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From phyxel-gamedev
Use when adding voxel objects, props, furniture, or buildings to a Phyxel game — spawning existing templates, searching the template catalog, or generating brand-new voxel models from a text prompt via BlockSmith. Invoke for "add a chair / tree / castle / barrel / generate a <thing>" tasks.
How this skill is triggered — by the user, by Claude, or both
Slash command
/phyxel-gamedev:phyxel-assetsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- `spawn_template` — place a `.voxel` template at a position (static, or dynamic-physics).
spawn_template — place a .voxel template at a position (static, or dynamic-physics).list_templates / search_templates / list_generated_templates — find what exists.{"type":"template","name":"tree.voxel","position":{...}}.tree.voxel, tree2.voxel, sphere.voxel, and generated furniture/
buildings cached in resources/templates/ (catalog: template_catalog.json).Text prompt → LLM → .bbmodel → .voxel. Two routes:
generate_template, build_building, search_templates, list_generated_templates.python tools/blocksmith_generate.py "a wooden chair" --name chair --size 2 --material Wood; buildings via --building --building-type tavern --style medieval --width 14 --depth 18 --stories 2 --materials '{"wall":"Stone","floor":"Wood","roof":"Wood"}'.
Sizes: furniture 2–3, buildings 8–15. Needs PHYXEL_AI_API_KEY or ANTHROPIC_API_KEY.
Generated templates are cached permanently in resources/templates/.Templates drop with their origin at the given position — place on top of terrain (Y =
surface + 1). Use spawn_template then screenshot to check scale/orientation; furniture is
small (2–3 voxels), buildings span many chunks. rotate_placed_object / move_placed_object
to adjust; list_placed_objects to inspect.
Inspect a model before using it: inspect_template / critique_template (screenshots +
evaluation). Refine generations with refine_template.
npx claudepluginhub barbarisch/phyxel --plugin phyxel-gamedevGuides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.