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Multi-Role OpenClaw on Feishu - One AI, Multiple Experts

用通俗语言讲解如何在飞书上实现单Agent多角色和多Agents多角色，让你的AI助手在不同群里扮演不同角色。

V
Victor.Chen
2026年3月21日

Source: linux.do community discussion

Core Concepts

What Is an Agent?

Think of an Agent as an "AI employee". It has a name, a personality, skills, and it gets work done.

What Is a Role (Persona)?

A role is the "outfit" this employee wears and the way they "talk". In different groups, it plays different roles:

  • Tech group → NodeJS expert
  • Design group → UI consultant
  • Operations group → data analyst

Comparing the Three Approaches

Approach In Plain Words Pros Cons
Single agent, multiple roles One employee changing uniforms per shift Simple to manage, saves resources Capabilities capped by that one agent
Multiple agents, multiple roles Several employees, each with their own job Each has a specialty, stronger overall Harder to manage, heavier on resources
One master, many sub-agents A butler leading a crew of specialists Tasks decompose and run automatically Complex setup, needs human oversight

Approach 1: Single Agent, Multiple Roles (Recommended for Beginners)

How to Think About It

Imagine you have an all-purpose "little assistant". Normally it's just an ordinary bot, but once you add it to the "NodeJS Discussion Group", it automatically becomes a "NodeJS expert" — it speaks professionally and knows the technical details.

Implementation Steps

  1. Create one Agent (call it "General Assistant", for example)
  2. Design a persona for each group (e.g. a "NodeJS Group Persona")
  3. Bind the persona to the group (the bot automatically uses the matching persona after joining)

What It Looks Like in Practice

Group Bot Persona Answering Style
Tech discussion group NodeJS expert This issue is usually caused by event-loop blocking; I'd check...
Design discussion group UI consultant From a UX perspective, this button's color contrast is too low...
Operations data group Data analyst Based on last week's data, conversion dropped 15%...

Advantages

  • Cheaper: one Agent only, low API costs
  • Simple: only one entity to manage
  • Flexible: swap personas anytime

Approach 2: Multiple Agents, Multiple Roles (For Advanced Users)

How to Think About It

You now have several specialist employees: Wang writes code, Li handles design, Zhang writes copy. Each employee is independent, with their own skills and persona.

Implementation Steps

  1. Create multiple Agents (code expert, design expert, copywriting expert)
  2. Bind an independent persona and skill set to each Agent
  3. Add different Agents to different groups

What It Looks Like in Practice

Agent Specialty Skills
Code expert Writing code, debugging Dev tools, documentation lookup
Design expert Design work, image editing Design tools, color-palette analysis
Copywriting expert Copywriting, polishing Writing templates, grammar checks

Advantages

  • Specialized: each Agent focuses on one thing and does it better
  • Independent skills: different Agents can get different tools
  • Parallel work: multiple Agents can work at the same time

Approach 3: One Master, Many Sub-Agents (Advanced Play)

How to Think About It

You have a "project manager" (the master Agent) with a crew of "specialist employees" (sub-agents). You only talk to the "project manager"; it automatically assigns tasks to the right workers and gathers the results back for you.

Workflow

User → Project manager → Assign tasks → Each expert executes → Aggregate results

A Plain Analogy

It's like the "project manager" at a renovation company:

  • The project manager sends the electrician to run the wiring
  • Sends the plumber to install the pipes
  • Sends the carpenter to build the cabinets
  • Finally inspects, wraps everything up, and hands you the keys

Caveats

Today it can't quite "finish everything while you sleep". In practice you may run into:

  • Tasks dropping midway (network issues, API timeouts)
  • Poor task planning (the AI assigns work badly)
  • Key decisions that still need a human sign-off

Treat "one master, many sub-agents" as an "advanced assistant", not a "fully automated factory".

FAQ

Q: What happens if multiple Agents chat in the same group?

Not recommended. Reasons:

  • Noise: every Agent sees every message in the group, but not every message is relevant to it
  • Possible infinite loops: Agent A @-mentions Agent B, Agent B replies @-mentioning Agent A, back and forth forever
  • Confusion: you can't tell who is answering you

Q: Which approach should I pick?

Your Situation Recommended Approach
Just starting out, want something simple Single agent, multiple roles
Need a clear division of labor Multiple agents, multiple roles
Want AI to run complex projects One master, many sub-agents

Q: How do I share this with friends?

"Single agent, multiple roles" is the easiest:

  1. Create one general-purpose Agent
  2. Create a custom persona for your friend's group
  3. Add the Agent to the group and bind the persona
  4. Your friend can now chat with a "dedicated expert"

Summary

Approach One-Liner Best For
Single agent, multiple roles One bot, costume changes Beginners, personal users
Multiple agents, multiple roles Multiple bots, each owns its turf Teams, professional users
One master, many sub-agents A butler leading a crew Advanced users, complex tasks

Start with "single agent, multiple roles", then explore the more advanced approaches once you're comfortable.

原文来源

linux.do community

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