1.6천건 ・ 연동 도구: Docker · 인기순
Dockerベースのアプリケーションのデプロイメント手順書（Markdown）を作成するスキル。「デプロイ手順書」「デプロイメント手順」「deployment guide」「本番環境への配置手順」「サーバーへの配置手順」などの依頼でトリガーする。Docker Composeビルド→イメージ転送→サーバー配置→設定→動作確認→cron設定の流れで手順書を生成する。
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pytestのマーク体系を設計・実装するスキル。「テストをマークで分類したい」「CIでDockerテストをスキップしたい」「Dockerコンテナ内で実行できないテストを除外したい」「make testでDockerテストを実行したい」「テストの実行対象を環境ごとに切り替えたい」「新しいマークを追加したい」「skipifを使いたい」「pytestの--strict-markersで未定義マークエラーが出る」という依頼で起動。マーク設計→pyproject.toml登録→テストコード付与→CI/ローカルコマンド整合の流れで実装する。
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Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
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Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
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Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.
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High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
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OSINT username search across 400+ social networks. Hunt down social media accounts by username.
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Use when: User wants to extend Docker with custom tools, personalize the Docker environment, or set up user-specific Docker customization. Triggers: 'extend docker', 'docker-extend', 'add tools to docker', 'customize docker', 'add my tools to the container', 'personalize docker setup', 'docker user setup', 'install tools in docker'. Does: Interactively sets up Dockerfile.user and docker-compose.override.yml so users can add personal tools to their Docker environment without affecting maintainer files or committing user-specific config to git.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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Manage Docker containers, images, volumes, networks, and Compose stacks — lifecycle ops, debugging, cleanup, and Dockerfile optimization.
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Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges
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Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
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Develop Openrind Shell's OpenShell-supervised PostgreSQL FUSE runtime, compatibility sync runtime, and just-bash library.
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Start the Openrind Desktop dev stack via Docker and verify real user flows via Chrome MCP. Triggers when user mentions: - "dev-up.sh" - "docker dev stack" - "verify in chrome mcp" - "test the real flow"
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Set up and maintain continuous integration and continuous deployment pipelines with GitHub Actions, GitLab CI, Jenkins, or similar tools to automate testing, building, and deployment. Use when configuring automated builds, setting up test automation, implementing deployment automation, creating release workflows, managing environment deployments, configuring build caching, implementing blue-green deployments, setting up rollback strategies, or automating the entire software delivery pipeline.
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Interactive developer experience plan review. Explores developer personas, benchmarks against competitors, designs magical moments, and traces friction points before scoring. Three modes: DX EXPANSION (competitive advantage), DX POLISH (bulletproof every touchpoint), DX TRIAGE (critical gaps only). Use when asked to "DX review", "developer experience audit", "devex review", or "API design review". Proactively suggest when the user has a plan for developer-facing products (APIs, CLIs, SDKs, libraries, platforms, docs). (gstack) Voice triggers (speech-to-text aliases): "dx review", "developer experience review", "devex review", "devex audit", "API design review", "onboarding review".
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Chief Security Officer mode. Infrastructure-first security audit: secrets archaeology, dependency supply chain, CI/CD pipeline security, LLM/AI security, skill supply chain scanning, plus OWASP Top 10, STRIDE threat modeling, and active verification. Two modes: daily (zero-noise, 8/10 confidence gate) and comprehensive (monthly deep scan, 2/10 bar). Trend tracking across audit runs. Use when: "security audit", "threat model", "pentest review", "OWASP", "CSO review". (gstack) Voice triggers (speech-to-text aliases): "see-so", "see so", "security review", "security check", "vulnerability scan", "run security".
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Use when you need to visually interact with a GUI — test buttons, fill forms, verify visual layouts, fuzz web pages, automate user flows, take screenshots, or perform end-to-end QA on any application. Works on cloud VMs, Docker containers, local machines, and sandboxes. Install: pip install cua.
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Capture the "why" behind technical choices to prevent architectural drift. Load when the user makes a major technical decision, chooses a library/framework, defines a system boundary, or changes a core architectural pattern. Also triggers on "record a decision", "write an ADR", "why did we do this", "document this architectural choice", or "architectural decision record". Supports `SYNTHESIS=true` mode for retrospective ADR backfill from observed repo state — used by `retroactive-project-setup` and any future backfill skill. Essential for long-term project maintainability and agent alignment.
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Generate comprehensive C4 architecture documentation for an existing repository/codebase using a bottom-up analysis approach.
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Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.
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Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.
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Designs pegRNAs and nicking guides for prime editing (PE) -- choosing the nick/strand, tuning the primer-binding site (PBS) and reverse-transcription template (RTT) as a per-locus panel, selecting the PE system (PE2/PE3/PE3b/PE4/PE5/PEmax/PE7), adding MMR-evading and PAM-disrupting silent edits, appending epegRNA 3' motifs (tevopreQ1/mpknot), and ranking with PRIDICT/DeepPrime. Covers twinPE/PASTE for large insertions and the prime-vs-base-editing decision. Use when designing a scarless point mutation, small insertion/deletion, or any of the 12 base conversions without a double-strand break, when efficiency is low and MMR inhibition or pegRNA stabilization is needed, or when routing a large insertion to an integrase method. Generic guide scoring and base editing are separate skills.
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Designs Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and posterior probability stopping rules. Covers FDA Bayesian Devices Guidance (2010), FDA Bayesian Methodology in Drugs Draft (January 2026), BOIN Fit-for-Purpose qualification (December 2021), and Project Optimus dose-optimisation. Use when designing dose-finding studies, platform trials, or sensitivity analyses with informative priors.
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