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Multi Agent Collaboration

OrganizationPopular
agentscope-ai
multi_agent_collaboration

Use this skill when another agent's expertise or context is needed, or when the user explicitly asks to involve another agent. First list agents, then use qwenpaw agents chat for two-way communication with replies.

Overview

Publisheragentscope-ai
RepositoryQwenPaw
Skill namemulti_agent_collaboration
Stars
35.6K
Forks
3.2K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by agentscope-ai on GitHub. Read the source before you install it.

Installation

Install the Multi Agent Collaboration AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/agentscope-ai/QwenPaw/tree/main/src/qwenpaw/agents/skills/multi_agent_collaboration-en
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/agentscope-ai/QwenPaw.git /tmp/QwenPaw
mkdir -p .claude/skills
cp -r /tmp/QwenPaw/src/qwenpaw/agents/skills/multi_agent_collaboration-en .claude/skills/multi_agent_collaboration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Multi Agent Collaboration in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Multi Agent Collaboration on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Multi Agent Collaboration is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Multi-Agent Collaboration

When to Use

Use this skill when you need another agent's expertise, context, workspace content, or collaborative support. If the user explicitly asks a specific agent to participate/assist/answer, you should also use this skill.

Should Use

  • The current task is clearly better suited for a specialized agent
  • You need another agent's workspace / files / context
  • You need a second opinion or expert review
  • The user explicitly asks for a specific agent to participate or to invoke another agent

Should Not Use

  • You can complete the task on your own and the user has not explicitly asked to invoke another agent
  • It is just a normal Q&A that does not require a specialized agent
  • Information is insufficient -- you should ask the user for clarification first
  • You just received a message from Agent B -- do not call Agent B again to avoid loops

Decision Rules

  1. If the user explicitly requests invoking another agent, prioritize following the request
  2. Otherwise, if you can do it yourself, do not invoke another agent
  3. Check agents before invoking -- do not guess IDs
  4. When context continuation is needed, you must pass --session-id
  5. Do not call back the source agent

Most Common Commands

1) First Query Available Agents

bash
qwenpaw agents list

2) Start a New Conversation (Real-time Mode)

bash
qwenpaw agents chat \
  --from-agent <your_agent> \
  --to-agent <target_agent> \
  --text "[Agent <your_agent> requesting] ..."

3) Submit a Complex Task (Background Mode)

Complex tasks include: data analysis, report generation, batch processing, external API calls, etc.

bash
qwenpaw agents chat --background \
  --from-agent <your_agent> \
  --to-agent <target_agent> \
  --text "[Agent <your_agent> requesting] ..."

Output:

[TASK_ID: xxx-xxx-xxx]
[SESSION: ...]

4) Query Background Task Status

bash
qwenpaw agents chat --background --task-id <task_id>

Important: Do not query frequently! After submitting a task:

  1. Do not block - Continue handling other tasks or work
  2. Wait a reasonable time before querying - Choose based on task complexity:
    • Simple analysis: query after 10-20 seconds
    • Complex analysis: query after 30-60 seconds
    • Batch processing: query after 1-3 minutes
  3. During the wait - You can reply to the user, handle other requests, or execute other tasks

5) Continue an Existing Conversation

bash
qwenpaw agents chat \
  --from-agent <your_agent> \
  --to-agent <target_agent> \
  --session-id "<session_id>" \
  --text "[Agent <your_agent> requesting] ..."

Key points:

  • Not passing --session-id = new conversation
  • Passing --session-id = continue conversation (context preserved)
  • Use --background for complex tasks; record the task_id after submission

Task Mode Selection

Real-time Mode vs Background Mode

Task TypeMode to UseCommand
Simple quick queryReal-time modeqwenpaw agents chat
Complex task (data analysis, batch processing, etc.)Background modeqwenpaw agents chat --background

Examples of complex tasks:

  • Analyzing large amounts of data or log files
  • Generating detailed reports
  • Batch processing files (10+ files)
  • Calling slow external APIs
  • Independent tasks that need parallel execution

Decision criteria: If you are unsure how long a task will take, or if the task is complex, prefer background mode.


