2.4万 件 ・ 関連度順
概要と使いどころ
Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations.
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 AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video.
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。
Guidelines for modern Avalonia UI layout using Zafiro.Avalonia, emphasizing shared styles, generic components, and avoiding XAML redundancy.
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 comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
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。
Audits and designs iOS/macOS/watchOS/visionOS interfaces against the Apple Human Interface Guidelines, including the Liquid Glass design language (announced WWDC25, shipped with iOS 26/macOS Tahoe, Sept 2025). Use when reviewing an Apple-platform mockup or app for HIG compliance, checking contrast or tap-target sizes, or designing native-feeling Apple UI (e.g., 'audit my iOS app against the HIG', 'is this text readable on Liquid Glass?').
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。
Configure and orchestrate parallel agents using the standalone Antigravity 2.0 Agent Manager and Antigravity IDE.
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。
Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.
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。
API documentation workflow for generating OpenAPI specs, creating developer guides, and maintaining comprehensive API documentation.
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。
Orchestrate multiple Antigravity skills through guided workflows for SaaS MVP delivery, security audits, AI agent builds, and browser QA.
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。
Production-grade Android app development guide covering native (Kotlin/Java), cross-platform (Flutter, RN, KMM), and hybrid architectures.
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。
Automate Amplitude tasks via Rube MCP (Composio): events, user activity, cohorts, user identification. 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。
Angular performance optimization and best practices guide. Use when writing, reviewing, or refactoring Angular code for optimal performance, bundle size, and rendering efficiency.
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。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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。
Provide comprehensive techniques for attacking Microsoft Active Directory environments. Covers reconnaissance, credential harvesting, Kerberos attacks, lateral movement, privilege escalation, and domain dominance for red team operations and penetration testing.
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。
n8n workflow automation knowledge base. Provides n8n node information, node functionality details, workflow patterns, and configuration examples. Covers triggers, data transformation, data input/output, AI integration, covering 10 nodes. Keywords: n8n, workflow, automation, node, trigger, webhook, http request, database, ai agent.
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。
Clone or recreate a live website URL, page, or section as React + Tailwind with extracted DOM, CSS, assets, responsive layout, motion, and interactions. Use for live-URL implementation or fidelity repair; not capture-only or diff-only requests.
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。
Diagnose why an existing implementation differs from reference evidence using AE/SSIM, pixel, section, computed-style, and transition diffs. Use for post-implementation mismatch or repair guidance; not baseline capture or full clone generation.
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。
Rewrite AI-sounding prose so it reads as considered human writing — cut the tells (em-dash pile-ups, "it's not X, it's Y" antitheses, inflated vocabulary, uniform rhythm, empty uplift) while preserving every fact, claim, and the author's own voice. Use when the user says "make this not sound like AI", "de-AI this", "humanize/humanise this", "this reads like ChatGPT", "remove the AI tells", "it sounds robotic/generic", or shares a draft (post, email, essay, docs, cover letter) to sharpen into a more human voice. Ships a stdlib scanner that flags the mechanical tells.
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。
Critically review a resume/CV against ATS (applicant tracking system) parsing rules, recruiter skim patterns, and keyword alignment with a target job description. Use when the user asks to "review my resume/CV", "check my resume against this job ad", "will this pass ATS", or shares a resume file (.docx/.pdf/.md) for feedback. Provides scored, prioritised, critical feedback — not a rewrite.
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。
Use when Amazon Ads optimization analysis, recommendations, approval packets, demos, recordings, or public artifacts must preserve exact source KPIs while masking account/profile/project names, products, ASINs, SKUs, campaigns, ad groups, keywords, search terms, targets, placements, filenames, URLs, and source-derived identifiers. Produces masked approval packets only; it must not directly mutate Amazon Ads.
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。
Find Amazon Ads search terms ready for exact-match harvesting from auto, broad, phrase, or other discovery campaigns. Use when Codex needs standalone or Rocketcart MCP-aware search-term harvesting: classify terms by harvest readiness, resolve live IDs, choose safe destination campaigns/ad groups, preflight duplicates/current negatives/destination feasibility, decide whether source negatives are justified, execute only explicitly approved rows, and read back/monitor Sponsored Products or Sponsored Brands actions without unsafe negatives, duplicate routing, stale approvals, brand-defense cuts, own-ASIN-defense cuts, launch/rank mistakes, or low-sample overfitting.
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。
Analyze Amazon product, sales, Amazon Ads, retail-readiness, and Best Seller Rank data to find commercially actionable growth opportunities. Use when Codex needs to identify which ASINs, campaigns, keywords, search terms, product targets, placements, categories, or BSR movements deserve more investment, optimization, harvesting, bid/budget changes, retail-readiness fixes, investigation, protection, or controlled scaling across Sponsored Products, Sponsored Brands, Sponsored Display, search term reports, targeting reports, campaign reports, placement reports, advertised/purchased product reports, Business Reports, organic performance, and BSR history.
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。