sessions on the web, that turns a feature request into requirements, a design, and tasks before writing code, on Claude, GPT, or open-weight models.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fkiro.svg",{"slug":156,"display_name":157,"description":158},{"category_id":308,"name":309,"slug":310},{"subcategory_id":667,"name":668,"slug":669},48,"IDEs & Editors","ides-editors",[671],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[673],{"subcategory_id":667,"name":668,"slug":669,"category_id":308,"is_primary":3,"display_order":109},[675,676],{"tag_id":248,"name":249,"slug":250,"tag_type":173},{"tag_id":252,"name":253,"slug":254,"tag_type":173},{"learning_curve":678,"performance":679,"portability":680,"flexibility":681,"popularity":682},"AWS-backed spec-driven editor; the agent-first workflow is new for most developers.","Cloud-backed AI features introduce latency; reasonable responsiveness for typical use.","Spec-driven workflow is AWS-specific; core coding skills transfer to any editor.","Spec-driven workflow supports custom hooks and agent customization.","Early access as of early 2026; very limited public adoption so far.",{"tool_id":301,"name":302,"slug":303,"tooltip_description":304,"logo_url":305,"logo_bg":133,"pricing_model":684,"learning_curve_score":39,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":685,"subcategory":686,"categories":687,"subcategories":689,"flexibility_score":45,"performance_score":39,"portability_score":42,"is_featured":112,"tags":691,"score_reasonings":695,"published_date":125,"last_updated_date":185},{"slug":156,"display_name":157,"description":158},{"category_id":308,"name":309,"slug":310},{"subcategory_id":312,"name":298,"slug":313},[688],{"category_id":308,"name":309,"slug":310,"is_primary":3,"display_order":109},[690],{"subcategory_id":312,"name":298,"slug":313,"category_id":308,"is_primary":3,"display_order":109},[692,693,694],{"tag_id":320,"name":321,"slug":322,"tag_type":323},{"tag_id":248,"name":249,"slug":250,"tag_type":173},{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":327,"flexibility":328,"performance":329,"popularity":330,"portability":331},[697],{"tool_id":88,"name":89,"slug":90,"tooltip_description":91,"logo_url":92,"logo_bg":93,"pricing_model":698,"learning_curve_score":42,"popularity_score":98,"hosting_assignment_type":36,"hosting_provider_restriction":99,"hosting_target_restriction":99,"hosting_compatible_tool_ids":36,"parent_tool_id":36,"category":699,"subcategory":700,"categories":701,"subcategories":703,"flexibility_score":45,"performance_score":98,"portability_score":39,"is_featured":112,"tags":705,"score_reasonings":707,"published_date":125,"last_updated_date":126},{"slug":95,"display_name":96,"description":97},{"category_id":101,"name":85,"slug":102},{"subcategory_id":104,"name":105,"slug":106},[702],{"category_id":101,"name":85,"slug":102,"is_primary":3,"display_order":109},[704],{"subcategory_id":104,"name":105,"slug":106,"category_id":101,"is_primary":3,"display_order":109},[706],{"tag_id":115,"name":116,"slug":117,"tag_type":118},{"learning_curve":120,"flexibility":121,"performance":122,"popularity":123,"portability":124},[709,726,734,749],{"stack_id":710,"slug":711,"name":712,"tagline":713,"experience_level":714,"project_type":36,"stack_type_slug":715,"stack_type_icon_url":716,"score_popularity":42,"score_learning_curve":39,"catalog_display_order":36,"published_date":36,"last_updated_date":36,"core_tool_previews":717},231,"paseo-dev-stack","Paseo Dev Stack","Run Claude Code, Codex, and other coding agents on your own machine with Paseo and steer them from any