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retail-knowledge零售知识

Agent Skill

retail-knowledge 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

5,544

周安装

231

GitHub Stars

公开资料未说明

下载量

1,848
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:retail-knowledge(零售知识)
来源仓库:https://github.com/fangwei-frank/retail-knowledge
安装命令:
openclaw skills install retail-knowledge
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 retail-knowledge

简介

零售数字员工的产品知识问答和政策查找。回答客户和员工有关产品、商店政策、促销、常见问题解答等的问题

SKILL.md

name
retail-knowledge
description
>
metadata
openclaw
emoji
📖

Retail Knowledge — Q&A Engine

Overview

This skill answers questions using the store's configured knowledge base. It is the foundational skill for all retail digital employee roles.

Depends on: Knowledge base populated via retail-agent-setup Step 03. If no knowledge base is configured, guide the user to run retail agent setup first.


Query Routing

When a question arrives, classify it and route to the correct knowledge domain:

Query TypeKeywordsKnowledge Domain
Product info产品/商品/成分/规格/面料/尺寸/功效products
Policy退货/换货/退款/保修/三包/质保policies
Promotion活动/优惠/折扣/满减/赠品/促销promotions
FAQ怎么/如何/可以/能否/多久faqs
Store info地址/营业时间/几点/电话/停车store_info
Membership积分/会员/等级/VIP/余额membership
Recommendation推荐/适合/送礼/比较/哪个好→ hand off to product-recommender skill
Inventory有没有/还有/库存/现货→ hand off to inventory-query skill
Complaint坏了/质量问题/投诉/要退→ hand off to complaint-handler skill

Answer Construction Rules

Rule 1: Always ground answers in the knowledge base

Never invent product specs, policy terms, or promotion details. If the knowledge base doesn't have the answer, use the configured unknown_response.

Rule 2: Be specific

Bad: "我们有退货政策" Good: "购买后7天内,商品未使用且保留吊牌,可申请无理由退货。退款将在3个工作日内到账。"

Rule 3: Cite conditions when relevant

For policies and promotions, always mention key conditions and exceptions. Example: "满300减50,不与其他优惠叠加,促销商品除外。"

Rule 4: Match persona tone

Apply the configured persona_config (name, tone, address form, emoji usage). Reference: answer-style-guide.md

Rule 5: Handle unknowns gracefully

If no matching knowledge base entry exists:

  1. Say so honestly (use configured unknown_response)
  2. Offer an alternative: escalate, or suggest the user contact staff
  3. Log the query internally for Step 12 gap digest

Never say "I don't know" bluntly — soften it while staying honest.


Multi-Turn Conversation

Maintain context across turns within a session:

  • Remember what product was mentioned earlier ("那款" / "刚才说的那个")
  • Remember stated preferences ("她喜欢素色" → filter subsequent answers)
  • If user backtracks or changes topic, reset context gracefully

Reference: conversation-patterns.md


Knowledge Base Structure

Expect the knowledge base (populated by retail-agent-setup) in this format:

{
  "products": [ { "sku": "...", "name": "...", "description": "...", ... } ],
  "policy_entries": [ { "policy_id": "...", "title": "...", "full_text": "...", ... } ],
  "promotions": [ { "promo_id": "...", "title": "...", "rules": "...", ... } ],
  "faqs": [ { "faq_id": "...", "question": "...", "answer": "...", ... } ],
  "store_info": { "name": "...", "address": "...", "hours": "...", "phone": "..." },
  "membership": { "levels": [...], "points_rules": "...", "query_method": "..." }
}

Reference: kb-schema.md — full schema with field descriptions.


Fallback Behavior

If the knowledge base is empty or missing a domain:

Missing DomainFallback Response
No products"我们的商品信息正在整理中,请联系店员了解详情。"
No policies"退换货政策请联系门店工作人员确认。"
No promotions"目前暂无特别优惠活动,欢迎关注我们的公众号获取最新信息。"
No store infoEscalate to configured L1 contact

Script: Knowledge Base Search

Use scripts/kb_search.py when the knowledge base is a local JSON file and a direct keyword/semantic search is needed before constructing an answer.

Reference: search-strategy.md — when to use exact match vs. fuzzy match vs. LLM synthesis.

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

75.9%
按下载量换算1,403

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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