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概要と使いどころ
Embedded firmware setup: STM32, ESP32, AVR, RP2040, Nordic nRF, Zephyr/RTOS, vendor SDKs, CMake/CMakePresets, VS Code/clangd, cross toolchains, flash/debug, Docker/CI. Use for MCU scaffolds, existing firmware modernization, BSPs, linker/startup files, SDK package selection, and embedded CI; prefer cpp-project-setup for host-side C++.
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。
Dockerfile、Compose、Terraform、GitHub Actionsの危険設定を決定的な検出器で検査し、共通Finding schemaとredaction基準で返す。secretや一般の脆弱性はreviewerのsecurity観点を使う。明示的な `/sentinel-review` の指定でだけ使う。
Dockerfile・Compose・Terraform・GitHub Actionsの差分または指定パスを決定的な検出器で検査し、共通Finding schemaとredaction基準で結果を返す。IaCの危険設定検査専用で、secretや一般の脆弱性はreviewerのsecurity観点を使う。明示的な `/sentinel-review` の指定でだけ使う。
Builds a WooCommerce-style AJAX product search select (the selectWoo / wooselect dropdown) — class="wc-product-search" + the data-action attribute pointing to woocommerce_json_search_products (products only) or woocommerce_json_search_products_and_variations (products AND variations, often the right choice). Pre-selected items rendered server-side as <option selected> via wc_get_product() + get_formatted_name(); WC's wc-enhanced-select script auto-enqueued on WC admin screens, explicit enqueue required on non-WC pages. Solves the "load 20k products into a select" antipattern AI assistants commonly emit. Use when adding a product picker meta box, a custom WC admin page selector, or any UI where the user must search and pick from many products. Triggers on wc-product-search, woocommerce_json_search_products, woocommerce_json_search_products_and_variations, selectWoo, wc-enhanced-select, "select2 products in WooCommerce", or product-picker meta box scaffolding.
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。
Complete operational guide for the NV oOS (Open Operator System) WordPress plugin in Docker/WSL2 — setup, assistant creation, credential tokens, MCP tool calling, API key auto-detection, env var bridging, common fixes, and IGCSE study configuration. Use when setting up the plugin for the first time, creating assistants programmatically, generating MCP bridge tokens, troubleshooting Docker path issues, bridging API keys, or calling tools via JSON-RPC over HTTP.
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 as a distributed worker — continuously claim, work, and release Up Next tickets
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。
Build, run, and manage OCI/Linux containers as lightweight per-container VMs on Apple-silicon macOS using Apple's open-source container CLI, no Docker daemon required.
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。
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, per
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。
Install and use the official AI Logo Maker package, pinned by digest, for paid hosted work on the Beatra 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。
Use when the user asks to "check technical SEO"; audits crawlability, indexing, Core Web Vitals, robots.txt, sitemaps, canonicals, redirects, and migrations. Not for on-page tags or content — use on-page-seo-checker. 技术SEO/网站速度
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。
Use when the user asks to "audit on-page SEO" or "diagnose why a single page dropped"; scores titles, meta, header structure, keyword placement, links, and images with prioritized fixes. Not for E-E-A-T / publish-readiness scoring — use content-quality-auditor; not for crawl / CWV / indexing — use technical-seo-checker. 页面SEO审计/排名诊断
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。
Use when the user asks to "measure how our narrative is landing", "track echo rate against our canon lexicon", or "check how AI answer engines describe our brand"; produces a resonance report — echo rate (overlap of market language with the narrative-registry canon lexicon, method declared), AI-answer perception via tavily.py --answer (proxy-labeled), share-of-voice on a locked competitor panel (reusing share-of-voice-tracker), and resonance signals from bluesky.py / gdelt.py / pageviews.py — every number labeled Measured / proxy / User-provided, feeding the TALE E dimension and the upstream of the E1 evidence-integrity veto. Not for rebuilding share-of-voice machinery — use share-of-voice-tracker; not for own-site GA4/GSC analytics — use performance-monitor; not for scoring TALE profile result — use narrative-quality-auditor; not for adjudicating claims — use offer-claims-registry. 回声率/AI回答感知/份额之声/共鸣信号
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。
Use when the user asks to "monitor my launch", "track our Product Hunt / Hacker News ranking", or "watch the launch window"; runs the T-0 to T+30 window watch — pre-launch instrumentation verification (UTM/event checks, the upstream of RAMP P1), HN rank/points/comments polling with a comments-over-points flamewar early-warning (Estimated heuristic), PH votes/featured status, store charts and reviews, news echo, D0/W1/M1 KPI snapshots vs targets, spike-vs-sustain and owned-capture reads, and alert thresholds against the launch-tier KPI targets. Not for launch-day go/rollback calls — use launch-day-conductor; not for metric deep-dives — use performance-analyzer; not for SEO rank tracking — use rank-tracker. 发布监控/排名轮询/火焰战比/spike-sustain
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。
DevOps e deploy de aplicacoes — Docker, CI/CD com GitHub Actions, AWS Lambda, SAM, Terraform, infraestrutura como codigo e monitoramento.