device.","advanced","developer","https:\u002F\u002Fassets.tekyous.dev\u002Ficons\u002Fstack-types\u002Fdeveloper.svg",[718,723,724,725],{"tool_id":719,"slug":720,"name":721,"logo_url":722,"logo_bg":133},278,"paseo","Paseo","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fpaseo.svg",{"tool_id":252,"slug":365,"name":364,"logo_url":92,"logo_bg":93},{"tool_id":301,"slug":303,"name":302,"logo_url":305,"logo_bg":133},{"tool_id":88,"slug":90,"name":89,"logo_url":92,"logo_bg":93},{"stack_id":567,"slug":727,"name":728,"tagline":729,"experience_level":714,"project_type":36,"stack_type_slug":715,"stack_type_icon_url":716,"score_popularity":45,"score_learning_curve":39,"catalog_display_order":36,"published_date":36,"last_updated_date":36,"core_tool_previews":730},"claude-code-dev-stack","Claude Code Dev Stack","Claude Code in the terminal, desktop app, or web, paired with Claude and the add-ons to run it anywhere.",[731,732,733],{"tool_id":252,"slug":365,"name":364,"logo_url":92,"logo_bg":93},{"tool_id":301,"slug":303,"name":302,"logo_url":305,"logo_bg":133},{"tool_id":88,"slug":90,"name":89,"logo_url":92,"logo_bg":93},{"stack_id":735,"slug":736,"name":737,"tagline":738,"experience_level":739,"project_type":36,"stack_type_slug":715,"stack_type_icon_url":716,"score_popularity":39,"score_learning_curve":42,"catalog_display_order":36,"published_date":36,"last_updated_date":36,"core_tool_previews":740},230,"t3-code-dev-stack","T3 Code Dev Stack","One open-source app for Claude Code, Codex, OpenCode, and other coding agents, on desktop and mobile.","intermediate",[741,746,747,748],{"tool_id":742,"slug":743,"name":744,"logo_url":745,"logo_bg":93},276,"t3-code","T3 Code","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Ft3-code.png",{"tool_id":252,"slug":365,"name":364,"logo_url":92,"logo_bg":93},{"tool_id":301,"slug":303,"name":302,"logo_url":305,"logo_bg":133},{"tool_id":88,"slug":90,"name":89,"logo_url":92,"logo_bg":93},{"stack_id":750,"slug":751,"name":752,"tagline":753,"experience_level":739,"project_type":36,"stack_type_slug":715,"stack_type_icon_url":716,"score_popularity":39,"score_learning_curve":42,"catalog_display_order":36,"published_date":36,"last_updated_date":36,"core_tool_previews":754},229,"conductor-dev-stack","Conductor Dev Stack","Run Claude Code, Codex, and Cursor's agent in parallel on your Mac with Conductor, each in its own workspace.",[755,760,761,762],{"tool_id":756,"slug":757,"name":758,"logo_url":759,"logo_bg":133},277,"conductor","Conductor","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fconductor.png",{"tool_id":252,"slug":365,"name":364,"logo_url":92,"logo_bg":93},{"tool_id":301,"slug":303,"name":302,"logo_url":305,"logo_bg":133},{"tool_id":88,"slug":90,"name":89,"logo_url":92,"logo_bg":93},[764,767,770,773,776],{"question":765,"answer":766},"Can Kiro keep working when my computer is off?","Yes, through cloud sessions on a paid plan. The agent runs in an isolated sandbox in Kiro's cloud with the repository cloned from GitHub or GitLab, so your computer can be off, and it hands back a pull request or merge request. A session can start in the IDE, the Kiro CLI, or Kiro Web in a browser, and continue from any of them. An iOS app in early access through TestFlight follows and steers cloud sessions; it doesn't control a session running in the IDE on your computer. Kiro Web can also run scheduled automations, such as dependency updates, without anyone starting them.",{"question":768,"answer":769},"Which models can Kiro use, and how are they billed?","Claude, OpenAI's GPT-5.6 family, and open-weight models from DeepSeek, Qwen, GLM, and MiniMax, all from Kiro's picker and all paid in Kiro credits rather than separate API keys. Each model has a multiplier against the Auto setting: Qwen3 Coder Next costs 0.05 times, Claude Sonnet 5.5 1.3 times, GPT-5.6 Sol 4.4 times. Credits are used fractionally per request, so a long spec