Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add godot-fun/godot-framework --skill image-inpaint-regiongit clone --depth 1 https://github.com/godot-fun/godot-frameworkWrote 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/godot-fun/godot-framework/image-inpaint-region)<a href="https://agentmods.dev/skills/godot-fun/godot-framework/image-inpaint-region"><img src="https://agentmods.dev/badge/skills/godot-fun/godot-framework/image-inpaint-region/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/godot-fun/godot-framework/image-inpaint-region"><img src="https://agentmods.dev/badge/skills/godot-fun/godot-framework/image-inpaint-region.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00057 | $0.01782 |
| Opus 5 | $0.00028 | $0.00891 |
| Sonnet 5 | $0.00011 | $0.00356 |
| Haiku 4.5 | $0.00006 | $0.00178 |
Grade A, and why
image-inpaint-region 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 12d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Inpaint Region (LaMa)
Local circular region inpainting with IOPaint LaMa. Builds a circular mask from --region cx,cy,r, then runs the same inference path as iopaint run / the IOPaint API.
Both --image and --region cx,cy,r are required.
Rules
When this skill applies, read and follow skill-dependency-manager �?run scripts as documented, install missing tools into .dependency/.
- Run
inpaint.pythrough theiopaintmanifest entry (.dependency/iopaint/.venv/). Never use hostpython,py,python3, or any interpreter outside.dependency/. - Do not hand-write equivalent inpaint commands �?use the bundled script.
- Single file only. Pass one image with
--image; directories are not supported. - Require region first. If
--region cx,cy,ris missing, inspect the image (or ask the user) before running. - Use IOPaint defaults for inference config unless the user explicitly asks otherwise �?do not invent custom mask blur, compositing, or hd_strategy overrides in the script.
- Pass the input path as-is. Output goes to
<image-dir>/image-inpaint-region/by default �?no path rewriting. - Never overwrite source files. Output lands in
image-inpaint-region/or--output.
Setup (first run)
IOPaint needs Python 3.11 and PyTorch. From project root:
.dependency/python-3.11/python.exe -m venv .dependency/iopaint/.venv
.dependency/iopaint/.venv/Scripts/python.exe -m pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118
.dependency/iopaint/.venv/Scripts/python.exe -m pip install iopaint
CPU-only: skip the CUDA torch line and pip install iopaint (pulls CPU torch). Use bin/python on Unix.
Register in .dependency/manifest.json:
"iopaint": {
"populated": true,
"bin": ".dependency/iopaint/.venv/Scripts/python.exe"
}
LaMa weights (big-lama.pt) download on first run.
Quick Start
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.
- 12d ago First seen · 144 lines · 57 tokens per session scan A 62be1798e960
image-inpaint-region is a skill published in the GitHub repository godot-fun/godot-framework (116 stars, last pushed 12d ago), licensed MIT. It adds 57 tokens to every session and 1,782 once invoked, about $0.0003 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 2026-08-30.
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