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Distill an already-built or near-launch product into one incisive brand kernel — the "reveal" already hiding in its name, story, or the product itself — then build the name, voice, visual identity, and a developer-ready handoff kit around it. This is LATE-STAGE branding: use it when there is a real, thought-through product that is about to launch, or already live but not explained in a way people grasp in an instant. Use whenever the user wants to name or rename a product, find a tagline or slogan, create a brand identity / brand kit / style guide / design system, design a logo, wordmark, palette, or type system, mock up a homepage for a launch, or hand brand assets to a coding agent (Claude Code, Codex, Cursor). Trigger even when the user only says their product needs to "land" or "feel like" something, or that they can't explain it simply yet. Do NOT use for half-baked, pre-product ideas with nothing to excavate — this skill extracts a kernel that already exists; it does not invent one from a blank canvas.
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。
Develops full-stack Dart backends using the Serverpod framework with PostgreSQL, Redis, and Docker. Use when building type-safe API endpoints, defining YAML data models, configuring Serverpod auth, writing server-side tests, running database migrations, deploying to Docker/AWS/GCP, or using Serverpod Mini for database-less BFF proxy endpoints.
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。
Delegate real-world tasks to human workers via the OpenHumancy API. Use when the user needs physical actions (field verification, photography, deliveries, mystery shopping), human judgment, or any task that requires a person. Manages the full lifecycle — worker search, task creation, chat, payments on the TON blockchain.
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。
How to migrate the tdmcp Claude Desktop bundle from legacy .dxt to .mcpb (MCP Bundle) and keep it building — covers the manifest schema (verify against the installed packer, never hardcode), the build-dxt.mjs packer/zip-fallback flow, the npm scripts, and the full .dxt→.mcpb reference sweep across docs and scripts. Use when packaging or migrating the tdmcp desktop bundle.
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 in Cloudflare Workers and the Edge Computing ecosystem. Covers Wrangler, KV, D1, Durable Objects, and R2 storage.
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Use when writing, running, or debugging Playwright e2e tests in this Hydrolix Grafana datasource plugin. Covers the docker-compose `playwright` service invocation, locator patterns for Grafana's react-select / Monaco editor / panel chrome, state-dependent interactions in QueryEditor, and timeout/retry expectations. Apply whenever a task touches `tests/*.spec.ts`, `tests/helpers.ts`, the `playwright` service in `docker-compose.yaml`, or the test results under `test-results/`.
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。
Use when working with Caprover — capRover self-hosted PaaS management covering app inventory, container status, custom domain mappings, persistent directory mounts, environment variable auditing, cluster node status, Docker registry integration, and Nginx configuration review. Use for managing CapRover infrastructure.
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。
Use when working with Celery — celery worker management, task monitoring, queue routing, Flower dashboard analysis, and task result tracking.
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。
Use when working with Changesets — changesets version management covering changeset file inventory, pending version bump analysis, package release readiness, changelog generation status, and monorepo release coordination. Use when auditing pending changesets, investigating release blockers, reviewing version bump strategies, or managing multi-package release workflows.
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。
Use when working with Baselime — baselime serverless observability platform for AWS Lambda, CloudFlare Workers, and Vercel functions. Covers log and trace querying, alert management, service discovery, and performance analysis of serverless workloads. Use when investigating serverless function performance, querying Baselime events, managing alerts, or analyzing cold start and duration metrics.
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。