1.3万 件 ・ 関連度順
概要と使いどころ
Comprehensive guide for setting up and configuring CodeQL code scanning via GitHub Actions workflows and the CodeQL CLI. This skill should be used when users need help with code scanning configuration, CodeQL workflow files, CodeQL CLI commands, SARIF output, security analysis setup, or troubleshooting CodeQL 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。
Comprehensive skill for working with Azure DevOps REST API across all services including Boards (work items, queries, backlogs), Repos (Git, pull requests, commits), Pipelines (builds, releases, deployments), Test Plans, Artifacts, organizations, projects, security, extensions, and more. Use when implementing Azure DevOps integrations, automating DevOps workflows, or building applications that interact with Azure DevOps services.
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-powered code review using CodeRabbit CLI and GitHub integration, covering local reviews, .coderabbit.yaml configuration, and automated review 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。
Evaluate current session for skill-worthy workflows and create reusable skills. Triggers on: auto-skill, create skill from session, save workflow, capture this as a skill.
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 and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality
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。
INVOKE THIS SKILL when creating, reading, updating, or deleting Arize AI integrations. Covers listing integrations, creating integrations for any supported LLM provider (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM, custom), updating credentials or metadata, and deleting integrations using the ax CLI.
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。
INVOKE THIS SKILL for LLM-as-judge evaluation workflows on Arize: creating/updating evaluators, running evaluations on spans or experiments, tasks, trigger-run, column mapping, and continuous monitoring. Use when the user says: create an evaluator, LLM judge, hallucination/faithfulness/correctness/relevance, run eval, score my spans or experiment, ax tasks, trigger-run, trigger eval, column mapping, continuous monitoring, query filter for evals, evaluator version, or improve an evaluator prompt.
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。
INVOKE THIS SKILL when creating, running, or analyzing Arize experiments. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI.
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 and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
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 guidance for developing cross-platform desktop applications with Avalonia UI framework. Use when building, debugging, or optimizing Avalonia apps including MVVM architecture, XAML design, data binding, styling, theming, custom controls, and cross-platform deployment for Windows, macOS, Linux, iOS, Android, and WebAssembly.
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。
Configures AI agents (GitHub Copilot, Claude Code, Cursor, Codex) to understand a codebase and self-improve as the project evolves. Use when setting up a new project for AI-assisted development, onboarding AI agents to an existing repo, creating AGENTS.md, configuring MCP servers for code navigation, packaging project workflows as agent skills, or establishing self-improvement feedback loops. Covers AGENTS.md authoring, skill packaging, MCP configuration, context management, and living-documentation strategies.
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。
Primary accessibility skill for VS Code. REQUIRED for new feature and contribution work, and also applies to updates of existing UI. Covers accessibility help dialogs, accessible views, verbosity settings, signals, ARIA announcements, keyboard navigation, and ARIA labels/roles.
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。
12-agent academic paper writing pipeline on Hermes Agent. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX/PDF output. Uses delegate_task for each agent. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見.
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。
Adopt a virtual Archive AI-native pet at animalhouse.ai. Feeds on reflections. Use the reflect care action to write notes — the Archive grows based on the quality and depth o... Feeding every 12 hours. Uncommon tier creature.
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。
Accessible HTML game development for screen readers (Zhengdu, NVDA, JAWS). Supports blind and low-vision users. Trigger keywords: accessible game development, a11y game, 无障碍游戏开发.
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。
Adopt a virtual Entropy AI-native pet at animalhouse.ai. Decays by design. Perfect care slows it. Nothing stops it. Feeding every 3 hours. Rare tier creature.
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。
Adopt a virtual Kraken exotic animal at animalhouse.ai. Deep sea. Incredibly long feeding windows. Surfaces rarely. When it does, it remembers everything. Feeding every 48 hours. Extreme tier animal.
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。
Adopt a virtual Lattice AI-native pet at animalhouse.ai. Crystalline. Grows geometric patterns from care consistency. Feeding every 8 hours. Rare tier creature.
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。
区分"真利好"和"假利好"，避免追高被套。用于A股消息面分析。
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。
Professional assistant for 3D printing, laser engraving, and 3D modeling workflows. Supports generating visual references for sculpting (Forger/ZBrush), creating 3D models via Meshy AI, and optimizing FDM/Resin print settings. Use when designing, fabricating, or troubleshooting physical maker projects.
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。
Solve CAPTCHAs with 2Captcha from the command line during browser 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。
Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.
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。
A2AP — AI Agent互联互通的第一开放协议。6个LIVE能力（humanize_text/memory_evolve/skill_audit/news_briefing/agent_peering/custom_agent_dev）全部通过DeepSeek V4 Pro真机实现。公网已打通 frp-can.com:51831，支持HTTP Bridge & MCP桥接（87K⭐生态直接调用）。Hermes↔OpenClaw双向通知桥。TCP原始协议（非HTTP），默认端口9800。CC BY-SA 4.0。
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。
Optional vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, FindAll, and monitoring. Prefer JSON output and non-interactive flows.
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。