「rsa」の検索結果

Java "Ghost Bits" / Cast Attack playbook (Black Hat Asia 2026). Use when attacking Java services where 16-bit char is silently narrowed to 8-bit byte to bypass WAF/IDS for SQL injection, deserialization RCE, file upload (Webshell), path traversal, CRLF injection, request smuggling, and SMTP injection. Affects Tomcat, Spring, Jetty, Undertow, Vert.x, Jackson, Fastjson, Apache Commons BCEL, Apache HttpClient, Angus Mail, JDK HttpServer, Lettuce, Jodd, XMLWriter and re-enables many "patched" CVEs through WAF bypass.

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。

Universal AI-powered web scraper for any platform. Scrape data from Instagram, Facebook, TikTok, YouTube, LinkedIn, X/Twitter, Google Maps, Google Search, Google Trends, Reddit, Airbnb, Yelp, and 15+ more platforms. Use for lead generation, brand monitoring, competitor analysis, influencer discovery, trend research, content analytics, audience analysis, review analysis, SEO intelligence, recruitment, or any data extraction task.

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。

Lark/Feishu channel output rules. Always active in Lark conversations.

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。

End-to-end orchestrated workflow that runs a task the way Fable ran sessions - parallel evidence subagents, one committed plan, surgical execution with an intent gate, adversarial verification agents, honest outcome-first report. Use for non-trivial multi-step tasks when the user says "/fable-loop", "run the fable loop", or "do this the way Fable would". For the rules alone without orchestration, use fable-method; for large multi-phase projects, prefer the GSD workflow and use this inside phases.

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。

Adversarial verification of finished work. Treats any "done" as a set of claims, then re-runs the claimed verifications, diffs what actually changed, detects weakened tests and false completion claims, and delivers an evidence-based verdict (VERIFIED / VERIFIED WITH CAVEATS / REFUTED). Use after any agent or model claims work is complete - "/fable-judge", "judge this work", "verify what it did", "did that actually work?". Also runs the fable-method trap suite against a skill or model via "/fable-judge suite TARGET".

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。

Verify a WordPress plugin's Abilities API registrations: enumerate abilities, check that callback behavior matches each annotation's claim (the adversarial readonly-but-writes detection), validate permissions and schemas, and validate audit documents produced by wp-abilities-audit.

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 "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Multiple LLM reviewers challenge changes from independent angles.

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。

Spot patterns appearing in 3+ domains to find universal principles

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。

When the user wants to design or optimize the funnel that takes web visitors into installing and onboarding the app — including smart app banners, web-to-app deep links, deferred deep links, web onboarding (Stripe-paid web flow before app install), QR codes, "open in app" CTAs, and the trade-off between paying on web vs in-app. Use when the user mentions "web to app", "smart app banner", "Stripe before app", "web paywall before install", "Branch web SDK", "web funnel for app", "AppsFlyer OneLink web", "Universal Links", "App Links", "QR code to app", "open in app", "deferred deep link from web", or "should I sell on web first then push to app". For pure in-app onboarding, see onboarding-optimization. For deep link infra, see attribution-setup.

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。

开发、维护、分发和验证 DeepSeek Harness (DSH) 插件的执行型 Skill。覆盖 host/client 形态判断、bundle/profile 契约、Service 与函数插件、工具、HTTP、持久化、slot、Conversation Node、客户端构建、HMR、GitHub 安装和真实组合验证。

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 tau2-bench task export files to identify exactly where and why tasks failed. Map failures to specific conversation rounds, show root causes, check whether relevant documentation was available, and cite sources. Use this skill whenever you need to debug a tau2-bench evaluation, understand why an agent made wrong decisions, identify missing knowledge, or review task performance—especially when context length, eligibility criteria, or policy compliance might be at fault.

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。

Handles the difficult human situations — grievances, complaints, investigations, conflict, and separations conducted properly. Use this to respond to a complaint or grievance, structure an investigation, handle a conflict between colleagues, prepare for a difficult conversation, or work out what a manager can and cannot do in a given situation.

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。

Answers a business question with data without fooling yourself — framing the question so an answer would change something, choosing the right comparison, checking the data before trusting it, recognizing the traps that produce confident wrong answers (aggregation reversals, survivorship, regression to the mean, multiple comparisons), and reporting uncertainty honestly. Use this to run an analysis, review one before acting on it, or work out why two people looking at the same data reached opposite conclusions.

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。

Universal UI/UX design principles covering visual hierarchy, interaction laws, typography foundations, and WCAG accessibility requirements. Use when making design decisions not covered by a specific design system, validating principle compliance, or resolving conflicts between aesthetics and accessibility. Design-system-agnostic and applies to every surface.

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。

Search and send sticker images in chat. Use during casual conversations, greetings, encouragement, or celebrations to make interactions more lively and engaging.

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。

Miaoda App Builder - create web apps, WeChat mini-programs, games, AI tools, SaaS products, and dashboards through natural language conversations. Full workflow from code generation to deployment.

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。

Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.

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 drafts according to target writing style or target journal format. Triggers when user says "rewrite in XX style", "match this tone", "format for XX journal", "rewrite following this format". Input can be .docx / .md / .txt or conversation 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。

Design evidence-discovery and validation workflows for drug repurposing studies by integrating disease mechanisms, drug-target logic, expression reversal, real-world evidence, and validation routes into a closed-loop study blueprint.

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。

Fail closed on published draft XQUIC code pull requests before ready-for-review state. Use when asked to pre-review a code PR or move it out of draft; verify current base-to-head code, protocol conformance, validation coverage, adversarial bad cases, hot-path performance, and memory safety in a five-part local report.

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 "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Multiple LLM reviewers challenge changes from independent angles.

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。

Recommend suitable prompts from 10,000+ Nano Banana Pro image generation prompts based on user needs. Optimized for Nano Banana Pro (Gemini), but prompts also work with Nano Banana 2, Seedream 5.0, GPT Image 1.5, Midjourney, DALL-E, Flux, Stable Diffusion, and any text-to-image AI model. Use this skill when users want to: - Generate images with AI (any model — Nano Banana Pro, Gemini, GPT Image, Seedream, etc.) - Find proven AI image generation prompts and prompt templates - Get prompt recommendations for specific use cases (portraits, products, social media, posters, etc.) - Create illustrations for articles, videos, podcasts, or marketing content - Browse a curated prompt library with sample images - Translate and understand prompt techniques Also available: "ai-image-prompts" skill — a model-agnostic version of this library for universal image 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。

Design or build a page, screen, landing page, website, app or UI from a request - the whole job, end to end. Use this for "design a landing page", "build a settings screen", "make me a website", "design the onboarding", "ออกแบบหน้าเว็บ", "ทำหน้า landing", "ออกแบบ UI", "ทำแอป". It runs the pipeline no single skill covers: the house doctrine, a written Brief Inference so the result is not the statistical mean, a committed visual direction, tokens, build, the objective gates, then an adversarial critic. Hands off to data-dashboard for dense data screens, redesign for existing UI, and image-to-code when a reference image is given.

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。

Adversarial design critique of the current work — render it, look at it, and argue for rejection. Run after the gates are green, never instead of them.

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。