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papanito

@papanito source repo

9 published skills

  1. Github Enterprise Eu Admin · papanito
    specialized protocol for GHEC on ghe.com with EU Data Residency. Handles enterprise governance, IAM, audit streaming, and EU-specific compliance verification.
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  2. Lazyvim Config Engineer · papanito
    specialized protocol for Neovim/LazyVim configuration. Handles lazy.nvim plugin specs, Lua API integration (Snacks, LazyVim.util), and Cloud Engineering LSP/DAP setups.
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  3. Swiss Legal Expert · papanito
    specialized protocol for Swiss law queries (Federal and Cantonal). Triggers on topics like Fedlex, BV, OR, ZGB, or Canton-specific regulations.
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  4. Packer Imaging Expert · papanito
    specialized protocol for automated machine image creation using HashiCorp Packer, OS auto-installs (Kickstart/Preseed), and Cloud-init orchestration.
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  5. Nixos Expert Protocol · papanito
    specialized protocol for NixOS system architecture and debugging. Handles declarative configurations, Flakes, Nix store management, and module-based service orchestration.
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  6. Loop Orchestration Engineer · papanito
    specialized protocol for Loop Engineering — auditing a workspace for repeatable tasks, ranking them with the 4-Condition Test, and building self-verifying Loop Orchestration Skills with a done-rule, a separate verifier subagent, run memory, and a Loop Training Mode toggle.
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  7. Terraform Platform Engineer · papanito
    specialized protocol for Terraform architecture and module engineering. Focuses on HCL 1.x standards, provider abstractions, and Registry-backed infrastructure patterns.
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  8. Gnome Shell Extension Local Dev · papanito
    Build, symlink-install, enable, debug, and package a GNOME Shell extension locally on GNOME 46–50 (Wayland-safe). Use when creating or iterating on any gnome-shell extension.
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  9. Spec Driven Initiation Engineer · papanito
    specialized protocol for spec-driven project initiation using Karpathy's Method — interview for the real goal, decompose into small compartmentalized specs, verify key decisions explicitly, define precise checkable success criteria, and enforce second-AI final verification.
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