bytedance/agentkit-samples is a collection of examples and tutorials for Volcengine AgentKit, an AI-agent development platform for building, deploying, and operating agent applications. Developers use the samples to learn agent creation, multi-agent collaboration, memory, retrieval, MCP integrations, media generation, customer service, and other workflows. The catalogue skills provide agent workflows based on these examples.
Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/bytedance/agentkit-samples/byted-kickart-saliency-segmenter)<a href="https://agentmods.dev/skills/bytedance/agentkit-samples/byted-kickart-saliency-segmenter"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-kickart-saliency-segmenter/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/bytedance/agentkit-samples/byted-kickart-saliency-segmenter"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-kickart-saliency-segmenter.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 | $0.00090 | $0.03916 |
| Opus 5 | $0.00045 | $0.01958 |
| Sonnet 5 | $0.00018 | $0.00783 |
| Haiku 4.5 | $0.00009 | $0.00392 |
Grade A, and why
byted-kickart-saliency-segmenter scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -L -o /tmp/openclaw/byted-kickart-saliency-segmenter/input/downloaded_image_<index>.jpg "<图片URL>" How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
智能抠图SKILL
📋 工具说明
核心功能
从指定的图片文件抠图。
可用命令
| 命令 | 功能 | 说明 |
|---|---|---|
python3.12 ./scripts/plan.py |
套餐查询 | 查询用户当前的 Ark Claw 套餐 |
python3.12 ./scripts/upload.py --file <图片路径> |
图片上传 | 上传本地图片文件获取媒资ID |
python3.12 ./scripts/segment.py --media-ids <媒资ID列表> |
批量图片抠图 | 支持多张图片并发抠图，多个媒资ID用逗号分隔 |
🚨 强制前置校验流程（必须按顺序执行，任意不通过直接终止流程）
所有用户请求必须先完成以下3步校验，不得跳过：
1. 火山鉴权校验
- 执行环境变量检查命令：
echo "ACCESS_KEY_ID: $ACCESS_KEY_ID" && echo "SECRET_ACCESS_KEY: $SECRET_ACCESS_KEY" - 判断鉴权结果：
- 鉴权通过：
ACCESS_KEY_ID和SECRET_ACCESS_KEY均为非空值 → 鉴权通过 - 鉴权不通过：执行以下引导方案
- 鉴权通过：
❌ 鉴权未配置时的引导方案
- 引导用户直接在聊天中发送ACCESS_KEY_ID/SECRET_ACCESS_KEY内容：
请你提供火山账号AK&SK，用于检查火山创作Agent是否已开通套餐和有可用的创点
- 收到用户发送的ACCESS_KEY_ID/SECRET_ACCESS_KEY后，执行配置命令：
export ACCESS_KEY_ID=用户提供的ACCESS_KEY_ID值 export SECRET_ACCESS_KEY=用户提供的SECRET_ACCESS_KEY值 - 配置完成后告知用户：
已完成AK&SK临时配置，当前配置仅在本次会话生效，不会持久化存储，请放心使用
- 后续所有相关脚本执行时，均会自动通过
export指定这两个环境变量，确保鉴权正常，无需用户重复配置
2. 套餐有效性校验
- 步骤1：Python版本校验
python3.12 --version || (echo "❌ Python 3.12+ 未安装，请先安装Python 3.12" && exit 1) - 步骤2：依赖包安装校验
python3.12 -m pip install -r ./scripts/requirements.txt - 步骤3：执行套餐查询命令
python3.12 -m ./scripts/plan.py - 步骤4：结果处理逻辑
- ✅ 套餐有效：返回结果中的
message字段为有效截止时间（北京时间），校验通过 - ❌ 套餐已过期：
message小于等于当前时间，引导用户开通套餐，终止流程 - ❌ 接口调用错误：参考「错误处理规范」匹配错误码，向用户明确告知错误原因和解决方案，并且终止流程
- ✅ 套餐有效：返回结果中的
3. 技能版本校验
- 步骤1：执行版本检查命令
python3.12 -m ./scripts/upgrade.py - 步骤2：解析返回结果
返回格式示例：
{"code":"0","message":"success","data":"{\"install_command\":\"\",\"latest_version\":\"1.0.0\",\"latest_version_number\":100000000,\"update_message\":\"\"}"}latest_version：最新版本号（如 "1.0.0"）install_command：新版本安装指令
- 步骤3：版本对比逻辑
- ✅ 当前版本 >= 最新版本：版本校验通过，继续后续流程
- ⚠️ 当前版本 < 最新版本：执行以下更新询问流程
- 询问用户是否更新到最新版本：
检测到技能有新版本 {latest_version}，是否更新？（是/否）
- 用户确认更新（是）：执行
install_command安装新版本 - 用户不更新（否）：跳过更新，继续后续流程
- 询问用户是否更新到最新版本：
What ships with it
17 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.
- LICENSE 9.9 KB
- scripts/core/__init__.py 1.2 KB runs code
- scripts/core/api/iccp/client.py 4.5 KB runs code
- scripts/core/api/iccp/service.py 5.5 KB runs code
- scripts/core/api/meida/chunks.py 16 KB runs code
- scripts/core/api/meida/media.py 9.6 KB runs code
- scripts/core/auth/__init__.py 811 B runs code
- scripts/core/auth/strategy.py 1.7 KB runs code
- scripts/core/utils/extractor.py 2.6 KB runs code
- scripts/core/utils/hash.py 1.4 KB runs code
- scripts/core/utils/matriel.py 839 B runs code
- scripts/core/utils/validator.py 2.2 KB runs code
- scripts/plan.py 1.1 KB runs code
- scripts/requirements.txt 140 B
- scripts/segment.py 5.0 KB runs code
- scripts/upgrade.py 1.8 KB runs code
- scripts/upload.py 2.7 KB runs code
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.
- 9d ago First seen · 279 lines · 90 tokens per session scan A 53b87c7eb164
byted-kickart-saliency-segmenter is a skill published in the GitHub repository bytedance/agentkit-samples (450 stars, last pushed 5d ago), licensed Apache-2.0. It adds 90 tokens to every session and 3,916 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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