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groupongroupon 搜索

Agent Skill

groupon 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

6,805

周安装

278

GitHub Stars

公开资料未说明

下载量

2,180
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:groupon(groupon 搜索)
来源仓库:https://github.com/ivangdavila/groupon
安装命令:
openclaw skills install groupon
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 groupon

简介

groupon 用于查找、比较和审查 Groupon 优惠券详情。

  • 适合优惠信息调研和兑换规则分析。
  • 通过 clawhub 安装,命令为 openclaw skills install groupon。
  • 建议确认 API 调用频率和地区可用性限制。
  • groupon 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
Groupon
slug
groupon
version
1.0.0
homepage
https://clawic.com/skills/groupon
description
Find, compare, and vet Groupon vouchers with fine-print checks, refund rules, and redemption planning.
changelog
Initial release with SAVE deal screening, merchant risk checks, and voucher recovery workflows.
metadata
{"clawdbot":{"emoji":"🎟️","requires":{"bins":[],"config":["~/groupon/"]},"os":["linux","darwin","win32"],"configPaths":["~/groupon/"]}}

When to Use

Use this skill when the user wants help with Groupon deals, vouchers, or local offers and needs more than a headline discount.

Use it for discovery, shortlist building, merchant validation, fine-print review, booking friction checks, post-purchase triage, and refund or support recovery planning.

Architecture

Memory lives in ~/groupon/. If ~/groupon/ does not exist, run setup.md. See memory-template.md for structure and status values.

~/groupon/
├── memory.md       # City, budget posture, category preferences, and hard no rules
├── shortlists.md   # Ranked deals with verdicts and caveats
├── purchases.md    # Bought, gifted, or expiring vouchers with next actions
└── incidents.md    # Booking failures, merchant disputes, refund attempts, support notes

Quick Reference

Use the smallest file needed for the current task.

TopicFile
Setup and activation behaviorsetup.md
Memory structure and status modelmemory-template.md
SAVE scorecard and output formatdeal-qualification.md
Merchant trust and fine-print checksmerchant-checks.md
Category-specific watchoutscategory-playbook.md
Refund, booking, and support recoveryrecovery.md

Core Rules

1. Start with intent, not the discount badge

  • Capture the real job first: category, city, date window, party size, budget, and travel tolerance.
  • Distinguish "find something fun under budget" from "check whether this exact voucher is worth buying."
  • A 70% headline discount is irrelevant if the user cannot redeem it on the needed day or for the needed group size.

2. Run the SAVE screen before recommending anything

Use the SAVE workflow from deal-qualification.md:

  • Scope the real use case and deal type.
  • Assess merchant quality and booking friction.
  • Verify every restriction in the fine print.
  • Estimate the true out-of-pocket cost and redemption effort.

No recommendation is complete until SAVE ends with a clear verdict.

3. Treat fine print as blocking data

  • Always read the restriction block, not just the title and hero price.
  • Check validity windows, excluded days, one-per-person rules, "new customers only" language, auto-gratuity, add-ons, taxes, paid value vs promo value, and required booking channels.
  • If any critical term is missing or ambiguous, say so plainly and downgrade confidence.

4. Optimize for redeemability, not theoretical savings

  • Prefer deals the user can actually book this week, in the right neighborhood, with acceptable scheduling friction.
  • Penalize phone-only booking, narrow redemption windows, poor recent reviews, and merchants that seem hard to reach.
  • If the merchant fit is weak, recommend a better option even when the headline discount is smaller.

5. Separate deal types before making policy claims

  • Local services, goods, getaways, and ticketed offers behave differently on booking, shipping, expiration, and refunds.
  • Do not promise refund outcomes from memory alone. Confirm the live deal type, voucher status, and current Groupon policy before giving a final answer.
  • In post-purchase workflows, document whether the voucher is unused, booked, redeemed, shipped, or disputed.

6. Keep money-impacting actions user-approved

  • The agent may search, compare, shortlist, draft support messages, and guide checkout or redemption.
  • Buying, gifting, booking, marking redeemed, or submitting a refund request needs explicit user confirmation.
  • Never store payment details, login secrets, full voucher barcodes, or claim codes in local files.

7. Leave a decision-ready output every time

Return the final recommendation in this structure:

Verdict: Recommend | Recommend with caveats | Skip
Best fit: [deal or category]
Why it wins: [up to 3 bullets]
Blocking terms: [if any]
True cost: [price + known extras]
Next step: [buy now, hold, compare, contact merchant, request support]

Common Traps

TrapWhy It FailsBetter Move
Ranking by discount percent aloneInflated list prices make weak offers look amazingCompare true cost, merchant quality, and redemption friction
Ignoring neighborhood and timingA cheap deal two neighborhoods away at the wrong hour is not valueScore location, travel time, and usable dates early
Skimming past "restrictions apply"The deal can become unusable for weekends, groups, or repeat visitsRead the full fine print before any recommendation
Assuming every voucher refunds the same wayGroupon rules vary by deal type and current statusClassify the deal first, then use recovery.md
Treating service deals like retail productsTrust, availability, and upsells dominate the real outcomeRun merchant checks and booking friction checks
Recommending merchants with stale or weak signalsClosed, overloaded, or badly rated merchants create support painUse recent reviews and direct booking clues, not score alone
Jumping to checkout without extrasMandatory gratuity, taxes, parking, drinks, or upgrades erase savingsEstimate true cost before telling the user to buy
Logging sensitive voucher detailsLocal notes can become a privacy or fraud problemStore only what is needed to follow up safely

External Endpoints

EndpointData SentPurpose
https://www.groupon.com/*search terms, city or ZIP, deal URLs, and normal browser navigation signalsdiscovery, fine-print review, and support page lookup
https://help.groupon.com/*issue categories, deal type references, and support navigationrefund, booking, and policy verification

No other data is sent externally.

Security & Privacy

Data that leaves your machine:

  • Search terms, location context, and deal URLs sent to Groupon pages during discovery and verification.
  • Optional support or booking context the user explicitly asks to submit.

Data that stays local:

  • Preferences, shortlist decisions, and follow-up notes in ~/groupon/.

This skill does NOT:

  • Access files outside ~/groupon/
  • Store payment cards, login secrets, or full voucher codes
  • Buy, redeem, or request refunds without explicit user approval
  • Claim merchant quality or refund certainty when the evidence is weak

Trust

By using this skill, deal-search context may be sent to Groupon and, when the user chooses to proceed, to the merchant tied to a specific offer. Only install if you trust Groupon and the selected merchant with that context.

Scope

This skill ONLY:

  • Finds and compares Groupon offers
  • Screens merchants, restrictions, and usable value
  • Guides checkout, booking, and recovery workflows with explicit approval boundaries

This skill NEVER:

  • Guarantee availability, savings, or refund outcomes
  • Hide uncertainty about fine print or merchant quality
  • Spend money or reveal voucher secrets without the user's instruction

Related Skills

Install with clawhub install <slug> if user confirms:

  • buy — evaluate real value, compare alternatives, and avoid bad purchases
  • shopping — broaden the search when Groupon is not the best channel
  • booking — plan reservations and compare travel or stay options
  • tripadvisor — validate hospitality and attraction quality with broader review signals
  • travel — connect local offers with larger trip planning decisions

Feedback

  • If useful: clawhub star groupon
  • Stay updated: clawhub sync

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

92.44%
按下载量换算2,015

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

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。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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