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概要と使いどころ
Use when working with Aws Rightsizing — analyze EC2, RDS, EBS, and Lambda resource utilization to identify right-sizing opportunities. Uses CloudWatch metrics with anti-hallucination rules for burstable instances, memory metrics, peak vs average analysis, and estimated monthly savings calculations.
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 working with Semgrep — semgrep static application security testing (SAST). Covers code scanning, custom rule creation, CI integration, autofix capabilities, multi-language support, and vulnerability triage. Use when scanning source code for security vulnerabilities, creating custom detection rules, or integrating SAST into CI pipelines.
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。
F16 on BitNet-embedding-270M prefill (8 threads) Supports I2_S conversion with optimized kernels on x86 CPUs Lossless inference with 2 bits per weight
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。
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
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。
Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.
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 Vercel cost and performance optimization on deployed projects, especially Next.js, SvelteKit, Nuxt, and limited Astro apps. Collect Vercel metrics, usage, project config, and code scan results first; investigate only metric-backed candidates; produce ranked recommendations grounded in verified files and version-aware Vercel/framework docs. Trigger for Vercel bill reduction, slow or expensive routes, caching opportunities, Function Invocations, Build Minutes, Fast Data Transfer, Core Web Vitals, Bot Management, Fluid compute, or cost breakdown 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。
Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning). Supports SFT, DPO, GRPO, KTO, RLOO and Reward Model training via CLI commands.
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 Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.
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。
Implement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.
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。
Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정.
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。
Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security 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。
Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.
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。
Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related 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。
Flip core assumptions to reveal hidden constraints and alternative approaches - "what if the opposite were true?
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。
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.
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。
Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
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。
Scan a codebase for deepening opportunities, present them as a visual HTML report, then guide a user-directed decision loop for the selected candidate.
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。
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
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。
Audit and rewrite content to remove AI writing patterns ("AI-isms"). Supports detect-only audits, edit-in-place file cleanup, voice and context profiles, and an iterate-to-convergence pass.
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。
Audit and improve web accessibility following WCAG 2.2 guidelines. Use when asked to "improve accessibility", "a11y audit", "WCAG compliance", "screen reader support", "keyboard navigation", or "make accessible".
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 QA exploratoire v4 (tests systématiques, chasse aux bugs, preuves, rapports, régression)
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 accessibilité des agents IA (support lecteurs d'écran, interfaces vocales, multilingue, UX simplifiée)
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 migration of .NET Framework Thread.Abort usage to cooperative cancellation in modern .NET. USE FOR: modernizing code that calls Thread.Abort, catching ThreadAbortException, replacing Thread.ResetAbort, replacing Thread.Interrupt for thread termination, resolving PlatformNotSupportedException or SYSLIB0006 after retargeting to .NET 6+, migrating ASP.NET Response.End or Response.Redirect(url, true) which internally call Thread.Abort. DO NOT USE FOR: code that only uses Thread.Join, Thread.Sleep, or Thread.Start without any abort, interrupt, or ThreadAbortException usage — these APIs work identically in modern .NET and need no migration. Also not for projects staying on .NET Framework, or Thread.Abort usage inside third-party libraries you do not control.
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 devcontainers with Claude Code, language-specific tooling (Python/Node/Rust/Go), and persistent volumes. Use when adding devcontainer support to a project, setting up isolated development environments, or configuring sandboxed Claude Code workspaces.
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。