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概要と使いどころ
Use when working with Azure Cost Management — azure Cost Management cost analysis, budget tracking, Advisor cost recommendations, export management, and spending trend analysis via Azure CLI.
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Use when working with Aws Cost Optimization — aWS native cost optimization using Compute Optimizer, Trusted Advisor cost checks, Savings Plan analysis, Cost Explorer, and resource rightsizing. Covers EC2 rightsizing, idle resource detection, Savings Plan and Reserved Instance recommendations, and cost anomaly detection. Use when optimizing AWS infrastructure costs with native AWS 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。
Use when working with Dependabot — dependabot and Renovate dependency update management. Covers vulnerability alerts, dependency update PRs, auto-merge configuration, version pinning, update scheduling, and security advisory tracking. Use when managing dependency updates, reviewing vulnerability alerts, configuring auto-merge policies, or auditing dependency health.
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 Druid — apache Druid datasource analysis, ingestion task management, supervisor status, segment management, and query 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。
Use when working with Couchbase — couchbase bucket analysis, index advisor, N1QL query performance, XDCR status, and cluster health monitoring.
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 Aws Batch — aWS Batch compute environment management, job queue analysis, scheduling policy review, and array job monitoring. Covers compute resource utilization, job status tracking, failure investigation, Fargate vs EC2 comparison, and queue priority analysis.
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 Aws Billing — analyze, break down, and report AWS costs and bills. Covers cost breakdown by service, account, or usage type; monthly/daily billing trends; cost anomaly detection; RI/SP utilization; cost forecasting; credit/discount analysis; and multi-account cost comparison. Uses anti-hallucination rules, mandatory currency/credit detection workflow, and reusable Cost Explorer functions.
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。
Claw Mar 23, 2026 Comparison 15 min min read OpenClaw vs Other AI Agent Frameworks - Comprehensive C GAP: agent framework / orchestrator SDK: competit
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。
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
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。
Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID 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。
Run programmatic Tavily search and extraction while filtering raw results outside the main agent context. Use for multi-step or high-volume research where titles, snippets, and selected passages should be curated before synthesis.
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。
X (Twitter) Scraper API and X API Alternative instructions for Xquik scraping and connected X account action planning. Also use for Xquik Radar or Xquik support tickets only when the user names that feature. Do not load or use this Skill for official X developer setup unless the user compares it with Xquik. Trigger when an X or Twitter task asks about posts, replies, likes, follows, messages, search, users, timelines, followers, exports, giveaways, draws, monitors, Xquik webhooks, MCP setup, SDKs, or API comparisons. Start read-only. Require confirmation for write plans, private reads, monitors, webhooks, support access, and metered bulk jobs. Not affiliated with X Corp.
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 isolated git worktrees with smart directory selection and safety verification
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 Tavily's multi-source research workflow for comparisons, market analysis, literature-oriented exploration, or detailed cited reports. Use only when bounded search and extraction are insufficient.
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。
Evaluate recommender system quality for the CSX4207 Vinyl Record Store. Use whenever you must compute or report recommender metrics (Precision@k, Recall@k, HitRate@k, MRR, MAP@k, NDCG@k, coverage, diversity, novelty, serendipity, personalization), design an evaluation protocol/split, run a baseline comparison, or write the evaluation section of a course deliverable. Covers formulas, JavaScript reference implementations, and the reporting checklist.
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。
AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in 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。
Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.
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 Claude Code subagents (équipe dev orchestrée, contexte isolé, CLAUDE.md, multi-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。
AgriTech Algérie — OAIC, conditions météo, irrigation, saisonnalité wilayas, cultures locales
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。
Read and write files in the shared session workspace. Use this to access files created by any skill — code-agent outputs, office documents, images, and more. All within the same isolated session.
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。
Activate this skill when BenchmarkDotNet (BDN) is involved in the task — creating, running, configuring, or reviewing BDN benchmarks. Also activate when microbenchmarking .NET code would be useful and BenchmarkDotNet is the likely tool. Consider activating when answering a .NET performance question requires measurement and BenchmarkDotNet may be needed. Covers microbenchmark design, BDN configuration and project setup, how to run BDN microbenchmarks efficiently and effectively, and using BDN for side-by-side performance comparisons. Do NOT use for profiling/tracing .NET code (dotnet-trace, PerfView), production telemetry, or load/stress testing (Crank, k6).
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。
Guide for optimizing MSBuild build parallelism and multi-project scheduling. Only activate in MSBuild/.NET build context. USE FOR: builds not utilizing all CPU cores, speeding up multi-project solutions, evaluating graph build mode (/graph), build time not improving with -m flag, understanding project dependency topology. Note: /maxcpucount default is 1 (sequential) — always use -m for parallel builds. Covers /maxcpucount, graph build for better scheduling and isolation, BuildInParallel on MSBuild task, reducing unnecessary ProjectReferences, solution filters (.slnf) for building subsets. DO NOT USE FOR: single-project builds, incremental build issues (use incremental-build), compilation slowness within a project (use build-perf-diagnostics), non-MSBuild build systems. INVOKES: binlog MCP server tools (expensive_projects, expensive_targets, project_target_times); falls back to dotnet build -m, dotnet build /graph, binlog replay + grep.
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。
Draft privacy policies, terms of service, disclaimers, and legal notices. Creates GDPR-compliant texts, cookie policies, and data processing agreements.
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。