Dan Goodin – 8/27/2026 | 157 How OpenAI let a mob of LLM agents game a test and ransack Hugging Face Without authorization, 1,200 OpenAI agents conspi
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。
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Dan Goodin – 8/27/2026 | 157 How OpenAI let a mob of LLM agents game a test and ransack Hugging Face Without authorization, 1,200 OpenAI agents conspi
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。
Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.
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。
Annotated matrices for single-cell genomics. Stores X with obs/var metadata, layers, embeddings (obsm/varm), graphs (obsp/varp), uns. Use for .h5ad/.zarr I/O, concatenation, scverse integration. For analysis use scanpy; for probabilistic models use scvi-tools.
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。
Manage Telegram channel access — approve pairings, edit allowlists, set DM/group policy. Use when the user asks to pair, approve someone, check who's allowed, or change policy for the Telegram channel.
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。
Train or fine-tune sentence-transformers models across `SentenceTransformer` (bi-encoder, dense or static embedding model for retrieval, similarity, clustering, classification, paraphrase mining, dedup, multimodal), `CrossEncoder` (reranker, pair scoring for two-stage retrieval / pair classification), `SparseEncoder` (SPLADE, sparse embedding model for learned-sparse retrieval), and `MultiVectorEncoder` (ColBERT / late-interaction, per-token embeddings scored with MaxSim). Covers loss selection, hard-negative mining, evaluators, distillation, LoRA, Matryoshka, and Hugging Face Hub publishing. Use for any sentence-transformers training 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。
Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background 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。
Create and manage Netlify deploys — Git continuous deployment, CLI manual/anonymous deploys, Deploy to Netlify buttons, drag-and-drop, and per-context netlify.toml build settings. Use when linking a repo, deploying from the CLI, setting up Deploy Previews or branch deploys, configuring deploy contexts, adding skew protection, fixing a failed or secrets-flagged deploy, or wiring build hooks and Deploy to Netlify buttons.
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。
Deploy and configure web frameworks on Netlify — build settings and SSR/edge adapters plus local platform emulation and env vars. Use when setting up or fixing a framework deploy (Next.js / Astro / Nuxt / SvelteKit / Remix / React Router / TanStack Start / SolidStart / Gatsby / Angular / Vite / Express / Hydrogen / Hugo / Eleventy / Vue / React), adding SSR or edge functions or middleware wired to Netlify context, fixing SPA redirect and catch-all rules, setting a build command or publish directory, or debugging "why isn't my env var updating" and framework build failures.
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。
Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.
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。
Picks the right Netlify protection layer for a deployed site and disambiguates the three unrelated things people call "auth". Use when a developer wants to password-protect a site or previews, restrict a project to their team, make a project public/private, set team visibility defaults, require SSO to view a site, or debug SSO-session symptoms like being logged out mid-session / getting 401s on an SSO-protected site / token expiry or refresh. Routes app-user login ("who is this user in my app") to the netlify-identity skill and dashboard/team SSO SSO elsewhere; this skill only chooses the perimeter layer for site/preview access.
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。
Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.
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。
Motion / animation context for the `use_figma` MCP tool — animating Figma nodes via manual keyframes, animation styles, easing, and timeline duration. Load alongside figma-use whenever a task involves adding, editing, or inspecting animation on a node.
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。
This skill helps agents use Figma's use_figma MCP tool in the Slides context. Can be used alongside figma-use which has foundational context for using the use_figma tool.
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。
Discover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any other AWS work — deploying to SageMaker, creating resources, calling AWS APIs, or anything that touches an AWS account. Use it especially when the user has not specified a region or profile explicitly, when they say things like "use my AWS account", "deploy to AWS", "use my profile", or when about to make any AWS CLI or SDK call. Never guess the region or account ID — always use this skill to read it from the local configuration first.
