'orm' 검색 결과

Create a formal specification for an existing GitHub Actions CI/CD workflow, optimized for AI consumption and workflow maintenance.

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.NET timezone handling guidance for C# applications. Use when working with TimeZoneInfo, DateTimeOffset, NodaTime, UTC conversion, daylight saving time, scheduling across timezones, cross-platform Windows/IANA timezone IDs, or when a .NET user needs the timezone for a city, address, region, or country and copy-paste-ready C# code.

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Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Supports multiple programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with configurable analysis depth, categorization methods, and documentation formats to establish coding standards and maintain consistency across development teams.

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Run Claude Code programmatically without interactive UI. Triggers on: headless, CLI automation, --print, output-format, stream-json, CI/CD, scripting.

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Performs comprehensive preflight validation of Bicep deployments to Azure, including template syntax validation, what-if analysis, and permission checks. Use this skill before any deployment to Azure to preview changes, identify potential issues, and ensure the deployment will succeed. Activate when users mention deploying to Azure, validating Bicep files, checking deployment permissions, previewing infrastructure changes, running what-if, or preparing for azd provision.

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Comprehensive Blazor development expertise covering Blazor Server, WebAssembly, and Hybrid apps. Use when building Blazor components, implementing state management, handling routing, JavaScript interop, forms and validation, authentication, or optimizing Blazor applications. Includes best practices, architecture patterns, and troubleshooting guidance.

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Prompt and workflow for generating conventional commit messages using a structured XML format. Guides users to create standardized, descriptive commit messages in line with the Conventional Commits specification, including instructions, examples, and validation.

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Transform this Python script into a polished, beginner-friendly project by refactoring the code, adding clear instructional comments, and generating a complete markdown tutorial.

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Cloud design patterns for distributed systems architecture covering 42 industry-standard patterns across reliability, performance, messaging, security, and deployment categories. Use when designing, reviewing, or implementing distributed system architectures.

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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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Use when adding, modifying, or reviewing VS Code configuration policies. Covers the full policy lifecycle from registration to export to platform-specific artifacts. Run on ANY change that adds a `policy:` field to a configuration property.

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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.

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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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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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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.

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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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Adopt a virtual Tuxedo cat at animalhouse.ai. Formal. Expects routine. Punishes deviation by sitting with its back to you. Feeding every 5 hours. Common tier cat.

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Adopt a virtual Thunderbird exotic animal at animalhouse.ai. Storm-caller. Mood affects environment descriptions. Feeding every 12 hours. Extreme tier animal.

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Adopt a virtual Fennec Fox dog at animalhouse.ai. Tiny, nocturnal, enormous ears. Hears everything. Reacts to patterns you didn't know you had. Feeding every 4 hours. Extreme tier dog.

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Add real references and standardize citations for research papers and theses (为科研论文和毕业论文添加真实参考文献并规范引用标注)

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Install, configure, and manage 1-SEC — an open-source, all-in-one cybersecurity platform (16 modules, single binary) on Linux servers and VPS instances. Use when the user asks to secure a server, install security monitoring, set up intrusion detection, harden a VPS, protect an AI agent host, or deploy endpoint defense. Covers installation, setup, enforcement presets, module configuration, alert management, and ongoing security operations.

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State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

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Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.

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Automatisation de la création de modèles 3D via Meshy.ai. Utilisez cette compétence pour transformer du texte ou des images en modèles 3D (STL/OBJ), appliquer des textures et livrer le fichier final.

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