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概要と使いどころ
Node-RED visual automation flows for Home Assistant. Covers visual automation, flow JSON, trigger-state, api-call-service, function nodes, context storage, timer patterns, error handling, and node-red-contrib-home-assistant-websocket nodes. Use when user mentions "Node-RED", "flow", "visual automation", or "node-redflöde".
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。
Home Assistant custom integration development in Python. Covers custom_components, DataUpdateCoordinator, config_flow, OAuth2, conversation agent, HACS publishing, device registry, entity platforms, services, repair issues, diagnostics, Bluetooth integrations, and multi-coordinator patterns.
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。
Data-model rules that make a schema importable from day one, so the migration-import-engineer is never blocked on missing columns. Every SMB Product-Builder product must let a customer bring their data from an incumbent (ServiceTitan/Toast/Mindbody/Shopify) — that requires provenance (source_ref) and rollback (import_batch_id) on importable entities, and modelling real-world actors as entities rather than inline fields. Applied by architect when writing the data model in ARCH-{slug}.md, and checked by migration-import-engineer. One cheap rule set prevents the migration↔architecture seam gap from recurring across all 40 products.
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。
Onboarding-and-switching playbook for SMB Product-Builder products. Defines the first-run experience that turns a prospect leaving an incumbent (ServiceTitan/Toast/Mindbody/Shopify/QuickBooks) into an activated user — import-first onboarding, the activation milestone, sample-data fallback, and the time-to-first-value target. Applied by migration-import-engineer and architect/pm so onboarding is designed as a funnel, not an afterthought. Our whole wedge is "low switching cost"; this skill makes that real on day 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。
Deploy to VPS. Code is already on the server. Start the service, configure nginx, verify accessible.
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。
Run before writing or changing code for any feature, bug fix or refactor that touches data, jobs, money, outside services or user-facing behaviour. Finds where the change will break before it is built, by walking ten named failure classes (twice, halfway, outside call, failure-is-not-empty, neighbors, endings, money, hostile user, words, scale and time) against the code, and writes the answers into the plan. Use when planning a change, when asked to "think it through", "cover the gaps", "make sure it's bug free", or before any edit to payment, publishing, deletion, auth or background-job code.
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。
Create, redesign, repair, validate, preview, and package lightweight standalone HTML deliverables. Use for marketing experiences, product prototypes, infographics, motion narratives, documents, browser tools, dashboards, guided workflows, knowledge interfaces, mini-games, presentations, reusable style and brand systems, and local-model text, vision, image, or code tools that must run without a build chain or hosted service.
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。
First-run onboarding — guides new users through Genesis setup on their first CC session. Configures user profile, essential API keys, Telegram, GitHub backup, and service verification. Triggered automatically while the install is not yet FUNCTIONAL (the setup floor — Claude Code login + an LLM key + an embedding key — is unmet), not merely while ~/.genesis/setup-complete is absent. Re-runnable by asking Genesis to "run setup" or "reconfigure [section]".
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。
Plans risk-based test coverage for a feature, service, release, or system by mapping user and business risk to test levels, environments, data, failure paths, automation, exploratory checks, and release gates. Use when choosing what to test or how much evidence is enough. Not for writing one test case, applying TDD to a single behavior, or debugging a failing test.
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。
Coordinates an active production incident by establishing command, reducing blast radius, preserving evidence, communicating verified impact, restoring service, validating recovery, and creating owned follow-up actions. Use for outages, severe degradation, security or data-integrity events, failed releases, and urgent operational triage. Not for a normal local bug, routine alert tuning, or a postmortem after the incident is already closed.
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。
Designs or reviews HTTP, REST, GraphQL, RPC, CLI, webhook, event, and service interfaces with explicit inputs, outputs, errors, compatibility, idempotency, pagination, authentication, versioning, and observability. Use when introducing or changing an API or cross-component contract. Not for internal implementation details with no boundary or for debugging one API failure; use root-cause-debugging there.
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。
Validates a running application, CLI, API, service, or generated artifact as a user or operator against a prewritten observable behavior contract while remaining source-blind. Use for acceptance checks, runtime proof, anti-fake probes, release smoke tests, or an independent companion to code review. Not for source-quality findings, root-cause diagnosis, or visual design judgment outside the contract.
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。
Designs cross-system target states and transition plans. Use when comparing end-to-end options or phased migrations. Not for in-service topology (software-architecture-design).
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。
Chooses managed backend platforms such as Supabase, Convex, and Firebase. Use when comparing database, auth, realtime, and backend-service tradeoffs.
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。
Designs runtime topology in a chosen solution. Use when choosing monolith vs services, cells, consistency, ADRs. Not for cross-system design (software-solution-architecture).
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。
Designs and troubleshoots NUKE-based CI/CD pipelines for .NET services. Use when refactoring target graphs, splitting test flows, publishing reports, or diagnosing slow pipelines.
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。
Designs AI-first help centers and self-service support. Use when shaping taxonomy, article templates, or content and answer contract for support AI, not the bot build.
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。
Cancel a subscription or unsubscribe from a service. Works from a description, a pasted charge line, a URL, or a photo/screenshot. Can also audit a full statement for recurring charges and cancel several at once. Finds the right contact method and handles the cancellation — including phone calls.
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。
Help find and book a service provider for a task — cleaning, handyman, moving, assembly, yard work, errands, etc. Searches TaskRabbit, Handy, Thumbtack, and similar platforms.
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。
Generates Angular code and provides architectural guidance. Trigger when creating projects, components, services, or HTTP communication, or for best practices on reactivity (signals, linkedSignal, resource, httpResource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, naming conventions, or CLI tooling.
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。
Expert Go programming skill authored by spf13 (former Go team lead, author of Cobra, Viper, Hugo, Afero). Covers idiomatic Go — package design, error handling, interfaces, concurrency, testing, and project layout, current through Go 1.27. Use whenever Go code is written, reviewed, debugged, or refactored — any .go file, go.mod, CLI tool, or web service, and whenever the user mentions Go or golang, even if they don't ask for "idiomatic" code.
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。
Operate HitKeep safely in isolated Git worktrees. Use when inspecting workspace state, resolving ports or URLs, starting or stopping development services, coordinating concurrent agents or QA runs, reusing active runs, reading bounded logs, or preparing a secret-free handoff.
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。
Expert guide for Monte Carlo's push ingestion model. Use this skill whenever a customer or engineer mentions: pushing data to Monte Carlo, the IngestionService, pycarlo push APIs, build me a collection script, push metadata/lineage/query logs, invocation_id tracing, custom lineage nodes or edges, deleting push tables, or any question about why pushed data is not showing up. Also trigger when they ask to generate code that collects metadata, table schema, row counts, freshness, lineage, or query history from any data warehouse or data source and sends it to Monte Carlo. If the user mentions any warehouse, database, or data platform alongside any Monte Carlo topic, this skill is almost certainly relevant.
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。
System-design thinking before any doc or code: goals/non-goals, back-of-envelope numbers, components and contracts, failure modes, operability, security, trade-offs. Use for "design this system", "architecture for X", "trade-offs for X", "how should we architect", "API design", "data model for", "service boundaries", or before an ADR. Hands off to /ship:write-docs to record the decision. Not implementation planning (/ship:design — that turns a decided design into stories).
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。