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 OPPO-Mente-Lab/X-OmniClaw --skill taobao-searchgit clone --depth 1 https://github.com/OPPO-Mente-Lab/X-OmniClawWrote 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/oppo-mente-lab/x-omniclaw/taobao-search)<a href="https://agentmods.dev/skills/oppo-mente-lab/x-omniclaw/taobao-search"><img src="https://agentmods.dev/badge/skills/oppo-mente-lab/x-omniclaw/taobao-search/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/oppo-mente-lab/x-omniclaw/taobao-search"><img src="https://agentmods.dev/badge/skills/oppo-mente-lab/x-omniclaw/taobao-search.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 | $0.00035 | $0.02867 |
| Opus 5 | $0.00017 | $0.01434 |
| Sonnet 5 | $0.00007 | $0.00573 |
| Haiku 4.5 | $0.00003 | $0.00287 |
Grade A, and why
taobao-search 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 13d 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 — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Taobao Search Tool
通过淘宝 Deep Link 直达搜索页面,浏览商品并为用户提供购物建议。
🎯 When to Use
Use this skill when user asks about:
✅ 商品搜索 - "帮我找阿迪达斯今年新款男鞋" ✅ 品牌查找 - "搜一下耐克跑步鞋" ✅ 比价购物 - "淘宝上看看有什么好的蓝牙耳机" ✅ 新品浏览 - "今年有什么新款连衣裙" ✅ 特定条件搜索 - "200元以内的双肩包"
📋 Workflow
标准搜索流程
1. 解析用户意图,提取搜索关键词
2. 通过 device(action="open", uri="taobao://...") 跳转淘宝搜索页
3. 等待淘宝 App 加载搜索结果:device(action="act", kind="wait", timeMs=1500)
4. 拉取页面 UI 树:device(action="snapshot", format="compact")
—— 这是商品名/价格/店铺/销量等文字信息的**唯一来源**
5. 从 snapshot 返回的 text 节点里逐条提取商品信息(详见 Step 3)
6. 基于提取到的具体商品信息回答用户(200字以内,必须包含真实数字和细节)
⚠️ 绝对禁止: 不要用
read_file读截图 PNG(如read_file("/sdcard/.xomniclaw/workspace/screenshots/*.png"))。PNG 是二进制,read_file 会以 UTF-8 解码出大量乱码并撑爆上下文窗口,整个 session 会被context window exceeds limit终止。只用device(action="snapshot")读页面文字。
🔗 Deep Link 构造规则
淘宝搜索 Deep Link 格式:
taobao://s.taobao.com/search?q={关键词}
关键词用 + 连接多个搜索词,示例:
| 用户意图 | 搜索关键词 | Deep Link |
|---|---|---|
| 阿迪达斯今年新款男鞋 | 阿迪达斯+2026+新款+男鞋 | taobao://s.taobao.com/search?q=阿迪达斯+2026+新款+男鞋 |
| 耐克跑步鞋 | 耐克+跑步鞋 | taobao://s.taobao.com/search?q=耐克+跑步鞋 |
| 200元蓝牙耳机 | 蓝牙耳机 | taobao://s.taobao.com/search?q=蓝牙耳机 |
🚀 X-OmniClaw Implementation
Tool: device (DeviceTool — 统一设备控制工具)
⚠️ 重要: 不要使用 shell am start 命令跳转 Deep Link(会因 SecurityException 权限拒绝),必须使用 device(action="open", uri="...") 通过 X-OmniClaw 应用上下文发起 ACTION_VIEW Intent。
Step 1: Deep Link 跳转淘宝搜索页
// 构造搜索关键词
val keyword = "阿迪达斯+2026+新款+男鞋"
val deepLink = "taobao://s.taobao.com/search?q=$keyword"
// 通过 device tool 的 open action + uri 参数跳转
device(action = "open", uri = deepLink)
Step 2: 等待页面加载并拉取 UI 树
// 等待淘宝 App 启动并加载搜索结果
device(action = "act", kind = "wait", timeMs = 1500)
// 拉取页面 UI 树(含所有可见文本节点) —— 商品信息的唯一来源
device(action = "snapshot", format = "compact")
不要在这一步用
screenshot:screenshot只用于内部 grounding(定位点击坐标),不会把图像内容送给你。snapshot才会把页面上每个可见文本节点(含商品名、价格、店铺名)以纯文本方式返回给你。
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.
- 13d ago First seen · 239 lines · 35 tokens per session scan A cf5c084887d7
taobao-search is a skill published in the GitHub repository OPPO-Mente-Lab/X-OmniClaw (261 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 35 tokens to every session and 2,867 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 2026-08-30.
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