「anti」の検索結果

Work with any Upstash product, SDK, or tool, including serverless Redis (caching, sessions, leaderboards, key-value storage), Ratelimit (rate limiting and throttling), QStash (message queue, cron schedules, background jobs), Workflow (durable long-running functions), Vector (vector database for embeddings, semantic search, and RAG), Search (full-text and semantic search), Box (sandboxed cloud containers for AI agents, TypeScript/JavaScript and Python), Blob (serverless S3-compatible file storage with direct browser uploads), the Upstash CLI, and no-signup scratch Redis for agents. Use when the user mentions Upstash or needs any of these capabilities in a serverless, edge, or Node.js app.

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。

Work with the @upstash/vector TypeScript/JavaScript SDK, a serverless vector database for embeddings, similarity search, semantic search, and RAG (retrieval-augmented generation). Use when upserting, querying, fetching, ranging, or deleting vectors, upserting raw text against an index with a built-in embedding model, choosing dense, sparse, or hybrid indexes, filtering by metadata, organizing data with namespaces, running resumable queries, or connecting Upstash Vector to an AI or LLM application. Also use when the user asks for a vector store, vector search, nearest-neighbor or kNN search, embeddings storage, semantic cache, recommendations or similarity features, or a hosted vector index that needs no infrastructure.

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 explore an Obsidian vault through the NoteBrain CLI (semantic search, tags, backlinks, connections, hidden links, boosted retrieval). Use it whenever the user mentions their notes, knowledge base, Obsidian vault, semantic search, finding connections or unlinked notes, or asks exploratory questions like "what do I know about X", "find notes related to Y", "what connects to Z", or "summarize my notes on W" — even when they never say NoteBrain, vector search, or ChromaDB.

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 a professional LinkedIn presence end-to-end using Claude: daily posting with pillar calendar, engagement with anti-detection rules, DM triage, reporting, and growth tracking. Use when the user wants to automate LinkedIn, manage a profile with AI, create a content strategy, or set up engagement automation. Triggers on: "automate my LinkedIn", "LinkedIn automation", "automated LinkedIn", "LinkedIn bot", "LinkedIn scheduling", "LinkedIn AI management", "LinkedIn content calendar", "LinkedIn engagement strategy", "build a LinkedIn presence", "can Claude manage my LinkedIn", "how do I automate my LinkedIn", or any request involving systematic LinkedIn content creation, audience growth, or profile management. Covers: identity/TOV setup, pillar calendar, post creation, engagement rules, anti-detection, scheduled task creation, and weekly 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。

Create reproducible animated infographic GIFs from structured data or measured results, with audience-language labels, explicit timing semantics, representative-frame QA, and a static fallback. Use when asked for GIF生成, animated infographic, 動的インフォグラフィック, 結果が流れる図, animated benchmark, or a blog/SNS animation whose displayed metrics must remain traceable to source data.

houtu-dependencies enterprise-grade Spring Cloud microservice foundational framework complete usage guide. GroupId is io.github.lujiafa, covering unified response, exception handling, parameter parsing, session authentication, permission control, signature verification, anti-replay, distributed lock, rate limiting, database field encryption, config decryption, access logging, canary routing, weighted load balancing, Feign enhancement, Sentinel circuit breaking, service discovery, Swagger documentation, crypto utilities, HTTP client, monitoring metrics, and other enterprise-grade capabilities. When the project build file (pom.xml or build.gradle/build.gradle.kts) contains io.github.lujiafa or houtu-related dependencies, or when the user mentions houtu or houtu-dependencies, this Skill must be read and code must be generated strictly following framework conventions. Even if the user is simply doing regular Spring Boot development (e.g., writing Controller, Service, Feign), as long as the project includes houtu, the houtu approach must be used instead of native Spring. When the user explicitly wants to use the houtu framework and the project has not yet included it, proactively add the BOM and required Starters; when the project already includes it, proactively identify and import required module dependencies based on business scenarios during coding, naturally integrating framework capabilities to enhance business services based on business semantics, rather than waiting for the user to specify each one.

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 and conduct mixed methods research using convergent, explanatory sequential, or exploratory sequential strategies with genuine integration of qualitative and quantitative strands. Use this skill when the user needs to choose a mixed methods design, integrate qualitative and quantitative data at design, methods, or interpretation levels, justify mixing on pragmatist grounds, or when they ask 'which mixed methods design should I use', 'how do I integrate qual and quant findings', or 'is running both qual and quant enough to be mixed methods'.".

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 prose writing and audit skill. Apply for writing, editing, or reviewing prose, and for explicit requests to score text or flag formulaic AI-writing patterns. Do not activate for ordinary factual, code, or configuration tasks.

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。

Anti-debugging detection and bypass playbook. Use when reversing protected binaries that detect debuggers via ptrace, PEB flags, timing checks, or signal/exception handlers on Linux and Windows.

