Secure Shopper

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

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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: