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secure-shopper安全购物者

Agent Skill

secure-shopper 用于处理浏览器自动化、网页检查和页面信息提取,适合在 OpenClaw 中需要让 Agent 打开页面、读取网页或验证前端流程时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

15,525

周安装

622

GitHub Stars

1

下载量

5,026
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:secure-shopper(安全购物者)
来源仓库:https://github.com/moodykong/secure-shopper
安装命令:
openclaw skills install secure-shopper
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install secure-shopper

简介

使用安全自动填充(1Password 支持的浏览器填充)进行异步购物研究 + 结帐,并将结果记录到工作区工件中。

SKILL.md

name
secure-shopper
description
Asynchronous shopping research + checkout using secure-autofill (1Password-backed browser filling) with results recorded to workspace artifacts.
metadata
openclaw
emoji
🛒

secure-shopper 🛒

Find items across one or more shopping sites, summarize candidates, and (optionally) place the order using secure-autofill.

This skill is asynchronous: spawn a sub-agent for browsing so the main chat stays responsive.

Prerequisites

Required skills / plugin

  • The secure-autofill skill exists at: ~/.openclaw/skills/secure-autofill/
  • The secure-autofill plugin tools are available:

- vault_suggest - vault_fill

Inherit secure-autofill prerequisites

  • A working non-headless Chrome (many shops block headless)
  • Gateway environment has required env vars (per secure-autofill)

Concrete check:

command -v google-chrome || command -v google-chrome-stable

Configuration (portable)

Skill-local config files:

  • Example (shareable, do not edit): ~/.openclaw/skills/secure-shopper/config.json.example
  • Real (machine-specific, written by onboarding): ~/.openclaw/skills/secure-shopper/config.json

Config keys:

  • goToSites[]: list of default shopping sites (e.g. Amazon, Walmart)
  • location.zip or location.address: used for shipping/availability context
  • preferences.priority: one of:

- relevancy - cheaper - faster - reviews

  • preferences.maxCandidatesPerSite: cap per site (default 5)
  • preferences.safeBrowsing: guardrails to avoid oversized pages / context overflow (applies to all sites)

- startFromSearch: true|false (default true) — prefer a site’s search results page over the homepage/product pages - maxCandidatesPerPass: number (default 3) — extract a few items at a time (then paginate/scroll) - snapshot: limits for browser.snapshot - compact: boolean (default true) - depth: number (default 6) - maxChars: number (default 12000) - fallback: what to do on context_length_exceeded - retryWithTighterSnapshot: boolean (default true) - switchToSearchUrl: boolean (default true)

Initialization / installation / onboarding

Preferred (chat-first)

Ask Boss and then write config.json:

1) Go-to shopping website(s) - Examples: Amazon, Walmart, Target - Store into goToSites[]

2) Zip code OR proximity address - Store into location.zip and/or location.address

3) Preferences - Ask for priority: relevancy vs cheaper vs faster delivery vs higher review scores - Store into preferences.priority (+ optional notes)

After collecting answers, update the real config file.

Optional helper (terminal):

node ~/.openclaw/skills/secure-shopper/scripts/onboard.mjs \
  --sites 'Amazon=https://www.amazon.com|Walmart=https://www.walmart.com' \
  --zip 46202 \
  --priority cheaper

How it works (agent behavior contract)

0) Require a shopping description

The user must provide a description of their shopping task.

  • If they didn’t: stop and ask for it.

1) Honor runtime user prompts

Runtime user instructions (the user’s message for this run) override stored config.

Examples of runtime overrides:

  • “Use Target instead of Amazon.”
  • “Only show Prime-eligible.”
  • “Budget under $50.”

2) Login via secure-autofill (skip if already logged in)

  • Use the configured go-to sites, unless the runtime prompt specifies a site.
  • If the site session appears already authenticated: skip login.
  • Otherwise, use secure-autofill login flow:

- browser.snapshot to get refs - vault_suggest/vault_fill to fill credentials

3) Make the browsing asynchronous

Immediately after accepting the task, respond with something like:

I’m en route to the stores. I’ll notify you when I find the best matches.

