Borrowing it
Nothing to install: this file belongs to ilhamdoanggg/aseprite-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ilhamdoanggg/aseprite-mcp/main/.opencode/skills/tukang-map/SKILL.mdgit clone --depth 1 https://github.com/ilhamdoanggg/aseprite-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ilhamdoanggg/aseprite-mcp/tukang-map)<a href="https://agentmods.dev/skills/ilhamdoanggg/aseprite-mcp/tukang-map"><img src="https://agentmods.dev/badge/skills/ilhamdoanggg/aseprite-mcp/tukang-map/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ilhamdoanggg/aseprite-mcp/tukang-map"><img src="https://agentmods.dev/badge/skills/ilhamdoanggg/aseprite-mcp/tukang-map.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.04753 |
| Opus 5 | $0.00021 | $0.02377 |
| Sonnet 5 | $0.00008 | $0.00951 |
| Haiku 4.5 | $0.00004 | $0.00475 |
Grade A, and why
generate2dmap scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 458 lines — stays where its author put it; the contents beside it link to each section on GitHub.
generate2dmap
Structured tile map generation using aseprite-mcp drawing tools. Define tile set → plan map grid → build layers → place tiles → export.
Tool reference
| Tool | Purpose |
|---|---|
create_sprite |
Start a new sprite (width, height) |
draw_pixels |
Place individual pixels |
draw_line |
Bresenham line |
draw_rectangle |
Filled or outline rectangle |
draw_circle |
Filled or outline circle |
flood_fill |
Fill contiguous area |
add_layer |
New layer for map depth |
remove_layer |
Delete a layer |
add_frame |
New frame for animated tiles |
set_frame_duration |
Set frame timing |
export_png |
Export to PNG |
export_gif |
Export animated map |
get_sprite_info |
Read sprite dimensions |
inspect_sprite |
Full cel dump |
get_pixel_color |
Read pixel color |
resize_canvas |
Change sprite dimensions |
Map conventions
Grid and canvas
- Tile size: 16×16 (standard) or 32×32 (detailed)
- Canvas: tile_size × map_width × map_height pixels
- Example: 16×16 tiles, 20×15 grid → 320×240 canvas
- Origin: top-left (0,0)
Coordinate system
Tile (col, row) → pixel (col * tile_w, row * tile_h)
Example for 16×16 tiles:
Tile (0,0) → pixel (0,0)
Tile (1,0) → pixel (16,0)
Tile (5,3) → pixel (80,48)
Tile types
Define tile set before building the map:
Ground tiles
| Tile | Color | Hex | Properties |
|---|---|---|---|
| Grass | Green | #44aa33 | Walkable |
| Dirt | Brown | #8B5E3C | Walkable |
| Sand | Tan | #ddcc88 | Walkable (slow) |
| Snow | White | #eeeedd | Walkable (slippery) |
| Stone floor | Gray | #999988 | Walkable |
| Wood floor | Brown | #bb8855 | Walkable |
| Water | Blue | #3388ff | Impassable |
| Deep water | Dark blue | #1144bb | Impassable |
| Lava | Orange | #ff4400 | Deadly |
Wall / obstacle tiles
| Tile | Color | Hex | Properties |
|---|---|---|---|
| Brick wall | Red-brown | #cc6644 | Solid |
| Stone wall | Gray | #888888 | Solid |
| Metal wall | Dark gray | #666677 | Solid |
| Fence | Brown | #996633 | Semi-solid (see through) |
| Hedge | Dark green | #228833 | Semi-solid |
| Cliff | Brown-gray | #8B7D6B | Solid (one-way up) |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 458 lines · 42 tokens per session scan A 341f641dc494
generate2dmap is a skill published in the GitHub repository ilhamdoanggg/aseprite-mcp (0 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 4,753 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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