By secondsky
Integrate lightweight Git-backed headless CMS into static sites using Hugo, Jekyll, 11ty, Gatsby, Astro, or Next.js to manage blogs, docs, and i18n content via Git commits. Resolves OAuth errors, TOML/YAML issues, CORS problems, and content listing failures found in Netlify CMS.
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npx claudepluginhub secondsky/claude-skills --plugin sveltia-cmsNuxt Content v3 Git-backed CMS for Markdown/MDC content sites. Use for blogs, docs, content-driven apps with type-safe queries, schema validation (Zod/Valibot), full-text search, navigation utilities. Supports Nuxt Studio production editing, Cloudflare D1/Pages deployment, Vercel deployment, SQL storage, MDC components, content collections.
Netlify platform skills for Claude Code
Inki — research, write, review, submit your docs. A Claude Code plugin encapsulating the Strapi documentation toolkit.
Claude Code skill pack for Webflow (24 skills)
Payload Development plugin - covers collections, fields, hooks, access control, plugins, and database adapters.
Production-ready skills for managing Webflow CMS content, auditing site health, optimizing assets, and safely publishing changes
This skill provides comprehensive guidance for SAP BTP Job Scheduling Service development, configuration, and operations. It should be used when creating, managing, or troubleshooting scheduled jobs on SAP Business Technology Platform. The skill covers service setup, REST API usage, schedule types and formats, OAuth 2.0 authentication, multitenancy, Cloud Foundry tasks, Kyma runtime integration, and monitoring with SAP Cloud ALM and Alert Notification Service. Keywords: SAP BTP, Job Scheduling, jobscheduler, cron, schedule, recurring jobs, one-time jobs, Cloud Foundry tasks, CF tasks, Kyma, OAuth 2.0, XSUAA, @sap/jobs-client, REST API, asynchronous jobs, action endpoint, run logs, SAP Cloud ALM, Alert Notification Service, multitenancy, tenant-aware, BC-CP-CF-JBS
Production-ready SAP BTP best practices for enterprise architecture, account management, security, and operations. Use when planning BTP implementations, setting up account hierarchies, configuring environments, implementing authentication, designing CI/CD pipelines, establishing governance, building Platform Engineering teams, implementing failover strategies, or managing application lifecycle on SAP BTP. Keywords: SAP BTP, account hierarchy, global account, directory, subaccount, Cloud Foundry, Kyma, ABAP, SAP Identity Authentication, CI/CD, governance, Platform Engineering, failover, multi-region, SAP BTP best practices
Guides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP. Use when: deploying generative AI models (GPT, Llama, Gemini, Mistral), building orchestration workflows with templating/filtering/grounding, implementing RAG with vector databases, managing ML training pipelines with Argo Workflows, configuring content filtering and data masking for PII protection, using the Generative AI Hub for prompt experimentation, or integrating AI capabilities into SAP applications. Covers service plans (Free/Standard/Extended), model providers (Azure OpenAI, AWS Bedrock, GCP Vertex AI, Mistral, IBM), orchestration modules, embeddings, tool calling, and structured outputs.
SAP BTP Cloud Integration Automation Service (CIAS) skill for guided integration workflows. Use when: setting up CIAS subscriptions, configuring destinations, assigning roles (CIASIntegrationAdministrator, CIASIntegrationExpert, CIASIntegrationMonitor), planning integration scenarios, working with My Inbox tasks, monitoring scenario execution, troubleshooting CIAS errors, creating OAuth2 instances, configuring identity providers for CIAS, understanding CIAS security architecture, or integrating SAP products (S/4HANA, SuccessFactors, BTP services, SAP Build, IBP).
SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage