platform-strip

Solid

Generate non-pixel-art, horizontally repeatable platform strips from real image sources as fixed Texture2D cells or AtlasTexture regions.

API & Backend 538 stars 46 forks Updated today NOASSERTION

Install

View on GitHub

Quality Score: 81/100

Stars 20%
91
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Platform Strip Asset Use for collision-aligned floors, bridges, rails, pipes, terrain ledges, and long horizontal hazards. Do not use for characters, UI, compact props, full backgrounds, or pixel art. ## Contract Accept the shared Asset Skill request schema at `.godotmaker/asset-runtime/schema/asset-skill-request.schema.json` with `asset_type: "platform-strip"`. Use the shared result schema and checker. This skill can be invoked directly or by an orchestrator with the same contract. Do not read or write `ASSETS.md`, tags, stage state, or generated manifests. `spec` must contain exactly: ```json { "kind": "single" | "atlas", "grid": {"columns": 3, "rows": 1, "cell_width": 160, "cell_height": 80}, "segments": [ {"name": "left_cap", "role": "left_cap", "slot": [0, 0]}, {"name": "repeat_middle", "role": "repeat_middle", "slot": [1, 0]}, {"name": "right_cap", "role": "right_cap", "slot": [2, 0]} ] } ``` The fixed grid dimensions are positive integers. This v1 family is one closed horizontal row: `rows` must be `1`, `columns` must equal `segments.length`, and entries must be declared in left-to-right slot order as `[0, 0]` through `[columns - 1, 0]`. The first entry is the only `left_cap`, the last is the only `right_cap`, and every interior entry is `repeat_middle`. Empty slots, reordered entries, and a request without a repeatable middle segment are unsupported. `references` is optional. With references, validate every path is readable, preserve each ...

Details

Author
RandallLiuXin
Repository
RandallLiuXin/GodotMaker
Created
5 months ago
Last Updated
today
Language
Python
License
NOASSERTION

Similar Skills

Semantically similar based on skill content — not just same category