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概要と使いどころ
Design and review client UI changes — visual token discipline, reuse-before-adding, feedback surfaces (toast vs in-place notice vs empty state), overlay and menu safety, platform window adaptation, loading states, and error copy placement. Use when adding or changing product-user-visible GUI behavior, or when reviewing such a PR.
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 a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Runs on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.
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 the HyperFrames CLI development loop: init, add, catalog, capture, lint, check, snapshot, compare, grade-compare, preview, play, present, beats, keyframes, single or batch render, publish, cloud, cloudrun, feedback, lambda, doctor, browser, info, upgrade, skills, compositions, docs, benchmark, telemetry, transcribe, auth, tts, and remove-background. Also use when diagnosing build or render failures. validate, inspect, and layout are deprecated aliases; use check. Covers local, HeyGen-hosted cloud, AWS Lambda, and Google Cloud Run rendering.
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 for Electron desktop application implementation, local packaging, and macOS Electron installer builds in GitHub Actions. Covers secure IPC, preload and multi-process architecture, electron-builder/Forge configuration, native modules, signing/notarization setup, DMG/ZIP packaging, mounted packaged smoke, and macOS qualification evidence. For cloud releases, this Skill owns macOS build and qualification; use github-desktop-release for Windows GitHub Actions qualification and for shared artifact promotion, GitHub Release publication, resume, or authoritative readback. Do not use this Skill to build or qualify Windows installers in GitHub Actions.
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。
Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.
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。
Review a GitHub pull request and provide structured feedback with severity ratings
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。
Appwrite Rust SDK skill. Use when building server-side Rust applications with Appwrite. Covers async client setup with API keys, user management, TablesDB database/table/row operations, file storage, function executions, permissions, queries, and error handling. Uses the crates.io `appwrite` package and Tokio.
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。
Day-to-day operation runbook for nuxt-crouton apps — boot any app/POC locally with auth working, seed and inspect the local database (including the miniflare-vs-.data split that makes seeded data "disappear"), turn on the review overlay / eruda, observe deployed staging (tail, smoke, row counts), and capture screenshots. Use when asked to "run the app", "boot velo/fanfare/a poc locally", "why can't I log in locally", "seed the database", "the seed data doesn't show up", "look at the local db", "check what's on staging", "screenshot the app", or "where do the artifacts land".
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。
Symptom → root-cause lookup table for nuxt-crouton's recurring failure modes — exact error strings mapped to their known cause, fix, and evidence issue. Use when you hit an error you don't recognize in this repo, before debugging from first principles. Trigger phrases and symptoms: "Cannot resolve entry module .nuxt/hub/db/schema.entry.ts", "Could not load '@fyit/crouton'", "No migrations present", "No schema files found", "$setup.t is not a function", "does not provide an export named 'Map'", "no such table: translations_ui", "collection pages 500 in production", "the build was green but the app is broken", "is this a known issue?".
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。
The migration step and the package-owned-table exception — NOT the normal collection flow. For app collections use the crouton CLI/skill (schema JSON → `crouton config`); reach here when you then need to generate/apply the Drizzle migration and hit the schema.mjs-only-after-build gotcha ("No schema files found"), or when adding a package-owned infra table (the crouton-flow pattern) that does NOT go through `crouton config`.
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 MEASURE this repo instead of eyeballing it — interpret the loop-station context-budget trend (history.jsonl, thresholds, the tokenizer-switch gotcha), read a session trace, use the eval ledger (cost-per-success), and pick the right evidence tool (app-shots, smoke-deployed, db-counts, --check modes). Use when asked "is the harness bloating", "how big is CLAUDE.md really", "did this agent run actually succeed", "prove this works", "what evidence do we have", or when tempted to declare a capability (browser, tool) unavailable. For RUNNING the loop-station scripts, defer to the loop-station skill — this skill is interpretation + the wider evidence toolkit.
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。
Decision transparency, feedback collection, and debate invitations for AID methodology. Active in ALL phases for ALL roles.
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。
Package an AI skill, prompt workflow, or internal operating habit into a public-ready release with a catchy hook, safe redaction, useful examples, demo tasks, README copy, and launch messaging. Use when preparing a skill for GitHub, social sharing, marketplace submission, documentation, or community feedback.
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。
Convex UI component patterns from the live Storybook preview. Use when building React components, forms, modals, navigation, feedback states, or app layouts that should match the current Convex design system. Applies to both shared primitives and dashboard style product UI.
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。
Convex UI component patterns from the live Storybook preview. Use when building React components, forms, modals, navigation, feedback states, or app layouts that should match the current Convex design system. Applies to both shared primitives and dashboard style product UI.
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。
Design Azure architectures for startups and enterprises. Use when asked to design Azure infrastructure, create Bicep/ARM templates, optimize Azure costs, set up Azure DevOps pipelines, or migrate to Azure. Covers AKS, App Service, Azure Functions, Cosmos DB, and cost optimization.
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。
AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g
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。
Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.
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。
XML-specified Android UI journey testing, interactive step execution, assertion verification, and JSON outcome reporting.
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。
Automated end-to-end UI testing and verification on an Android Emulator using ADB.
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。
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews 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。
Orchestrates Android development tasks including project creation, deployment, SDK management, and environment diagnostics using the `android` command-line tool.
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。
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home).
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。
Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.
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。