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 building Django REST APIs with django-ninja - Pydantic schemas, routers, CRUD endpoints, authentication, pagination, file uploads, async views, OpenAPI docs, or migrating from DRF

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。

Mantine v7 component library — theming, styling, hooks, forms, notifications

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。

Idiomatic modern C++: RAII, smart pointers, move semantics, value semantics, STL algorithms, and safe concurrency. Use when writing, reviewing, or structuring C++ 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。

Instantiates prefab in the current active scene. Use 'assets-find' tool to find prefab assets in the project.

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。

Analyzes git commit history and generates professional changelogs with semantic versioning, conventional commit support, and multiple output formats (Keep a Changelog, Conventional, GitHub). Use when editing CHANGELOG.md, CHANGELOG.txt, or HISTORY.md files, preparing release notes, creating releases, bumping versions, updating changelog, documenting changes, writing release notes, tracking changes, version bump, tag release, or when user mentions "changelog", "release notes", "version history", "release", "semantic versioning", or "conventional commits".

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。

Transform reference photographs and visually dense images into sparse, recognizable, high-saturation flat-vector-style illustrations through semantic compression rather than literal tracing. Use when the user asks for photo-to-flat illustration, photo-to-vector-style redraw, 照片转扁平插画, 无渐变高饱和插画, iconification, visual simplification, composition-preserving abstraction, a consistent minimal illustration set, or revisions that remove gradients, glow, texture, blur, clutter, text, logos, numbers, or UI. Default to human-perceived semantic complexity 6 out of 10 or lower, fixed-HSB solid fills, crisp boundaries, and no gradients or light-halo effects.

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。

Parse natural-language quantities, units, dates, and ranges ("5'11\"", "1.5 cups", "72 in to cm", "three days ago", "between 5 and 10 kg", "it's hot") into canonical, validated values with issue codes and spans — and humanize them back. Use when a form input, LLM tool schema, MCP handler, or import pipeline takes free-text measurements/units/dates. Covers Standard Schema fields (quantityField/dateField/lingoObject) for the AI SDK and MCP, the headless <lingo-input>, unit conversion, and format/humanize round-trips. Zero-dependency TypeScript, deterministic.

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。

Discovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.

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。

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management 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。

Use when configuring the Salesforce product catalog and pricing structure: creating Product2 records, setting up Standard and custom Pricebooks, managing PricebookEntry junction records, enabling multi-currency pricing, configuring Product Schedules (Revenue and Quantity), or troubleshooting incorrect prices on Opportunity line items and Quotes. Triggers: 'add product to pricebook', 'pricebook entry', 'standard pricebook', 'product catalog', 'multi-currency product pricing', 'product schedule', 'revenue schedule', 'quantity schedule', 'deactivate product'. NOT for bulk catalog loads — use data/product-catalog-data-model. NOT for CPQ bundles and product rules — use admin/cpq-product-catalog-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。

Run the same scrape or task across many accounts at once - each in its own browser profile with its own fingerprint, cookies and exit IP - and read data from sites that need a session or that answer a plain HTTP scraper with a captcha while answering a real browser. One command per site returns JSON, so there are no selectors to write or repair: Amazon and Walmart search, Google and DuckDuckGo results, Reddit posts and comments, X timeline, Medium, Yelp, Indeed job listings, Hacker News, GitHub, PyPI, npm, plus exit-IP and fingerprint checks. Use for multi-account operations you are authorized to run, price and listing monitoring per region, SERP collection, logged-in data, and scrapers that keep breaking. Also for 'scrape amazon', 'google search results', 'reddit data', 'scrape logged in site', 'run task on many accounts', 'site blocks my scraper', 'scraping without selectors'. Node or Python.

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。

Semantic Design System Skill for Google Stitch. Generates agent-friendly DESIGN.md files that enforce premium, anti-generic UI standards — strict typography, calibrated color, asymmetric layouts, perpetual micro-motion, and hardware-accelerated performance.

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。

Drafts board-ready Anti-Money Laundering compliance programs for U.S. financial institutions under BSA/FinCEN requirements. Covers CIP, CDD, EDD, SAR/CTR reporting, OFAC screening, risk assessment, training, independent testing, and governance structures. Use when creating or updating AML policies, BSA compliance programs, or financial institution regulatory documentation. Trigger keywords: AML, BSA, FinCEN, Bank Secrecy Act, anti-money laundering, SAR, CTR, OFAC, CIP, CDD, KYC, compliance program.

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。

Drafts FDA 510(k) Premarket Notification submissions demonstrating substantial equivalence under 21 CFR Part 807. Supports Traditional, Special, and Abbreviated pathways. Use when preparing Class II medical device regulatory filings, substantial equivalence analyses, or FDA premarket submissions.

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。

Generate or update docs/project-context.md — the single source of truth for project conventions, tech stack, and anti-patterns. Loaded by all agents as a "constitution" to ensure consistent behavior.

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。