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 meitu/meitu-skills --skill meitu-cutoutgit clone --depth 1 https://github.com/meitu/meitu-skillsWrote 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/meitu/meitu-skills/meitu-cutout)<a href="https://agentmods.dev/skills/meitu/meitu-skills/meitu-cutout"><img src="https://agentmods.dev/badge/skills/meitu/meitu-skills/meitu-cutout/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/meitu/meitu-skills/meitu-cutout"><img src="https://agentmods.dev/badge/skills/meitu/meitu-skills/meitu-cutout.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 5 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 12 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 14 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 18 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 41 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Rogue Agent · line 21 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00083 | $0.01715 |
| Opus 5 | $0.00042 | $0.00857 |
| Sonnet 5 | $0.00017 | $0.00343 |
| Haiku 4.5 | $0.00008 | $0.00171 |
Grade A, and why
meitu-cutout 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meitu Cutout
Overview
调用 meitu image-cutout 从图片中分离前景主体，输出透明背景 PNG。仅支持人物、宠物、商品、图标、印章五类主体；可选人像、商品、图形三种模型，也可省略模型参数自动检测。
Dependencies
- meitu-cli:
npm install -g meitu-cli@latest - 凭证: 首选 env vars
MEITU_OPENAPI_ACCESS_KEY/MEITU_OPENAPI_SECRET_KEY，或预置~/.meitu/credentials.json；仅在用户明确要求写入本地凭证时，再执行meitu config set-ak --value "..."/meitu config set-sk --value "..."
路径别名： 下文中
$VISUAL={OPENCLAW_HOME}/workspace/visual/
Core Workflow
Preflight → [Context: 跳过（工具型抠图，无创意自由度）] → Execute → Deliver
Preflight
meitu --version→ 未安装则提示npm install -g meitu-cli@latestmeitu auth verify --json→ 凭证无效则引导配置- Detect mode: cwd has
openclaw.yaml→ project mode; else → one-off 检查$VISUAL目录 → 确定 capabilities - output_dir 解析（Preflight 内 MUST 完成）：
Resolve output_dir: openclaw.yaml →
./output/| else →$VISUAL/output/meitu-cutout/mkdir -p {output_dir}
Execute
输入解析
用户提供图片，支持两种形式：
- 本地文件路径（如
./photo.jpg） - 图片 URL（如
https://example.com/photo.jpg）
如果用户只说"帮我抠图"但没给图片 → 问："请提供需要抠图的图片（本地路径或 URL）"。
模型选择
| 图片主体 | model_type |
输出 |
|---|---|---|
| 人像、证件照、半身照 | 0 |
透明底 PNG，保留发丝细节 |
| 商品、产品、电商图 | 1 |
透明底 PNG，优化产品边缘 |
| 设计素材、图标、印章 | 2 |
透明底 PNG |
| 宠物或类型不确定 | 省略 | 服务端自动选择模型，输出透明底 PNG |
model_type 仅允许 0、1、2。建筑、植物、车辆、食物、家具等非五类主体以及白底隔离不受支持，不得通过 prompt 或替代 API 绕过限制；需要生成白底时改用 image-edit。
工具调用
单张抠图：
meitu image-cutout --image_url {image_url_or_path} --json --download-dir {output_dir} --skill_name skill_meitu-cutout
明确指定模型时追加 --model_type 0、--model_type 1 或 --model_type 2；省略时自动选型。
批量处理
批量处理整个目录：
meitu batch image-cutout --input-dir {input_dir} --output-dir {output_dir} --skill_name skill_meitu-cutout
整个批次共用固定模型时追加 --model-type 0、--model-type 1 或 --model-type 2。逐条指定时使用 JSON/YAML 配置，条目字段 modelType（兼容 model_type）映射到单次命令的 model_type。批处理默认并发数为 3，输出 .png。
注意：单次命令不支持 --image_list；输入参数只接 --image_url（别名 --image）。
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 · 134 lines · 83 tokens per session scan A 12d7eb2db42a
meitu-cutout is a skill published in the GitHub repository meitu/meitu-skills (32 stars, last pushed 15d ago), licensed MIT. It adds 83 tokens to every session and 1,715 once invoked, about $0.0004 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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