Minimal Workflow

Real-time Mode Workflow

1. Determine whether another agent is needed, or whether the user explicitly requested it
2. qwenpaw agents list
3. qwenpaw agents chat to start a conversation
4. Record [SESSION: ...] from the output
5. Include --session-id when context continuation is needed later

Background Mode Workflow

1. Determine whether the task is complex (data analysis, report generation, etc.)
2. qwenpaw agents list
3. qwenpaw agents chat --background to submit the task
4. Record [TASK_ID: ...] from the output
5. Continue handling other work
6. Wait a reasonable time (30-60 seconds) before querying status
7. Use --background --task-id to query results

Key Rules

Required Parameters

qwenpaw agents chat must include all of the following:

  • --from-agent
  • --to-agent
  • --text

Identity Prefix

Messages should begin with the following prefix:

text
[Agent my_agent requesting] ...

Session Reuse

The first call will return:

text
[SESSION: your_agent:to:target_agent:...]

For subsequent follow-ups, you must copy this session_id and pass it via --session-id.


Brief Examples

User Explicitly Requests Invoking Another Agent

bash
qwenpaw agents list

qwenpaw agents chat \
  --from-agent scheduler_bot \
  --to-agent finance_bot \
  --text "[Agent scheduler_bot requesting] User explicitly asked to consult finance_bot. Please answer what pending financial tasks are there."

New Conversation

bash
qwenpaw agents chat \
  --from-agent scheduler_bot \
  --to-agent finance_bot \
  --text "[Agent scheduler_bot requesting] What pending financial tasks are there today?"

Continue Conversation

bash
qwenpaw agents chat \
  --from-agent scheduler_bot \
  --to-agent finance_bot \
  --session-id "scheduler_bot:to:finance_bot:1710912345:a1b2c3d4" \
  --text "[Agent scheduler_bot requesting] Expand on item 2"

Common Mistakes

Mistake 1: Not checking agents first

Do not guess agent IDs. First run:

bash
qwenpaw agents list

Mistake 2: Wanting to continue a conversation but not passing session-id

This will create a new conversation, losing context.

Mistake 3: Calling back the source agent

If you just received a message from Agent B, do not call Agent B again.


Optional Commands

View Existing Sessions

bash
qwenpaw chats list --agent-id <your_agent>

Streaming Output

bash
qwenpaw agents chat \
  --from-agent <your_agent> \
  --to-agent <target_agent> \
  --mode stream \
  --text "[Agent <your_agent> requesting] ..."

JSON Output

bash
qwenpaw agents chat \
  --from-agent <your_agent> \
  --to-agent <target_agent> \
  --json-output \
  --text "[Agent <your_agent> requesting] ..."

Full Parameter Reference

qwenpaw agents list

Parameters:

  • --base-url (optional): Override the API address

No required parameters -- just run it directly.

qwenpaw agents chat

Required parameters (real-time mode):

  • --from-agent: Sender agent ID
  • --to-agent: Target agent ID
  • --text: Message content

Background task parameters:

  • --background: Background task mode
  • --task-id: Query task status (used together with --background)

Optional parameters:

  • --session-id: Reuse session context (copy from previous output)
  • --new-session: Force create a new session (even if session-id is passed)
  • --mode: stream (streaming) or final (complete, default)
  • --timeout: Timeout in seconds (default 300)
  • --json-output: Output full JSON instead of plain text
  • --base-url: Override the API address

Background Task Mode Details

When to Use Background Mode?

When the task is a complex task, use --background to submit it to the background:

Should use background mode:

  • Data analysis (analyzing logs, computing statistics)
  • Report generation (generating long reports or documents)
  • Batch processing (processing multiple files)
  • External API calls (calling slow services)
  • Complex tasks with uncertain duration

Does not need background mode:

  • Simple quick queries
  • Tasks that are clearly going to complete quickly

Background Task Examples

Submitting a Complex Task
bash
qwenpaw agents chat --background \
  --from-agent scheduler \
  --to-agent data_analyst \
  --text "[Agent scheduler requesting] Analyze user behavior in /data/logs/2026-03-26.log and generate a detailed report"

Output:

[TASK_ID: 20802ea3-832d-4fb4-86f0-666ad79fcc80]
[SESSION: scheduler:to:data_analyst:1774516703206:ec02e542]

✅ Task submitted successfully

Check status with:
  qwenpaw agents chat --background --task-id 20802ea3-...
Querying Task Status

Important: Do not block after submitting!

