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Patterns for vibe coding that produce production-quality output instead of garbage. Covers prompt engineering for AI coding, verification without reading every line, accept/reject/refine decision framework, architectural guardrails, context management (CLAUDE.md, .cursor/rules), TDD-driven vibe coding, screenshot-driven development, diff review discipline, and the anti-patterns that destroy quality. Activate on: "vibe coding", "AI coding quality", "Claude Code workflow", "AI-assisted development", "how to use AI for coding", "coding with AI", "agentic engineering workflow", "AI code quality", "vibe code without garbage", "production quality AI code", "CLAUDE.md setup", "cursorrules setup", "pre-commit hooks for AI", "TDD with AI", "test-driven vibe coding". NOT for: multi-person collaborative coding sessions (use cooperative-vibe-coding), building AI/LLM applications (use ai-engineer), prompt engineering for non-coding LLM use cases (use prompt-engineer).

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。

Refactor apps so backend owns runtime truth and UI only projects snapshots. Use when tools have split authority. NOT for cosmetic UI work or new features before drift is removed.

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 genome-browser-style multi-track figures with pyGenomeTracks (config-driven), Gviz (R), and IGV batch screenshotting. Covers BigWig coverage tracks, BED/peak overlays, gene-model rendering, Hi-C matrix tracks, BedPE link arcs, spike-in-aware normalization, and the bamCoverage --normalizeUsing trap. Use when producing publication figures of genomic loci with stacked aligned tracks (coverage, peaks, genes, interactions) for ChIP-seq, ATAC-seq, RNA-seq, Hi-C, or generic locus visualization.

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。

Visualizes ChIP-seq data using deepTools (computeMatrix, plotHeatmap, plotProfile, bamCoverage, bamCompare), pyGenomeTracks (modern INI-driven track plots), Gviz (R browser-style), EnrichedHeatmap (ComplexHeatmap-based), ChIPseeker tag heatmaps, and IGV batch screenshots. Handles bigWig normalization choices (CPM, BPM, RPGC, spike-in scaled), bamCompare operations (log2 ratio, subtract) with SES scaling, k-means clustering of heatmaps for biological subgrouping, and spike-in-scaled tracks for global-shift experiments. Use when generating publication-quality ChIP-seq signal heatmaps, profile plots, genome-browser tracks, or comparing samples visually.

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。

Bulk-query Ensembl BioMart (and other BioMart instances) for cross-database ID mapping, gene/transcript/exon coordinates, and ortholog tables. Use when batch-converting Ensembl IDs to other namespaces (HGNC, RefSeq, UniProt, Entrez), pulling gene coordinate tables for thousands of genes, building ortholog wide-tables across species, or replacing slow Ensembl REST loops with one-shot bulk export. Encodes BioMart's XML query format, R biomaRt vs Python pybiomart trade-off, mart-vs-dataset hierarchy, and the URL endpoint that's BioMart-specific (separate from rest.ensembl.org).

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。

Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test web pages. Use whenever a browser would be useful, not just when the user explicitly asks.

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。

Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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。

Save a site or section as local files (markdown, screenshots). Use for "download the site", offline docs, or a local copy for reference.

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。

Azure App Configuration SDK for Java. Centralized application configuration management with key-value settings, feature flags, and snapshots.

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。

Capture baseline evidence from a live website URL: screenshots, scroll states, hover/click behavior, parallax, timers, and transition recordings. Use when reference artifacts are needed before implementation or comparison; not to build or diagnose a clone.

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 read-first Amazon Sponsored Products optimization, product-aware growth, preflight readiness, and post-change monitoring reviews that can run standalone from static exports or use Rocketcart MCP as an optional Amazon Ads plus product-intelligence layer. Guides Codex to inspect Rocketcart profiles, live SP campaigns, product ads/ASIN context, category rank/BSR movement, competitor signals, product readiness, budget and targeting drift, snapshots/changelogs, and proposed approval-gated action rows without executing writes by default.

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。

Quick-reference card for all caveman modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /caveman-help, "caveman help", "what caveman commands", "how do I use caveman".

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。

SAM: zero-shot image segmentation via points, boxes, masks.

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。

Audit social media accounts (TikTok, IG, etc.): scrape profiles, calculate engagement metrics, diagnose performance drops, interpret analytics screenshots.

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。

Produce a short executive summary for the current rolling-wave project. Use when the user wants a concise status update, investor/team-friendly summary, leadership summary, project progress snapshot, or TL;DR of completed slices, the current slice plan, and upcoming slices.

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。

Turn briefs, mockups, and product context into Stitch UI screens, design systems, variants, prototypes, Tailwind-friendly HTML, and screenshots. Use when the user wants to explore a screen, edit an existing Stitch project, compare visual directions, build a multi-screen prototype, or save local design/code-export artifacts from natural-language input.

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 an experiment-overview snapshot of all research questions under research/reports/. Invoke when a new point-in-time report across all RQs should be produced.

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。

Drive QA of a SwiftUI app on a real iPhone over USB - screenshot, read the accessibility tree, inspect @Observable state, tap, swipe, and type through an HTTP bridge embedded in the app under test. Use when asked to test an iOS app on a physical device, find bugs on the device, or expose a connected iPhone to a remote agent over Tailscale. Requires the ios-agent-qa runtime; not for simulator or XCTest 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。

Plan, write, and maintain automated tests in any language, with worked examples in Python and JavaScript/TypeScript. Use this skill whenever the user wants to write or plan tests, apply TDD (red-green-refactor), structure unit tests with arrange-act-assert and given-when-then naming, choose between fakes, stubs, and mocks, set up dependency injection for testability, build integration tests with testcontainers, database seeding, or transaction rollback, write Playwright or Cypress end-to-end tests, use property-based testing with Hypothesis or fast-check, create pytest fixtures or factory_boy factories, review coverage or mutation testing, or triage flaky tests in CI. Also trigger for "test pyramid", "test trophy", "test isolation", "mocking", "snapshot tests", "golden files", "parametrized tests", "make the tests pass".

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 designing production-LLM prompts — few-shot, chain-of-thought, system prompts, templates, self-verification — distinct from prompt-optimizer and refine-prompt.

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 says "create context", "document this area", or wants a structured snapshot of a codebase area for agent orientation.

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 adding, running, or debugging proctmux end-to-end integration tests, especially PTY/TUI behavior, terminal snapshots, unified/client modes, timing flakes, VT100 emulator limits, or files under tests/e2e and internal/testharness/e2e.

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 quando o Codex está construindo ou iterando em um jogo web (HTML/JS) e precisa de um loop confiável de desenvolvimento + teste: implementar pequenas mudanças, executar um script de teste baseado em Playwright com rajadas curtas de input e pausas intencionais, inspecionar screenshots/texto e revisar erros de console com render_game_to_text.

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 o servidor Figma MCP para buscar contexto de design, screenshots, variáveis e assets do Figma, além de traduzir nós do Figma em código de produção. Ative quando uma tarefa envolver URLs do Figma, IDs de nós, implementação design-to-code ou configuração e troubleshooting do Figma MCP.

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。