Then spawn a sub-agent so the main session is not interrupted.

Implementation note:

  • Use sessions_spawn with a task that includes the shopping description and any runtime overrides.

4) Browse + identify candidates

The sub-agent browses each chosen site, searches, filters, and identifies candidates that fit the user description.

Context-safe browsing (ALL shopping sites)

Many shopping sites can produce extremely large pages/snapshots. To avoid context_length_exceeded failures:

  • Prefer starting from a search results URL (or the site’s search box) rather than the homepage.
  • Use small snapshots:

- browser.snapshot(..., compact=true) - keep depth modest (e.g., 4–8) - set maxChars and/or target a specific container when possible

  • Extract incrementally:

- grab top ~3 candidates, record them, then paginate/scroll and repeat until maxCandidatesPerSite is met

  • If a snapshot still overflows:

- retry with a tighter snapshot (smaller depth / smaller region) - switch to a search URL (/search?q=...) and re-extract

  • Do not “reason through” massive dumps. If the page is huge, reduce the page slice first.

Record results to:

/home/miles/.openclaw/workspace/artifacts/secure_shopping/{timestamp}_shopping_task.json

JSON requirements:

  • Record:

- userPrompt (shopping description) - startTime - endTime - phase (required): - candidates_found | awaiting_accept_deny | awaiting_checkout_confirm | ordered - candidates[]

  • Candidates for the same request must live under the same parent task.
  • Each candidate must include:

- price (string) - reviewScore (string/number) - url - verdict (short) - status: pending | accepted | denied | shopped

Suggested candidate shape:

{
  "site": "Amazon",
  "title": "...",
  "price": "$39.99",
  "reviewScore": "4.6 (12,345)",
  "url": "https://...",
  "verdict": "Best value under $50; good reviews; ships tomorrow",
  "status": "pending"
}

Helper module (optional): scripts/task_io.mjs.

5) Notify user + REQUIRE accept/deny (hard gate)

When browsing is done, you must:

1) Set JSON phase = "awaiting_accept_deny". 2) Translate the JSON into a human-friendly summary. 3) In the same message, require an ACCEPT/DENY decision. Do not end the turn without the prompt.

Mandatory message template (copy this structure):

  • Recommended pick: <title> — <price> — <reviewScore> — <1-line why>
  • Other options: (optional, 1–5 bullets)
  • Choose: Reply with A=accept/deny, B=accept/deny, ... (or “Accept A” / “Deny B”).
  • Next step: “If you accept one: do you want me to checkout, or stop at ready-to-buy?”

Hard rule:

  • If you listed candidates/links but did not include an explicit Choose (ACCEPT/DENY) line, the output is invalid and must be rewritten before sending.

6) Apply accept/deny updates

Once the user replies:

  • Update each candidate status to accepted or denied.
  • Confirm the accepted candidate(s).
  • Set JSON phase:

- awaiting_checkout_confirm if at least one is accepted and checkout is not yet confirmed - keep awaiting_accept_deny if the user’s response is ambiguous / incomplete

7) Checkout (only after explicit confirmation)

Before you click any “Place order” / “Submit” equivalent:

  • Ask for a clear confirmation like: “Confirm checkout for A? (yes/no)”
  • Set JSON phase = "awaiting_checkout_confirm" until confirmed.

If the user confirms checkout:

  • Navigate to the accepted candidate’s URL
  • Add to cart / proceed to checkout
  • Use secure-autofill to input payment/shipping info and submit

If secure-autofill reports an error:

  • Do not guess.
  • Pass the error back to the user.

8) Mark as shopped

If the order is successfully placed:

  • update that candidate’s status to shopped
  • set JSON phase = "ordered"

Notes / guardrails

  • Never paste secrets.
  • Checkout flows often require MFA / SMS verification; ask the user when needed.
  • Prefer fewer high-quality candidates over a long list.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

92.74%
按下载量换算4,661

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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