Execute Lua scripts or YAML checks in a Kubernetes runtime.
npx skills add https://github.com/developerinlondon/assay --skill assay
Please help me install this Agent Skill. Skill: assay Source: https://github.com/developerinlondon/assay/tree/main Command: npx skills add https://github.com/developerinlondon/assay --skill assay
This Skill provides a lightweight, single-binary Lua runtime that replaces large Python/Node.js/kubectl containers in Kubernetes, enabling efficient scripting, verification, and web services.
Use the assay skill to run the attached Lua script 'deploy-check.lua'.
High-intent search queries and answers about installing and using this skill.
Kubernetes automation with Lua scripts is executed via a lightweight, single-binary runtime that replaces large Python or Node.js containers. This minimizes container image sizes while directly running Lua scripts or YAML check configurations.
Post-deployment verification checks in a CI/CD pipeline are performed by executing YAML check configurations or Lua scripts. This approach integrates natively with Kubernetes services to validate deployments without heavy runtime dependencies.
Yes, a Lua runtime can interact directly with Kubernetes services by utilizing embedded Lua modules. It supports integration with over 23 Kubernetes-native services, enabling direct cluster automation and API execution.
Yes, Kubernetes automation supports executing YAML check configurations natively. The runtime processes these YAML files directly to perform verification checks and automate job tasks within the cluster environment.
Container image sizes for Kubernetes scripting are optimized by replacing large Python, Node.js, or kubectl containers with a single-binary Lua runtime. This reduces the overall footprint while maintaining full scripting and web service capabilities.
Limitations of this lightweight Lua runtime for Kubernetes job automation include relying on Lua scripting knowledge instead of standard Python or Node.js workflows. It is tailored for minimal footprint tasks rather than heavy computational processing.
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