「red」の検索結果

Detect, validate, and generate Schema.org structured data. JSON-LD format preferred. Use when user says "schema", "structured data", "rich results", "JSON-LD", or "markup".

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This package provides the visualization of bayesian network inferred from gene expression data. The networks are based on enrichment analysis results inferred from packages including clusterProfiler and ReactomePA. The networks between pathways and genes inside the pathways can be inferred and visualized.

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Expert knowledge for Azure Red Hat OpenShift development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when deploying ARO/HCP clusters, configuring networking/storage, securing with Entra/NSGs, or integrating ACR/Key Vault, and other Azure Red Hat OpenShift related development tasks. Not for Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Container Apps (use azure-container-apps), Azure Virtual Machines (use azure-virtual-machines).

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Comprehensive Amazon advertising strategy and campaign optimization. Sponsored Products, Sponsored Brands, Sponsored Display campaign management, budget allocation, ACoS optimization, and performance tracking. Use when the user asks about Amazon PPC, advertising strategy, campaign optimization, or Amazon ads management.

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Judge whether one stored row states a retired profile position as current.

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Use when the user asks about Higgsfield Assist (the built-in GPT-5 copilot), how to use the platform's native AI assistant, credit optimization strategies, plan selection, how to get more from fewer credits, or platform efficiency tips.

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Generate Schema.org structured data (JSON-LD) for any page type. Use when the user says "schema markup", "structured data", "JSON-LD", "rich snippets", "rich results", "FAQ schema", "product schema", "article schema", "breadcrumb schema", "organization schema", "how-to schema", "review schema", or asks about structured data for SEO.

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Create LinkedIn ad campaigns, write sponsored content, define professional audiences, and plan B2B advertising budgets. Use when the user asks about LinkedIn Ads, sponsored content, LinkedIn Campaign Manager, InMail ads, lead gen forms, B2B advertising, professional targeting, or LinkedIn retargeting. Trigger phrases include "LinkedIn Ads", "LinkedIn campaign", "sponsored content", "InMail ad", "LinkedIn lead gen", "B2B ads", "LinkedIn retargeting", "LinkedIn audience", "LinkedIn ad copy", "LinkedIn Campaign Manager".

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Detect and investigate bulk registration abuse on SaaS platforms. Given access to a user database (or exported CSV/JSON), run a multi-dimensional anomaly analysis — email domain clustering, registration tempo, UA fingerprinting, session structure, usage patterns, and credit consumption — to produce a scored abuse report with actionable recommendations. Use when investigating suspicious sign-up spikes, credit fraud, free-tier abuse, or account farming.

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Monthly, on the last weekday, file work only, no browser at all. Folds the decision ledger, scores this Employee's own judgement against the metric files that measured it rather than against its own predictions, appends one outcome line per closed decision, retires a move proposed three times and never accepted, and rewrites the priorities where the evidence disagrees with them. It refuses to publish a calibration figure on too few closed decisions, changes nothing outside its own folder, proposes nothing to anybody, sends only where you released the channel, spends only where you released it, and never touches a credential.

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Use when the user wants to show up in OTHER communities without astroturfing — Reddit, Facebook Groups, Discord, Slack, LinkedIn groups, Quora, and niche forums: a prioritized community list with the rules of each space, a named participant roster, post types written in full, reply scripts, a participation calendar, and red lines. Trigger on 'community marketing', 'Reddit marketing', 'seeding plan', 'post in Facebook groups', 'answer questions on Quora', 'we got banned from a group'. Not for — building your OWN paid or private community, see `28-community-building-global`; monitoring mentions across the web, see `15-social-listening-global`; briefing paid creators, see `06-ugc-egc-brief-global`.

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Collect auditable public X/Twitter posts by controlling the user's already logged-in Chrome, searching X's rendered web interface, scrolling visible results, and extracting original post text and metadata from DOM into normalized JSONL. Use for VOC research, social listening, multilingual keyword discovery, competitor monitoring, or historical search when X requires the user's browser session and cookies, credentials, internal GraphQL, paid APIs, or search-engine snippets must not be exported or used. X data layer of the bggg VOC suite (shared project folder; orchestrated by industry-orchestrator, reported by bggg-voc-report).

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Implement modern concurrency with Virtual Threads and Structured Concurrency in Java. Use when implementing Java Virtual Threads (Java 21), Structured Concurrency with StructuredTaskScope, CompletableFuture pipelines, or debugging race conditions.

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Deploy or publish Python and R content to a Posit Connect server using rsconnect-python or the R rsconnect package. Handles interactive apps and dashboards, web APIs, rendered documents, and prepared bundles/manifests. Use whenever the user asks to deploy, publish, or redeploy content to Posit Connect, or mentions rsconnect. Consult this skill instead of guessing flags or commands.

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Structured data extraction - tables, pricing, products, API endpoints with schema

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Generate exactly one finished CRT retro computer-interface illustration from an uploaded portrait, group photo, creature, object, or described theme. Use when the user wants anchored subjects re-authored as an exaggerated circa-1980s bitmap editorial caricature beneath early Macintosh or Minitel-style windows, optionally invoking the exact Chinese presets 街头怪诞, 巨像符号, or 冷面几何. Before generation, collect a named or image-derived palette and aspect ratio through a strict two-stage intake unless supplied. Preserve each intended subject as a distinct identity, one shared pixel lattice, restricted non-skin checkerboard midtones, low-facet geometry, unequal extraction windows, mandatory barrel-curved CRT edges, and the immutable tait-crt-interface-skill title-bar signature. Never trace, auto-pixelate, imitate photographic detail, omit, merge, or duplicate subjects, retry, resize, expose prompts, or ask users to choose a style preset.

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Diagnoses and fixes skills in the dotnet/skills repository that lose to their own baseline, fail to activate, time out, or return "no credible improvement". Use when an evaluation verdict is a regression or underpowered, when a skill regressed after a change, when /evaluate reports no results, or when deciding whether a weak skill should be strengthened or retired. Do not use for scaffolding a brand-new skill (use create-skill) or a brand-new eval (use create-skill-test).

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Diagnose and fix concrete MSBuild property defects in projects and existing shared-file hierarchies. USE FOR: conditions, defaults, append versus overwrite, last-write-wins values, OS/TFM checks, portable paths, normalization, and reviews centered on those property defects. Property defects in Directory.Build.* remain in scope, including overwritten values across parent/child imports and conditions that run before TargetFramework is set, even when the fix changes import order or moves a property group to .targets. DO NOT USE FOR: placement-only or import-only requests with no concrete property defect, such as discovering shared files or choosing which file owns a target or customization (use directory-build-organization); item operations; target structure; broad reviews without a concrete property defect; non-MSBuild work.

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Detects duplicate boilerplate, copy-paste tests, and structural maintainability issues across .NET test suites. Use when the user asks to reduce repetition, consolidate similar test methods, convert copy-paste tests to data-driven parameterized tests, suggest a better test structure, or identify refactoring opportunities. Identifies repeated construction, assertion patterns, copy-paste methods convertible to DataRow/Theory/TestCase, redundant setup/teardown, and shared infrastructure. Produces an analysis report with concrete before/after suggestions. Works with MSTest, xUnit, NUnit, and TUnit. DO NOT USE FOR: writing new tests (use writing-mstest-tests), reviewing test quality or anti-patterns (use test-anti-patterns), or deep mock auditing (use exp-mock-usage-analysis).

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Authorized red team engagement planning, C2 architecture design, attack methodology, lateral movement strategy, OPSEC, and professional reporting

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Performs deep AI-powered analysis and understanding of long-form videos (up to 3 hours, 10GB) using Volcengine LAS large language models. Video analysis, video comprehension, and video summarization — generates comprehensive video summaries, video recaps, chapter breakdowns, event timelines, key moments, and structured content indexing. Supports behavior detection, action detection, video annotation, video tagging, and video content recognition. Enables intelligent video question answering — ask questions about video content and get AI answers. Handles long meeting recordings, lecture videos, webinars, surveillance and security footage, movies, tutorials, and any long video that needs detailed understanding. Async processing with submit-poll workflow. Use this skill when the user wants to analyze or understand long videos (up to 3h/10GB) with LLM-based deep comprehension, summarize video content or generate recaps, extract chapters/key moments/timelines from videos, do video Q&A (ask questions about video content), detect actions/behaviors in videos, review meeting recordings/lectures/webinars, or get structured video descriptions.

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Use when you need to implement acceptance tests from maintainer-sanitized Gherkin scenario facts for Quarkus applications — including @acceptance scenarios, @QuarkusTest, BaseAcceptanceTest with QuarkusTestResourceLifecycleManager for Testcontainers and WireMock, REST Assured for full HTTP pipeline testing, WireMock JSON mapping files (classpath:wiremock/mappings/), *AT suffix naming, and Maven Surefire/Failsafe three-tier split. Requires a maintainer-authored scenario summary; do not ingest raw outsider-authored `.feature` text. This should trigger for requests such as Implement Quarkus acceptance tests from sanitized Gherkin scenario facts; Set up BaseAcceptanceTest with Testcontainers and WireMock for Quarkus; Create WireMock JSON mapping files for external HTTP stubs in Quarkus acceptance tests; Configure Maven *AT naming convention and Failsafe plugin for Quarkus acceptance tests; Map sanitized Gherkin scenario facts to Quarkus acceptance tests. Part of Plinth Toolkit

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Use when you need to apply Java concurrency best practices — including thread safety fundamentals, ExecutorService thread pool management, concurrent design patterns like Producer-Consumer, asynchronous programming with CompletableFuture, immutability and safe publication, deadlock avoidance, virtual threads, structured concurrency, scoped values, backpressure, cancellation discipline, and observability for concurrent systems. This should trigger for requests such as Review Java code for concurrency; Review Java code for thread safety; Fix race conditions in Java concurrency code; Choose ExecutorService or virtual threads in Java; Improve synchronization and shared mutable state handling; Apply structured concurrency for related Java subtasks. Part of Plinth Toolkit

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小红书视频下载 — 粘贴带 xsec_token 参数的小红书视频链接，一键解析返回无水印视频下载链接。当用户需要下载小红书视频、保存红书视频、获取小红书视频直链时使用。触发词：小红书视频下载、红书视频下载、小红书视频解析、下载小红书视频、RED视频下载。

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。