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 0xDarkMatter/claude-mods --skill rembg-opsgit clone --depth 1 https://github.com/0xDarkMatter/claude-modsWrote 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/0xdarkmatter/claude-mods/rembg-ops)<a href="https://agentmods.dev/skills/0xdarkmatter/claude-mods/rembg-ops"><img src="https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/rembg-ops/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/0xdarkmatter/claude-mods/rembg-ops"><img src="https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/rembg-ops.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 | $0.00093 | $0.01291 |
| Opus 5 | $0.00046 | $0.00646 |
| Sonnet 5 | $0.00019 | $0.00258 |
| Haiku 4.5 | $0.00009 | $0.00129 |
Grade A, and why
rembg-ops 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 7d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
rembg Operations — cutouts for flat illustration & sticker art
Turn opaque, flat-background illustration (avatars, stickers, cartoon/vector art, generated character portraits) into clean transparent PNGs — without regenerating the source. rembg's ML models are the default engine; the value this skill adds is the deterministic fallback ladder for the cases pure ML gets wrong on flat-colour art.
The one thing to know
rembg is a semantic model, not a chroma keyer. isnet-anime (the model tuned
for outlined cartoon art) segments the salient character and ignores background
colour — so it cannot be "helped" with a greenscreen, and it fails in two
predictable ways on flat art:
- Pale / low-salience subjects get dropped (a near-white moon, a mint UFO on a light background read as "not the subject").
- Baked drop-shadows survive as a grey ghost or an opaque offset blob.
Both are fixed deterministically because flat sticker art always has one flat background colour + a sealing outline. That geometry makes a corner flood-fill colour-key exact, regardless of how pale the subject is. The axis that matters is shadow-vs-no-shadow, never greenscreen-vs-not.
Quickstart
# default: rembg isnet-anime, auto-fallback to colour-key if the subject collapses
python scripts/cutout.py "avatars/*.png" --out cutouts/ --contact-sheet
The --contact-sheet renders every cutout on a checkerboard so bad mattes jump
out. Then triage failures with the ladder below. --json | jq '.data[] | select(.coverage < 0.12)' flags collapsed subjects programmatically.
Method ladder — escalate only for the images that need it
| Symptom on the contact sheet | Fix | Flag |
|---|---|---|
| Clean die-cut | — (rembg isnet-anime) | default |
| Subject gone / faint ghost (pale subject) | flat-bg colour-key | --method colorkey |
| Translucent subject reads see-through (glass, clear cup) | colour-key forces the sealed interior opaque | --method colorkey |
| Semi-transparent grey shadow ghost | binarise alpha — drops the ~50% shadow, keeps the 100% subject | --flatten-alpha 170 |
| Opaque baked offset shadow (survives binarise) | colour-aware: drop dark pixels not hugging a coloured fill | --strip-offset-shadow |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 103 lines · 93 tokens per session scan A 1ca95f50ddc8
rembg-ops is a skill published in the GitHub repository 0xDarkMatter/claude-mods (35 stars, last pushed 18d ago), licensed MIT. It adds 93 tokens to every session and 1,291 once invoked, about $0.0005 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 2026-09-03.
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