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customer-memory顾客记忆

Agent Skill

customer-memory 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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

2,036

周安装

84

GitHub Stars

公开资料未说明

下载量

665
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:customer-memory(顾客记忆)
来源仓库:https://github.com/bluecolumnconsulting-lgtm/customer-memory
安装命令:
openclaw skills install customer-memory
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 customer-memory

简介

customer-memory 为 AI 代理提供客户互动、偏好和历史记录的持久记忆能力。

  • 适用于建立客户支持或销售代理,需要长期跟踪客户状态的场景。
  • 通过 BlueColumn 集成实现记忆存储与调用,需配置相关 API 密钥。
  • 安装前请确认权限范围及是否会触发敏感数据读写操作。
  • 适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

SKILL.md

name
customer-memory
description
Give AI agents persistent memory of customer interactions, preferences, and history using BlueColumn. Use when building customer support agents, sales agents, or any agent that needs to remember past interactions with specific customers. Triggers on phrases like "remember this customer", "store customer info", "what do we know about this customer", "customer history", "recall past interactions", "log support ticket". Requires a BlueColumn API key (bc_live_*).

Customer Memory Skill

Persistent customer context for support, sales, and success agents backed by BlueColumn.

Setup

Read TOOLS.md for the BlueColumn API key (bc_live_*). Keys are generated at bluecolumn.ai/dashboard. Store securely — never log or expose them.

Base URL: https://xkjkwqbfvkswwdmbtndo.supabase.co/functions/v1 (BlueColumn's official backend — bluecolumn.ai runs on Supabase Edge Functions)

Store Customer Interaction

curl -X POST .../agent-remember \
  -H "Authorization: Bearer <key>" \
  -d '{
    "text": "Customer: jane@acme.com. Issue: API rate limiting on Developer plan. Resolved by upgrading to Builder. Prefers email communication. Tech stack: Python + LangChain.",
    "title": "Customer: jane@acme.com - 2026-04-14"
  }'

Store Quick Customer Note

curl -X POST .../agent-note \
  -H "Authorization: Bearer <key>" \
  -d '{
    "text": "jane@acme.com prefers async email over live chat",
    "tags": ["customer", "jane@acme.com", "preference"]
  }'

Recall Customer History

curl -X POST .../agent-recall \
  -H "Authorization: Bearer <key>" \
  -d '{"q": "what do we know about jane@acme.com and her past issues?"}'

Workflow

New interaction:

  1. Query customer history first: "what do we know about [customer]?"
  2. Use context to personalize response
  3. After interaction → store summary via /agent-remember
  4. Store key preferences via /agent-note with customer email tag

Support ticket:

  1. Recall similar past issues: "have we seen this error before?"
  2. Resolve using historical context
  3. Log resolution with outcome

Title Convention

"Customer: <email> - <YYYY-MM-DD>"

Use consistent email-based naming so recall queries work accurately across all interactions with the same customer.

Tags to Use

  • Customer email (e.g. jane@acme.com)
  • support, sales, onboarding
  • resolved, pending, escalated
  • Plan tier: free, developer, builder, scale

See references/api.md for full API reference.

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

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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

90.41%
按下载量换算601

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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来源信息

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