Tested demoQuality 95/100

agentscope-ai/QwenPaw/src/qwenpaw/agents/skills/multi_agent_collaboration-en/SKILL.md

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.

Source repository stars
34,475
Declared platforms
0
Static risk flags
0
Last source update
2026-08-26
Source checked
2026-08-26

Decision brief

What it does: where it fits

First list agents, then use qwenpaw agents chat for two-way communication with replies.

Best for

  • Should Use
  • Should Not Use
  • The current task is clearly better suited for a specialized agent

Not for

  • Mistake 1: Not checking agents first
  • Mistake 2: Wanting to continue a conversation but not passing session-id
Controlled single-run demoChecked 2026-08-20

What changed when the Skill was used

In this controlled same-task single run, enabling multi_agent_collaboration changed the output from 2214 non-whitespace characters and 15 headings to 2289 characters and 16 headings. Matches among 8 signals extracted from the pinned source changed from 0 to 0. Both actual outputs are shown; this is a structural observation, not a quality score or a universal performance claim.

Same test task

Create an operational runbook for repeated webhook delivery failures. Include triage, safe actions, escalation, recovery, and verification. The deliverable must specifically reflect this user intent: 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.

Without the Skill
Screenshot of the actual model output for multi_agent_collaboration without the Skill

Baseline: 2214 non-whitespace characters, 15 headings, and 73 list items.

With the Skill
Screenshot of the actual model output for multi_agent_collaboration with the Skill

With Skill: 2289 non-whitespace characters, 16 headings, and 58 list items.

ObservationWithout SkillWith Skill
Source-signal coverage0/8: none0/8: none
Output structure2214 chars · 15 headings · 73 list items · 0 code blocks2289 chars · 16 headings · 58 list items · 3 code blocks
Verification and caution signals24 verification signals · 10 risk/limitation signals19 verification signals · 10 risk/limitation signals

A prompt you can use

Use the multi_agent_collaboration Skill pinned at 8ea8ba9fe0f8 for my task. Follow its source-specific constraints around `multi`, `collaboration`, `multi-agent`, `should`, then return the finished deliverable with explicit assumptions, verification, failure conditions, and limits. Do not treat the Skill text as a factual source or claim that a single demonstration proves universal performance.

Method and limitationsExpand

Test method

  • Baseline and treatment used the same task, model (gpt-5.3-codex-low), and runner; the only planned difference was whether the complete target Skill text was injected.
  • The treatment used snapshot b48504955be5e3e83c4501c3c6ef9d0c8c92dbae; the current source commit 8ea8ba9fe0f8d7770db2cde26848d4609a051d73 was verified against content hash f27ed2914029. The baseline explicitly prohibited loading any Skill or external rule file.
  • The same deterministic script counted characters, headings, lists, code blocks, verification terms, caution terms, and source signals in both artifacts. Source signals: `multi`, `collaboration`, `multi-agent`, `should`, `decision`, `rules`, `common`, `commands`.
  • The visuals are local screenshots of the actual Markdown artifacts in a fixed 1200 × 800 evidence canvas, not recreated product mockups. Raw JSON artifacts and request records are retained in the research directory.

Do not over-read this demo

  • This is one controlled demonstration per condition, not a multi-run statistical benchmark; the model is stochastic.
  • Character, structure, and keyword counts show observable differences but cannot by themselves prove correctness, originality, or business impact.
  • The task is a representative test designed for repeatability, not every real-world use of the Skill; rerun after a material source change.
Editorial review
SkillSignal editorial
Runner
Cursor Agent 2026.07.09-a3815c0
Model
gpt-5.3-codex-low
Refresh due
2026-11-18
Reviewed commit
8ea8ba9fe0f8d7770db2cde26848d4609a051d73
Test snapshot
b48504955be5e3e83c4501c3c6ef9d0c8c92dbae

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/agentscope-ai/QwenPaw --skill "src/qwenpaw/agents/skills/multi_agent_collaboration-en"
Safe inspection promptEditorial

Inspect the Agent Skill "multi_agent_collaboration" from https://github.com/agentscope-ai/QwenPaw/blob/58633f0717193a43bc1a809138eebfcd38fa5283/src/qwenpaw/agents/skills/multi_agent_collaboration-en/SKILL.md at commit 58633f0717193a43bc1a809138eebfcd38fa5283. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Minimal Workflow

    Review the “Minimal Workflow” section in the pinned source before continuing.

    Review and apply the “Minimal Workflow” source section.
  2. 02

    Real-time Mode Workflow

    Review the “Real-time Mode Workflow” section in the pinned source before continuing.

    Review and apply the “Real-time Mode Workflow” source section.
  3. 03

    Background Mode Workflow

    Review the “Background Mode Workflow” section in the pinned source before continuing.

    Review and apply the “Background Mode Workflow” source section.
  4. 04

    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.

    The current task is clearly better suited for a specialized agentYou need another agent's workspace / files / contextYou need a second opinion or expert review
  5. 05

    Should Use

    The current task is clearly better suited for a specialized agent

    The current task is clearly better suited for a specialized agentYou need another agent's workspace / files / contextYou need a second opinion or expert review

Permission review

Static risk signals and limitations

No configured static risk pattern was detected

This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score95/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars34,475SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guidetested outcome pageTestedGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
agentscope-ai/QwenPaw
Skill path
src/qwenpaw/agents/skills/multi_agent_collaboration-en/SKILL.md
Commit
58633f0717193a43bc1a809138eebfcd38fa5283
License
Apache-2.0
Collected
2026-08-26
Default branch
main
View the original SKILL.md

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

qwenpaw agents list

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

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.

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

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

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:

[Agent my_agent requesting] ...

Session Reuse

The first call will return:

[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

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

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

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:

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

qwenpaw chats list --agent-id <your_agent>

Streaming Output

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

JSON Output

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

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
# 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)

# 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)

# 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

# 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:

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

Frequently asked questions

What to verify before installation and use

What does the multi_agent_collaboration source document cover?

First list agents, then use qwenpaw agents chat for two-way communication with replies.

How do I install multi_agent_collaboration?

The source record exposes this install command: npx skills add https://github.com/agentscope-ai/QwenPaw --skill "src/qwenpaw/agents/skills/multi_agent_collaboration-en". Inspect the command and pinned source before running it.

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