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Found 5,557 Skills
Infrastructure-as-Code fundamentals for data engineers using Terraform to provision AWS resources (S3, EC2, IAM)
Analyze Terraform plan JSON output for AzureRM Provider to distinguish between false-positive diffs (order-only changes in Set-type attributes) and actual resource changes. Use when reviewing terraform plan output for Azure resources like Application Gateway, Load Balancer, Firewall, Front Door, NSG, and other resources with Set-type attributes that cause spurious diffs due to internal ordering changes.
Alchemy IaC framework for TypeScript. Use when the user mentions Alchemy, wants to set up infrastructure, deploy Cloudflare Workers, configure databases, KV, R2, queues, use bindings and secrets, set up dev mode, use framework adapters (Vite, Astro, React Router, SvelteKit, Nuxt, TanStack Start), create custom resources, or work with any Alchemy provider.
Helps migrate self-managed Apache Kafka workloads to Amazon MSK Express. Inventories the source cluster (from IaC files, Kafka CLI output, or manual input), assesses MSK Express compatibility across topology, Kafka version, configs, auth, and quotas, produces a target Express specification (instance type, broker count, monthly cost) by filling the AWS-published MSK Sizing/Pricing workbook, and guides migration execution using MSK Replicator. Applicable when the user mentions migrating Kafka, MSK, MSK Express, Kafka migration, analyzing Kafka infrastructure, moving to MSK, moving streaming platform to MSK, streaming migration, moving streaming workloads to AWS, MSK workload compatibility, MSK cluster sizing, choosing an MSK cluster type, or MSK Replicator.
AI-driven multi-format SVG content generation system. Converts source documents (PDF/DOCX/URL/Markdown) into high-quality SVG pages and exports to PPTX through multi-role collaboration. Use when user asks to "create PPT", "make presentation", "生成PPT", "做PPT", "制作演示文稿", or mentions "ppt-master".
Produce distinctive, non-generic UI and design applications well, working strategy-first. Identify the project (landing page, SaaS app, dashboard, ecommerce, presentation, docs, portfolio...) and its positioning and personality, commit to brand adjectives, translate into a typography and color system, then apply the craft layer (layout, components and states, motion, iconography, imagery, dark mode and theming, accessibility), avoiding the AI-slop / Claude-esque default. This is both a de-slop and an expert app-design skill. Use this whenever building or styling any web frontend, app, dashboard, landing page, deck, or artifact, or when the user says "make it not look like AI", "de-slopify", "deslop", "less generic", "give it character", "design a UI for X", "design an app", "update DESIGN.md", or complains the output looks like every other AI site. Trigger even when the user just says "build a UI for X" without naming an aesthetic, because the default without this skill is slop.
Activated when the user mentions LiteFlow (a lightweight Java rule engine/business orchestration framework). Coverage includes: components, EL rules (THEN/WHEN/IF/SWITCH/FOR/WHILE/ITERATOR, etc.), context, script components, rule configuration sources, configuration items, executors, AI Agent orchestration (ReAct Agent / liteflow-react-agent), testing and debugging, source code details.
Manage Azure DevOps resources via CLI including projects, repos, pipelines, builds, pull requests, work items, artifacts, and service endpoints. Use when working with Azure DevOps, az commands, devops automation, CI/CD, or when user mentions Azure DevOps CLI.
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.
Use when developing, reviewing, or explaining Rill projects and project files (connectors, models, metrics views, explores, canvases, themes, rill.yaml, sources, alerts, reports, APIs). Apply runtime workflow guidance and project-file reference docs, and cite rule files and source URLs.
SAP Converged Cloud Go coding conventions extracted from sapcc/keppel and sapcc/go-bits PR reviews. Enforces architecture patterns, library usage rules, error handling conventions, testing patterns, and anti-over-engineering principles. Use when working in sapcc/* repos, when code imports github.com/sapcc/go-bits, or when targeting SAP CC code review standards. Do NOT use for general Go projects without sapcc dependencies.
Finds and inspects data assets within Google Cloud. Relevant when any of the following conditions are true: 1. The user request involves finding, exploring, or inspecting data assets in Google Cloud, such as: - BigQuery datasets, tables, or views - BigLake catalog or tables - Spanner instances, databases or tables - etc. 2. You need to retrieve the schema, metadata, or governance policies for a GCP data asset. 3. You have a keyword or topic (e.g., "sales data") but lack the specific table or resource ID. 4. You are attempting to find data using `bq ls`, as this skill offers a superior approach. Don't use when: - Assets are outside Google Cloud