Modular orchestration of agent patterns from Anthropic's engineering guide. Intelligently selects and implements prompt chaining, routing, parallelization, orchestrator-workers, evaluator-optimizer, and autonomous agents. Includes pattern combinations and language-specific implementations.
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Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational content.
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Core principles and golden rules for writing production-quality Ansible automation, covering FQCN requirements, module selection guidance, and execution patterns using uv run.
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Secure secrets handling in Ansible with Infisical vault integration, no_log directive enforcement, and a reusable Infisical lookup task for safe credential retrieval.
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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?'
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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.
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Authentication and authorization patterns - JWT, OAuth2, sessions, RBAC, ABAC, passkeys, and MFA. Use for: authentication, authorization, jwt, oauth, oauth2, session, login, rbac, abac, passkey, mfa, totp, api key, token, auth, cookie, csrf, cors credentials, bearer token, refresh token, oidc.
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Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
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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.
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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)
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Astro framework patterns, islands architecture, content collections, rendering strategies, and deployment. Use for: astro, islands architecture, content collections, astro cloudflare, view transitions, partial hydration, astrojs, SSG, SSR, hybrid rendering, astro adapter.
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Create ASP.NET Minimal API endpoints with proper OpenAPI documentation
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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.
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INVOKE THIS SKILL when downloading or exporting Arize traces and spans. Covers exporting traces by ID, sessions by ID, and debugging LLM application issues using the ax CLI.
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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.
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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.
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Testing strategies and ansible-lint configuration for validating Ansible automation quality, covering lint rules, syntax validation, and integration test setup.
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Identify all files a specific author contributed to on a branch vs its upstream, tracing code through renames. Use when asked who edited what, what code an author contributed, or to audit authorship before a merge. This skill should be run as a subagent — it performs many git operations and returns a concise table.
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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.
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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.
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Instrument a webapp to send useful telemetry data to Azure App Insights
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INVOKE THIS SKILL when creating, managing, or using annotation configs on Arize (categorical, continuous, freeform), or applying human annotations to project spans via the Python SDK. Configs are the label schema for human feedback on spans and other surfaces in the Arize UI. Triggers: annotation config, label schema, human feedback schema, bulk annotate spans, update_annotations.
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Triage and resolve Arch Linux issues with pacman, systemd, and rolling-release best practices.
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Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.
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