  1. Continue handling other work - Reply to other user questions, execute other tasks
  2. Query at the right time - After finishing other work, or when the user asks about progress
  3. If you must wait - Use a reasonable interval (10-60 seconds); do not query immediately
bash
# Method 1: Query after handling other tasks (recommended)
# After submitting the task, continue with the user's other requests
# Query at an appropriate time:
qwenpaw agents chat --background \
  --task-id 20802ea3-832d-4fb4-86f0-666ad79fcc80

# Method 2: If you must wait, use a reasonable interval
sleep 30 && qwenpaw agents chat --background \
  --task-id 20802ea3-832d-4fb4-86f0-666ad79fcc80

Status Descriptions:

Task status has two layers:

  • Outer status (API response): submitted -> pending -> running -> finished
  • Inner status (only when outer status is finished): completed (success) or failed (failure)

Possible outputs:

  1. Submitted (may be seen when querying immediately after submission):
[TASK_ID: 20802ea3-832d-4fb4-86f0-666ad79fcc80]
[STATUS: submitted]

📤 Task submitted, waiting to start...

💡 Don't wait - continue with other work!
   Check again in a few seconds:
  qwenpaw agents chat --background --task-id 20802ea3-...
  1. Pending:
[TASK_ID: 20802ea3-832d-4fb4-86f0-666ad79fcc80]
[STATUS: pending]

⏸️  Task is pending in queue...

💡 Don't wait - handle other work first!
   Check again in a few seconds:
  qwenpaw agents chat --background --task-id 20802ea3-...
  1. Running:
[TASK_ID: 20802ea3-832d-4fb4-86f0-666ad79fcc80]
[STATUS: running]

⏳ Task is still running...
   Started at: 1774516703

💡 Don't wait - continue with other tasks first!
   Check again later (10-30s):
  qwenpaw agents chat --background --task-id 20802ea3-...
  1. Completed successfully:
[TASK_ID: 20802ea3-832d-4fb4-86f0-666ad79fcc80]
[STATUS: finished]

✅ Task completed

(Task result content...)
  1. Failed:
[TASK_ID: 20802ea3-832d-4fb4-86f0-666ad79fcc80]
[STATUS: finished]

❌ Task failed

Error: (Error message...)

Query Interval Strategy

Do not query frequently! After submitting a task, you should:

  1. Continue handling other work - Do not block; go complete other tasks
  2. Wait a reasonable time before querying - Choose the interval based on task complexity
  3. Avoid blocking the current flow - This is the core value of background tasks
Task TypeSuggested First QuerySubsequent IntervalWhat to Do While Waiting
Simple analysisAfter 10 seconds5-10 secondsHandle other user requests
Complex analysisAfter 30 seconds10-20 secondsComplete other parts of the current conversation
Batch processingAfter 1 minute20-30 secondsExecute other independent tasks
Very large tasksAfter 2 minutes30-60 secondsContinue with the user's other work
Recommended Approach

Method 1: Query after handling other tasks (recommended)

bash
# 1. Submit the task, record the task_id
qwenpaw agents chat --background ...
# Returns task_id

# 2. Continue handling the user's other requests or tasks
# (e.g., answer other questions, perform other operations)

# 3. Query the result at an appropriate time
# (e.g., after finishing the current task, or when the user asks about progress)
qwenpaw agents chat --background --task-id <id>

Method 2: Timed polling (if you must wait)

bash
# Incrementally increasing intervals, fast first then slow
sleep 10 && qwenpaw agents chat --background --task-id <id>
sleep 20 && qwenpaw agents chat --background --task-id <id>
sleep 30 && qwenpaw agents chat --background --task-id <id>
Do Not Do This
bash
# Wrong: querying too frequently
while true; do
    qwenpaw agents chat --background --task-id <id>
    sleep 1  # Too frequent!
done

Help Information

Use -h at any time to view detailed help:

bash
qwenpaw agents -h
qwenpaw agents list -h
qwenpaw agents chat -h

Frequently asked questions

What does the Multi Agent Collaboration AI skill do?

Use this skill when another agent's expertise or context is needed, or when the user explicitly asks to involve another agent. First list agents, then use qwenpaw agents chat for two-way communication with replies.

Why use Multi Agent Collaboration on TypingMind?

Because you install it once and use it with any model. Multi Agent Collaboration is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Multi Agent Collaboration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/agentscope-ai/QwenPaw/tree/main/src/qwenpaw/agents/skills/multi_agent_collaboration-en. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Multi Agent Collaboration?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Multi Agent Collaboration?

As many as you like. As long as a model supports skills, you can use Multi Agent Collaboration with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Multi Agent Collaboration AI skill free?

Yes. It is published on GitHub by agentscope-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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