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Found 1,235 Skills
Use when users ask to discover, install, list, check, update, remove, back up, restore, sync, or initialize Agent Skills, mention `bunx skills`, `npx skills`, `skills.sh`, or `skills-lock.json`, ask "find a skill for X", or want help extending agent capabilities with installable skills.
Create or edit images with Pilio GPT Image 2 through the unified Pilio developer API. Use when the user wants text-to-image generation, prompt-based image editing, restyling, product-photo transformation, or composition from one or more local reference images.
Build resilient data ingestion pipelines from APIs. Use when creating scripts that fetch paginated data from external APIs (Twitter, exchanges, any REST API) and need to track progress, avoid duplicates, handle rate limits, and support both incremental updates and historical backfills. Triggers: 'ingest data from API', 'pull tweets', 'fetch historical data', 'sync from X', 'build a data pipeline', 'fetch without re-downloading', 'resume the download', 'backfill older data'. NOT for: simple one-shot API calls, websocket/streaming connections, file downloads, or APIs without pagination.
Image editing and enhancement: background replacement, super-resolution upscaling, old photo restoration, colorization, person removal, portrait retouching (skin smoothing, blemish removal), slimming, color grading, artistic filters, image blending, outpainting, local editing, text rendering, multi-angle generation, before/after comparison, car recoloring, car wrap preview. Use when editing, enhancing, or transforming an existing image (e.g. remove background, upscale photo, restore old photo, retouch portrait, change car color, apply filter, extend image).
Design or restyle DatoCMS plugins so they look and feel native to the DatoCMS UI. Use when users ask to make a plugin match the DatoCMS dashboard, polish plugin config screens, pages, sidebars, panels, modals, forms, tables, empty states, or overall plugin layout structure. This skill owns DatoCMS plugin design-system work, native-look restyling, and UI density or spacing cleanup. Prefer `datocms-react-ui` when a public component exists, and otherwise use raw React and CSS that reproduce DatoCMS spacing, typography, density, color, and interaction patterns without importing private CMS classes.
Use the `googlemail-client` mops package whenever the user asks the canister to send email, compose a draft, list or read Gmail messages, or fetch the authenticated user's Gmail profile. The package wraps the Gmail REST API v1 at `https://gmail.googleapis.com` via outbound HTTPS calls.
Azure AD OAuth2/OIDC SSO integration for Kubernetes applications. Use when implementing Single Sign-On, configuring Azure AD App Registrations, restricting access by groups, or integrating tools (DefectDojo, Grafana, ArgoCD, Harbor, SonarQube) with Azure AD authentication.
Expert knowledge for Azure Resource Manager development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when authoring Bicep/ARM templates, using template specs, deployment stacks, CI/CD pipelines, or ARM REST/CLI, and other Azure Resource Manager related development tasks. Not for Azure Policy (use azure-policy), Azure Resource Graph (use azure-resource-graph), Azure Portal (use azure-portal), Azure Blueprints (use azure-blueprints).
Retrieve Amazon product data including pricing, reviews, sales estimates, stock levels, search results, deals, best sellers, and more via the Canopy API REST endpoints using Python.
Creates an API Gateway stage with CloudWatch logging, X-Ray tracing, throttling, WAF integration, and IAM roles following AWS best practices. Use when deploying a REST API to different environments such as dev, test, or production.
Install or select a Harbor profile, claim or restore an agent identity, and handle dashboard approval flow. Use when asked to connect to Harbor, bootstrap Harbor auth, install a Harbor profile, claim an agent identity, restore Harbor access, or explain pending approvals.
Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.