task costs more than a quick edit, and they reset each month without rolling over. Some models are offered only in certain regions. The Pricing section has the plans.",{"question":771,"answer":772},"How is Kiro different from Cursor?","Both are AI IDEs built on VS Code's open-source core, with a CLI and cloud agents that open pull requests. Kiro plans before it codes: a feature becomes requirements, a design, and tasks that you approve, which suits larger features and teams that review plans. Cursor leans on fast Tab completions and chat or agent edits, with its own Composer model. Kiro pays for every model in credits and includes open-weight models on its free plan, while Cursor's paid plan leads with Grok and frontier models.",{"question":774,"answer":775},"Can I use Claude Code or Codex inside Kiro?","Yes. The official Claude Code and Codex extensions are published on Open VSX, the registry Kiro installs from, and any agent CLI runs in the integrated terminal. Each needs its own subscription, since Kiro's credits only cover Kiro's agent. They don't follow Kiro's spec workflow, but the requirements, design, and task files are plain Markdown in the repository, so another agent can read them as context and work through a task from the same plan.",{"question":777,"answer":778},"Should every change go through a spec?","No. A spec costs time and credits to write and approve, which pays off for a feature that touches several files, needs agreement on behaviour, or will be reviewed by someone else. A one-line fix or a small refactor is faster in chat, and Quick Spec sits in between, writing all three documents without stopping for approval. The spec files stay in the repository, so they're worth keeping current: a design that no longer matches the code misleads the next person, or agent, that reads it.",{"summary":780,"starting_cost_label":781,"has_free_tier":3,"line_items":782},"Kiro's subscription is the main cost, and its credits pay for every model in the picker. The free plan has 50 credits a month with open-weight models and Claude Sonnet 4.5; Pro is $20\u002Fmonth for 1,000 credits, up to Power at $200 for 10,000, with extra credits at $0.04. Cloud sessions need a paid plan. A separate agent like Claude Code or Codex needs its own plan. GitHub and GitLab are free for individuals.","Free to start",[783,787,791,794,798],{"label":784,"cost":785,"note":786},"Kiro subscription","Free–$200\u002Fmo","Free: 50 credits; Pro $20 (1,000), Pro+ $40 (2,000), Pro Max $100 (5,000), Power $200 (10,000) per user; extra credits $0.04; Enterprise on request.",{"label":788,"cost":789,"note":790},"Version control (GitHub or GitLab)","Free–$29\u002Fmo","Free tier covers individual devs and small teams; GitHub Team is $4\u002Fmo, GitLab Premium is $29\u002Fmo for more seats.",{"label":792,"cost":785,"note":793},"Separate coding agent (optional)","Claude Code starts at $20\u002Fmo (no free tier); Codex has a free tier, with Plus at $20\u002Fmo; both go to $200\u002Fmo. OpenCode is free and bills per token.",{"label":795,"cost":796,"note":797},"Docker (optional)","Free–$5\u002Fmo","Docker Desktop is free for personal use; Docker Pro adds team features from $5\u002Fmo.",{"label":799,"cost":800,"note":801},"CI\u002FCD (optional)","Free tier available","GitHub Actions and GitLab CI\u002FCD both include free monthly minutes before paid tiers kick in.","beginner",{"title":804,"description":805,"og_image":36,"canonical":806},"Kiro Dev Stack: Tools, Pricing & How to Deploy | Tekyous","AWS's spec-driven IDE, planning features before the agent codes, on Claude, GPT, or open-weig… Compare Kiro Dev Stack tools, pricing & how to deploy on Tekyous.","https:\u002F\u002Ftekyous.dev\u002Fstacks\u002Fkiro-dev-stack",[],1791800560566]