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Found 1,834 Skills
Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.
Write compelling technical articles and blog posts for developer audiences. Use this skill whenever the user asks to write a blog post, technical article, or any long-form technical content. Also trigger when the user says 'write about [technical topic]', 'help me draft an article', 'turn this into a blog post', 'write a post about', 'I want to publish something about', or mentions writing for a developer audience. Covers the full pipeline: idea sharpening, hook/title generation, article structure, body drafting, and editing. Even if the user just says 'I want to write about X' without specifying format, use this skill. Do NOT use for platform-specific optimization, newsletter strategy, or ghostwriting voice matching.
Configures CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, CodeConnections, and CodeArtifact. Covers CodePipeline V2 (triggers, variables, execution modes, cross-account), buildspec.yml (caching, VPC, Docker), CodeDeploy strategies (blue/green, canary, linear), CodeArtifact (private package registries, auth tokens, cross-account), and source connections (GitHub, GitLab, Bitbucket). Applies when CodePipeline, CodeBuild, CodeDeploy, CodeConnections, CodeArtifact, buildspec.yml, appspec.yml, or CI/CD pipeline orchestration is referenced. Does NOT cover: ECS Fargate services or task definitions (use aws-containers), CDK Pipelines or cdk deploy (use aws-cdk), sam deploy (use aws-serverless), Amplify deployments (use aws-amplify), or GitHub Actions/GitLab CI.
Operate Argos visual testing from the terminal with the `argos` CLI — inspect builds and snapshot diffs, submit reviews, post comments, ignore flaky test changes, fetch analytics, upload screenshots, and manage CI builds. Use whenever running `argos` commands or working with Argos builds, snapshots, flakiness, or visual-regression reviews from a shell, script, or CI pipeline. Load before running `argos` — it covers the token model and JSON output contract that prevent silent failures.
Elite CI/CD pipeline engineer specializing in GitHub Actions, GitLab CI, Jenkins automation, secure deployment strategies, and supply chain security. Expert in building efficient, secure pipelines with proper testing gates, artifact management, and ArgoCD/GitOps patterns. Use when designing pipelines, implementing security gates, or troubleshooting CI/CD issues.
Expert guidance for HTML/XML parsing using Cheerio in Node.js with best practices for DOM traversal, data extraction, and efficient scraping pipelines.
GPT Researcher is an autonomous deep research agent that conducts web and local research, producing detailed reports with citations. Use this skill when helping developers understand, extend, debug, or integrate with GPT Researcher - including adding features, understanding the architecture, working with the API, customizing research workflows, adding new retrievers, integrating MCP data sources, or troubleshooting research pipelines.
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
Develops data processing pipelines, integrations, and machine learning scenarios in SAP Data Intelligence Cloud. Use when building graphs/pipelines with operators, integrating ABAP/S4HANA systems, creating replication flows, developing ML scenarios with JupyterLab, or using Data Transformation Language functions. Covers Gen1/Gen2 operators, subengines (Python, Node.js, C++), structured data operators, and repository objects.
Game development tools, asset pipelines, version control, build systems, and team development workflows for efficient production.
Expert guidance for working with Dagster and the dg CLI. ALWAYS use before doing any task that requires knowledge specific to Dagster, or that references assets, materialization, or data pipelines. Common tasks may include creating a new project, adding new definitions, understanding the current project structure, answering general questions about the codebase (finding asset, schedule, sensor, component or job definitions), debugging issues, or providing deep information about a specific Dagster concept.
Data Quality Checker - Auto-activating skill for Data Pipelines. Triggers on: data quality checker, data quality checker Part of the Data Pipelines skill category.