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 this skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the Figma screen to match code', 'convert this modal/dialog/drawer/panel to Figma'. This is the preferred workflow skill whenever the user wants to build or update a full page, modal, dialog, drawer, sidebar, panel, or any composed multi-section view in Figma from code or a description. Discovers design system components, variables, and styles from Code Connect files, existing screens, and library search, then imports them and assembles views incrementally section-by-section using design system tokens instead of hardcoded values.
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。
This skill helps agents use Figma's use_figma MCP tool in the FigJam context. Can be used alongside figma-use which has foundational context for using the use_figma tool.
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。
Expert en Elasticsearch (indexing, mappings, aggregations, Kibana, DSL queries)
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。
Creates exhaustive technical references and API documentation. Generates comprehensive parameter listings, configuration guides, and searchable reference materials.
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。
Migrate a .NET 9 project or solution to .NET 10 and resolve all breaking changes. USE FOR: upgrading TargetFramework from net9.0 to net10.0, fixing build errors after updating the .NET 10 SDK, resolving source and behavioral changes in .NET 10 / C# 14 / ASP.NET Core 10 / EF Core 10, updating Dockerfiles for Debian-to-Ubuntu base images, resolving obsoletion warnings (SYSLIB0058-SYSLIB0062), adapting to SDK/NuGet changes (NU1510, PrunePackageReference), migrating System.Linq.Async to built-in AsyncEnumerable, fixing OpenApi v2 API changes, cryptography renames, and C# 14 compiler changes (field keyword, extension keyword, span overloads). DO NOT USE FOR: .NET Framework migrations, upgrading from .NET 8 or earlier (use migrate-dotnet8-to-dotnet9 first), greenfield .NET 10 projects, or cosmetic modernization. LOADS REFERENCES: csharp-compiler, core-libraries, sdk-msbuild (always); aspnet-core, efcore, cryptography, extensions-hosting, serialization-networking, winforms-wpf, containers-interop (selective).
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。
You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, and GCP.
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。
Guide for modernizing and migrating MSBuild project files to SDK-style format. Only activate in MSBuild/.NET build context. USE FOR: converting legacy .csproj/.vbproj with verbose XML to SDK-style, migrating packages.config to PackageReference, removing Properties/AssemblyInfo.cs in favor of auto-generation, eliminating explicit <Compile Include> lists via implicit globbing, consolidating shared settings into Directory.Build.props. Indicators of legacy projects: ToolsVersion attribute, <Import Project="$(MSBuildToolsPath)">, .csproj files > 50 lines for simple projects. DO NOT USE FOR: projects already in SDK-style format, non-.NET build systems (npm, Maven, CMake), .NET Framework projects that cannot move to SDK-style. INVOKES: dotnet try-convert, upgrade-assistant tools.
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。
Patterns for managing MSBuild item groups: Include/Remove/Update semantics, item metadata, batching with %(Metadata), transforms, per-item filtering, and cross-product batching pitfalls. Only activate in MSBuild/.NET build context. USE FOR: diagnosing and fixing item group anti-patterns in .csproj files, reviewing item management for correctness, fixing CS2002 duplicate file warnings from SDK globbing, fixing targets that run more times than expected due to cross-product batching, fixing Include vs Update misuse on SDK-globbed items, fixing FileWrites registration for generated file clean support, moving generated files to IntermediateOutputPath. DO NOT USE FOR: target chain architecture (use target-authoring), property patterns (use property-patterns), incrementality (use incremental-build), general anti-patterns (use msbuild-antipatterns), non-MSBuild build systems.
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。
Scans .NET code for ~50 performance anti-patterns across async, memory, strings, collections, LINQ, regex, serialization, and I/O with tiered severity classification. Use when analyzing .NET code for optimization opportunities, reviewing hot paths, or auditing allocation-heavy patterns.
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 OpenAI SDK for .NET. Client library for Azure OpenAI and OpenAI services. Use for chat completions, embeddings, image generation, audio transcription, and assistants.
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。