本文へ移動
cccskills

「build」の検索結果

1.3万 件 ・ 関連度順

概要と使いどころ

Get a branch ready for the maintainer's final review. Review it for security, simplicity, and billing abuse, fix what's real, get checks passing, and open or update the PR. Use whenever the user says a feature, fix, or branch should be "merge ready", asks to get changes ready for review, or appends this to a build request ("build X and make it merge-ready").

日本語の概要は準備中です。原文の説明を表示しています。

every-app/open-seo2.4万2026年10月14日 更新

Verify a released archon binary works end-to-end via a specific install path. Use when: cutting a new release, reproducing a user bug report on the released version, or validating that a hotfix binary actually works after a re-tag. Triggers: "test the release", "test 0.3.1 via brew", "verify the curl install", "smoke test the binary", "did the release binary work", "run /test-release", "verify the release". NOT for: testing dev work (use bun link directly), testing unreleased changes (build locally via scripts/build-binaries.sh first), or running the full validate suite (bun run validate is separate).

日本語の概要は準備中です。原文の説明を表示しています。

coleam00/Archon2.4万2026年10月16日 更新

Build reusable, composable n8n sub-workflows. Use when extracting shared logic, building anything multi-step or reused across workflows, or any workflow over ~10 nodes — and whenever the user mentions sub-workflows, Execute Workflow, reuse, shared/common logic, modular workflows, "Define Below" inputs, waitForSubWorkflow, mode each vs all, or exposing a workflow as an agent tool. Covers typed sub-workflow inputs, all-vs-each execution, verb-first naming for discovery, stateless vs stateful design, and splitting by input shape.

日本語の概要は準備中です。原文の説明を表示しています。

czlonkowski/n8n-mcp2.3万2026年10月15日 更新

Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, batch processing, or scheduled tasks. Always consult this skill when the user asks to create, build, or design an n8n workflow, automate a process, or connect services — even if they don't explicitly mention 'patterns'. Covers webhook, API, database, AI, batch processing, and scheduled automation architectures. Also use when optimizing a slow workflow or speeding up large-item-count processing (node count, batchSize, all-items vs per-item).

日本語の概要は準備中です。原文の説明を表示しています。

czlonkowski/n8n-mcp2.3万2026年10月15日 更新

Designs, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context.

日本語の概要は準備中です。原文の説明を表示しています。

google/skills2.1万2026年10月17日 更新

Kortix Capture, the standalone recorder app in apps/capture (Rust engine, Swift macOS capture engine, timeline UI, Windows .msi, macOS .pkg, Linux .deb). Load WHENEVER you change anything under apps/capture, the Capture workflows (capture-build.yml, capture.yml, the build-capture and attach-capture jobs of deploy-prod.yml), the /download/capture route, or the Capture installers; when you cut or debug a Capture release; and when you need the Kortix Capture bucket format (schema 2) or the app's behavior.

日本語の概要は準備中です。原文の説明を表示しています。

kortix-ai/suna2万2026年10月16日 更新

Recipe: build, edit, present or record a Kortix deck or film (a Next.js route under /presentations in apps/web, never a file). Load kortix-brand first. This skill covers the slide engine, builds, presenter notes, films and QA. Load WHENEVER the user asks for a deck, slides, a presentation, a walkthrough, a talk track, a guided demo, presenter notes, or a product video; and whenever editing anything under apps/web/src/app/[locale]/presentations.

日本語の概要は準備中です。原文の説明を表示しています。

kortix-ai/suna2万2026年10月16日 更新

Create, manage, validate, preview, and export slide decks and presentations. Build 1920x1080 HTML slide decks (the default, higher-quality path) and export to PDF or PPTX — or produce/edit a fully native, editable PowerPoint (.pptx) file directly when the user needs a plain PowerPoint deliverable. Load this skill when you need to build a slide deck, presentation, or PowerPoint file, or export/edit/validate one.

日本語の概要は準備中です。原文の説明を表示しています。

kortix-ai/suna2万2026年10月16日 更新

Build a working artifact from a plain "implement X for me" request: a running end-to-end spine first, then one feature per rung, with every under-determined decision written to an assumption ledger BEFORE the code that depends on it and a sweep for the ones that slipped through undeclared (same-family provisional in the base Codex mirror). Use when user says "给我实现", "implement X", "帮我做一个能跑的", "先搭个原型再加功能", "build this feature", "prototype then extend", or hands over a capability description rather than an experiment plan.

日本語の概要は準備中です。原文の説明を表示しています。

wanshuiyin/Auto-claude-code-research-in-sleep1.8万2026年10月7日 更新

Build a working artifact from a plain "implement X for me" request: a running end-to-end spine first, then one feature per rung, with every under-determined decision written to an assumption ledger BEFORE the code that depends on it and a cross-model sweep for the ones that slipped through undeclared. Use when user says "给我实现", "implement X", "帮我做一个能跑的", "先搭个原型再加功能", "build this feature", "prototype then extend", or hands over a capability description rather than an experiment plan.

