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Implements robust error handling in Ansible using block/rescue/always patterns, retry logic with until/retries, and clear assertion patterns for graceful failure management.

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。

Techniques for writing truly idempotent Ansible tasks using changed_when, failed_when, and check-before-create patterns to eliminate spurious "changed" reports.

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。

Act on user feedback attached to the current session. Use when the user submits feedback on the session's changes via the Submit Feedback button.

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。

Analyze a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine.

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 optimizing, improving, or debugging LLM prompts using production trace data, evaluations, and annotations. Covers extracting prompts from spans, gathering performance signal, and running a data-driven optimization loop 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 for designing well-structured, maintainable Ansible playbooks with state-based (present/absent) design, play organization, and proper variable scoping.

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 adding Arize AX tracing to an application. Follow the Agent-Assisted Tracing two-phase flow: analyze the codebase (read-only), then implement instrumentation after user confirmation. When the app uses LLM tool/function calling, add manual CHAIN + TOOL spans so traces show each tool's input and output. Leverages https://arize.com/docs/ax/alyx/tracing-assistant and https://arize.com/docs/PROMPT.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。

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。

Expert Proxmox VE automation using the community.proxmox Ansible collection for VM provisioning, template management, and cluster operations with minimal CLI usage.

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。

Secure secrets handling in Ansible with Infisical vault integration, no_log directive enforcement, and a reusable Infisical lookup task for safe credential retrieval.

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。

Testing strategies and ansible-lint configuration for validating Ansible automation quality, covering lint rules, syntax validation, and integration test 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。

Use this agent when the user needs to upgrade Anthropic SDK packages. This includes: upgrading @anthropic-ai/sdk or @anthropic-ai/claude-agent-sdk to newer versions, migrating between SDK versions, resolving SDK-related dependency conflicts, updating SDK types and interfaces, or asking about SDK upgrade procedures. Examples: 'Upgrade the Anthropic SDK to the latest version', 'Help me migrate to the latest claude-agent-sdk', 'What's the process for upgrading Anthropic packages?'

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 project architecture blueprint generator that analyzes codebases to create detailed architectural documentation. Automatically detects technology stacks and architectural patterns, generates visual diagrams, documents implementation patterns, and provides extensible blueprints for maintaining architectural consistency and guiding new development.

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。

API design patterns for REST, gRPC, and GraphQL. Use for: api design, REST, gRPC, GraphQL, protobuf, schema design, api versioning, pagination, rate limiting, error format, OpenAPI, API authentication, JWT, OAuth2, API gateway, webhook, idempotency.

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。

Triage and resolve Arch Linux issues with pacman, systemd, and rolling-release best practices.

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。

Aspire skill covering the Aspire CLI, AppHost orchestration, service discovery, integrations, MCP server, VS Code extension, Dev Containers, GitHub Codespaces, templates, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application.

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。

Create ASP.NET Minimal API endpoints with proper OpenAPI documentation

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。

Atom of Thoughts (AoT) reasoning - decompose complex problems into atomic units with confidence tracking and backtracking. For genuinely complex reasoning, not everyday questions. Triggers on: atomise, complex reasoning, decompose problem, structured thinking, verify hypothesis.

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。

Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.

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。

Expert GNU awk (gawk) one-liner generation and transformation. Use this skill whenever the user asks to process text fields, extract columns, compute sums or aggregates, filter structured output, reformat CSV/TSV, parse logs, generate reports, or do any record/field processing task. Trigger on keywords like "awk", "extract column", "sum a field", "count occurrences", "print field N", "filter by column", "reformat output", "aggregate log data", "process CSV", "TSV", or any request that maps to a field-oriented text transformation. When in doubt, use this skill — awk is often the right tool when sed isn't enough.

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 deep links to the Arize UI. Use when the user wants a clickable URL to open a specific trace, span, session, dataset, labeling queue, evaluator, or annotation config.

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。