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Customer Memory

通过 BlueColumn 后端提供客户记忆能力:用 agent-remember 存储交互摘要,用 agent-note 存储带标签的快捷备注,用 agent-recall 按查询检索客户历史;需要 BlueColumn API 密钥,SKILL.md 提到的 TOOLS.md 未随包提供。

bluecolumnconsulting-lgtm
bluecolumnconsulting-lgtm
热度 43.61
最近更新 2026-05-11 17:43:48
分类:知识依赖:第三方 API / 代码执行应用场景:CRM / 笔记整理 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add customer-memory
Metadata
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.