日本語の概要は準備中です。原文の説明を表示しています。

wanshuiyin/Auto-claude-code-research-in-sleep1.8万2026年10月7日 更新

Operate FrontendExtension (FE) resources in frontend-forge: create, update, rebuild, inspect package artifacts, download packages, publish, unpublish, delete, and debug package/publish controller behavior. Use this skill whenever the user mentions FE operations, FrontendExtension lifecycle, extension package/download/publish/unpublish, artifact ConfigMaps, package Jobs, publisher Jobs, publish target ConfigMaps or Secrets, rebuild-token, package-state/publish-state labels, or troubleshooting FE status in a Kubernetes cluster.

日本語の概要は準備中です。原文の説明を表示しています。

kubesphere/kubesphere1.7万2026年7月15日 更新

Automate Buildkite tasks via Rube MCP (Composio). Always search tools first for current schemas.

日本語の概要は準備中です。原文の説明を表示しています。

composio-community/awesome-codex-skills1.7万2026年7月26日 更新

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

日本語の概要は準備中です。原文の説明を表示しています。

composio-community/awesome-codex-skills1.7万2026年7月26日 更新

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

日本語の概要は準備中です。原文の説明を表示しています。

HKUDS/DeepCode1.7万2026年10月14日 更新

Watch and monitor GitHub Actions workflow runs using the gh CLI. Use when the user wants to check workflow status, watch a running workflow, view CI/CD jobs, or monitor build progress. Trigger keywords - watch pipeline, pipeline status, CI status, check build, monitor CI, view pipeline, pipeline progress, workflow status, actions status.

日本語の概要は準備中です。原文の説明を表示しています。

NVIDIA/OpenShell1.6万2026年10月17日 更新

animate

無料

Build an animation from scratch, making the decisions in the order that determines whether it feels right — should it animate at all, what purpose, which tool, which properties, which curve and duration, how it interrupts, how it exits. Writes the implementation. Use when asked to animate something, add motion, make a component feel alive, or build a transition. For critiquing existing motion use review-animations; for auditing a whole codebase use improve-animations.

日本語の概要は準備中です。原文の説明を表示しています。

spree/spree1.6万2026年10月16日 更新

Automatically detect source types and build AI skills using Skill Seekers. Use when the user wants to create skills from documentation, repos, PDFs, videos, or other knowledge sources.

日本語の概要は準備中です。原文の説明を表示しています。

yusufkaraaslan/Skill_Seekers1.5万2026年10月1日 更新

Gets a custom map into CARLA on UE 5.8 — the four distinct routes and which one to pick — via Util/Tools/Import.py for FBX+OpenDRIVE assets into a source build, CARLA_MAPS_TO_COOK to ship a map inside a package, or client.generate_opendrive_world() for an OpenDRIVE-only map at runtime with no build at all. Covers where imported assets land, why an imported map cannot be loaded from a package by name, and the four capabilities the UE4 skill has that ue58 lacks — standalone asset packages, their installer, semantic-material tagging, and a pedestrian navmesh that is generated but silently skipped. Use when the user asks to "import a map", "add a custom map", "load my .xodr", "package my own town", or "create a standalone map package".

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla1.5万2026年10月16日 更新

Controls the map's light sources through the CARLA LightManager — turn street lamps, building/facade lights, vehicle lights or all of them on/off, set their colour and intensity, and toggle the automatic lights-at-night cycle. Use when the user asks to "turn on the street lights", "light up the city at night", "turn off building lights", "change the street-light colour", or "make lights come on automatically at night". Distinct from hiding lamp meshes (toggle-env-objects) and the sun (set-weather).

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla1.5万2026年10月16日 更新

Packages an agent for CARLA Leaderboard submission — builds the docker image with make_docker.sh (plain or ROS variant), checks the four required roots and the egg layout it assumes, sets the agent/track/routes environment inside the image, and verifies the image can import the stack and load the agent before submission. Use when the user asks to "build the leaderboard docker image", "submit to the leaderboard", "package my agent", or make_docker.sh fails.

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla1.5万2026年10月16日 更新

Lists and toggles a map's static environment objects via get_environment_objects / enable_environment_objects — hide or show buildings, vegetation, poles, fences, traffic signs and other baked assets by CityObjectLabel (and optional name filter). Use when the user asks to "hide/remove the buildings", "turn off the trees/vegetation", "show only the roads", "disable the fences", or "list the environment objects". Affects rendering and collision; resets on map reload.

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla1.5万2026年10月16日 更新

Imports an FBX pedestrian into a CARLA source build as a spawnable walker.pedestrian.NNNN — checks the FBX is skinned to CARLA's GEN3 rig, imports the mesh, physics asset and materials, builds the walker blueprint from a GEN3 donor, registers it in WalkerFactory through CARLA's own add_walker_to_walker_factory.py, and verifies it spawns, stands on the ground and walks. Use when the user asks to "add a pedestrian to CARLA", "import a walker/character FBX", or needs a custom human spawnable from the Python API.

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla1.5万2026年10月16日 更新

Cooks and packages CarlaUE4 into distributable tarballs under Dist/ — either the full simulator or a standalone asset package of selected maps and props for later import. ROS2=1 keeps the native ROS 2 interface in the cooked package (a plain cook silently drops it). Use when the user asks to "package CARLA", "make a Dist build", "cook the project", "export a map as a package", "package CARLA with ROS2", or needs a build with working camera and lidar sensors.

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla1.5万2026年10月16日 更新

langchain

無料

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

日本語の概要は準備中です。原文の説明を表示しています。

Orchestra-Research/AI-Research-SKILLs1.4万2026年10月11日 更新