Skill Composition: Multi-Skill Collaboration + MCP Composition

Today we move to Multi-Skill Collaboration + MCP Composition, which is important because it connects the Skill design capabilities with MCP Tools / Servers.

We have already learned that a Skill is a capability/work procedure, while an MCP Tool is an external execution capability.
Skill 是“能力/工作方法”,MCP Tool 是“外部执行能力”。

This topic addresses a practical problem: a real Agent cannot realistically have only one capability or call only one Tool.
一个真实 Agent 不可能只会一种能力,也不可能只调用一个 Tool。

Multi-Skill = an Agent has multiple specialized capabilities and selects and combines them according to the task.
Multi-Skill = 一个 Agent 拥有多个专业能力,并根据任务选择和组合这些能力。

MCP Composition = Skills do not implement every external operation themselves; they obtain external capabilities such as databases, APIs, filesystems, and Databricks through MCP.
MCP Composition = Skill 不直接实现所有外部操作,而是通过 MCP 获得数据库、API、文件系统、Databricks 等外部能力。

So, we can simply think this:

Skill = “我知道怎么做”
Skill = “I know how to do it.”

MCP Tool = “我有办法真正去做”
MCP Tool = “I have the ability to actually do it.”

LLM/Agent = “我决定什么时候做什么”
LLM/Agent = “I decide what to do and when to do it.”

Imagine that you have an AI Data Engineering Team, there are three experts in this team. They are: SQL Developer, Data Quality Engineer and Pipeline Auditor.

CapabilitiesSkillMCP
SQL DeveloperSQL Generation SkillDatabricks MCP
Data Quality EngineerDQ Report SkillDatabricks MCP
Pipeline AuditorPipeline Audit SkillDatabricks MCP

The team receiced this “Inspect the sales_orders pipeline, identify data-quality issues, generate SQL validations, and give me a report.”
“检查 sales_orders pipeline,找出数据质量问题,生成 SQL 验证,并给我一份报告。”

Agent may work this way:
User Request


Agent

├── Pipeline Audit Skill
│ │
│ └── MCP → Databricks

├── SQL Generator Skill
│ │
│ └── MCP → Databricks

└── DQ Report Skill

└── MCP → Databricks

The Agent does not put all logic into one giant Skill. Instead, each Skill focuses on one clearly defined responsibility.
Agent 不是把所有逻辑塞进一个巨大 Skill。而是让每个 Skill 专注一个明确的职责。