gleam-web-development
Guides Claude through Gleam backend web development with Wisp and Mist. Use for REST APIs, web services, and server-side rendering. For frontend/SPA development with Lustre, use the gleam-lustre-development ski...
Browse published AI skills maintained by renatillas. Compare skill descriptions and follow each source repository for setup instructions.
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8Repository stars across indexed skills
24Repository forks
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3Repository stars may repeat across skills from the same repository.
Guides Claude through Gleam backend web development with Wisp and Mist. Use for REST APIs, web services, and server-side rendering. For frontend/SPA development with Lustre, use the gleam-lustre-development ski...
Guides Claude through deploying Gleam applications to production on Fly.io, Docker, or other platforms. Use when setting up deployment pipelines, configuring environments, or troubleshooting production issues.
Guides Claude through integrating Gleam with JavaScript code using FFI, external functions, and NPM packages. Use when building for JavaScript target, using browser APIs, or wrapping JS libraries.
Guides Claude through building concurrent, fault-tolerant applications with Gleam OTP. Use when creating actors, supervision trees, or building distributed BEAM applications.
Guides Claude through creating and publishing Gleam packages to Hex.pm. Use when developing libraries, writing documentation, or preparing packages for publication.
Guides Claude through integrating Gleam with Erlang and Elixir code using FFI, external functions, and BEAM libraries. Use when building for Erlang target, calling Erlang libraries, or integrating with existing...
Guides Claude through testing Gleam applications with gleeunit. Use when writing unit tests, integration tests, or property-based tests. Always use let assert, NOT deprecated should module.
Guides Claude through idiomatic Lustre frontend development. Use when building SPAs, UI components, or interactive applications. Based on lustre_ui patterns from the official Lustre team.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.