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Collaboration Models Development Guide

This document provides detailed configuration examples, real-world cases, and technical implementation details for collaboration models.

Basic Concepts: Please read Collaboration Models Concepts first to understand the basic concepts.

Pipeline Configuration Details

Complete YAML Configuration Example

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: dev-pipeline-team
  namespace: default
spec:
  # Collaboration model: pipeline
  collaborationModel: "pipeline"

  # Team members (defined in execution order)
  members:
    # Step 1: Developer
    - name: "developer"
      role: "leader"
      botRef:
        name: developer-bot
        namespace: default
      prompt: |
        You are a senior software developer.
        Your task is to implement the feature based on the requirements.
        Write clean, well-documented code following best practices.

    # Step 2: Code Reviewer
    - name: "reviewer"
      role: "member"
      botRef:
        name: reviewer-bot
        namespace: default
      prompt: |
        You are a code reviewer.
        Review the code for:
        - Code quality and style
        - Potential bugs and security issues
        - Performance optimization opportunities
        Provide constructive feedback.

    # Step 3: Test Engineer
    - name: "tester"
      role: "member"
      botRef:
        name: tester-bot
        namespace: default
      prompt: |
        You are a QA engineer.
        Create comprehensive tests including:
        - Unit tests
        - Integration tests
        - Edge case scenarios
        Execute tests and report results.

    # Step 4: Deployment Expert
    - name: "deployer"
      role: "member"
      botRef:
        name: deployer-bot
        namespace: default
      prompt: |
        You are a DevOps engineer.
        Prepare the deployment:
        - Build the application
        - Create deployment configuration
        - Document deployment steps

Real-World Case: Blog Article Production Pipeline

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: blog-production-pipeline
  namespace: default
spec:
  collaborationModel: "pipeline"
  members:
    - name: "writer"
      role: "leader"
      botRef:
        name: content-writer-bot
        namespace: default
      prompt: "Write an engaging blog post on the given topic with proper structure and flow."

    - name: "editor"
      role: "member"
      botRef:
        name: content-editor-bot
        namespace: default
      prompt: "Edit the content for grammar, clarity, and readability. Improve sentence structure and flow."

    - name: "seo-optimizer"
      role: "member"
      botRef:
        name: seo-bot
        namespace: default
      prompt: "Optimize the content for SEO: add meta descriptions, keywords, and improve headings."

    - name: "publisher"
      role: "member"
      botRef:
        name: publisher-bot
        namespace: default
      prompt: "Format the content for publication and create a publishing checklist."

Pipeline Best Practices

✅ Recommended

  • Each stage has single clear responsibility
  • Control pipeline length (max 6 steps recommended)
  • Clear input/output expectations in each Bot's prompt
  • Add error handling and validation steps

❌ Avoid

  • Overly long pipelines (more than 8 steps)
  • Overlapping responsibilities between steps
  • Missing intermediate validation
  • Illogical Bot ordering

Optimized Pipeline Design Example

members:
  - name: "validator"        # First validate input
  - name: "processor"        # Then process
  - name: "quality-check"    # Quality check
  - name: "finalizer"        # Finally complete

Route Configuration Details

Complete YAML Configuration Example

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: tech-support-route-team
  namespace: default
spec:
  # Collaboration model: route
  collaborationModel: "route"

  # Team members
  members:
    # Leader: Routing Decision Maker
    - name: "router"
      role: "leader"
      botRef:
        name: router-bot
        namespace: default
      prompt: |
        You are a technical support router.
        Analyze the user's question and route it to the appropriate specialist:
        - Frontend issues → frontend-expert
        - Backend issues → backend-expert
        - Database issues → database-expert
        - DevOps/Infrastructure issues → devops-expert

        Provide a brief analysis of why you chose this specialist.

    # Expert 1: Frontend Specialist
    - name: "frontend-expert"
      role: "member"
      botRef:
        name: frontend-specialist-bot
        namespace: default
      prompt: |
        You are a frontend development expert specializing in:
        - React, Vue, Angular
        - HTML, CSS, JavaScript/TypeScript
        - UI/UX best practices
        - Browser compatibility

        Provide detailed, actionable solutions to frontend problems.

    # Expert 2: Backend Specialist
    - name: "backend-expert"
      role: "member"
      botRef:
        name: backend-specialist-bot
        namespace: default
      prompt: |
        You are a backend development expert specializing in:
        - Python, Java, Node.js
        - RESTful API design
        - Microservices architecture
        - Performance optimization

        Provide detailed, actionable solutions to backend problems.

    # Expert 3: Database Specialist
    - name: "database-expert"
      role: "member"
      botRef:
        name: database-specialist-bot
        namespace: default
      prompt: |
        You are a database expert specializing in:
        - SQL and NoSQL databases
        - Query optimization
        - Database design and normalization
        - Indexing strategies

        Provide detailed, actionable solutions to database problems.

    # Expert 4: DevOps Specialist
    - name: "devops-expert"
      role: "member"
      botRef:
        name: devops-specialist-bot
        namespace: default
      prompt: |
        You are a DevOps expert specializing in:
        - Docker and Kubernetes
        - CI/CD pipelines
        - Cloud infrastructure (AWS, GCP, Azure)
        - Monitoring and logging

        Provide detailed, actionable solutions to DevOps problems.

Real-World Case: Multi-Language Programming Q&A Platform

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: programming-qa-route-team
  namespace: default
spec:
  collaborationModel: "route"
  members:
    - name: "language-router"
      role: "leader"
      botRef:
        name: language-router-bot
        namespace: default
      prompt: |
        Analyze the programming question and route to the appropriate language expert:
        - Python questions → python-expert
        - JavaScript/TypeScript → js-expert
        - Java/Kotlin → jvm-expert
        - Go → go-expert

    - name: "python-expert"
      role: "member"
      botRef:
        name: python-bot
        namespace: default
      prompt: "You are a Python expert. Answer Python-related questions with code examples and best practices."

    - name: "js-expert"
      role: "member"
      botRef:
        name: javascript-bot
        namespace: default
      prompt: "You are a JavaScript/TypeScript expert. Provide modern ES6+ solutions and TypeScript types."

    - name: "jvm-expert"
      role: "member"
      botRef:
        name: java-bot
        namespace: default
      prompt: "You are a JVM expert. Answer Java and Kotlin questions with attention to performance."

    - name: "go-expert"
      role: "member"
      botRef:
        name: go-bot
        namespace: default
      prompt: "You are a Go expert. Provide idiomatic Go solutions emphasizing concurrency."

Route Best Practices

✅ Recommended

  • Clear and accurate routing logic in Leader Bot
  • Well-defined expert domains without overlap
  • Detailed routing rules for Leader
  • Include default routing for unknown cases

❌ Avoid

  • Ambiguous routing rules
  • Expert domain overlap causing selection difficulty
  • Missing default handling path
  • Overly complex routing decisions

Clear Routing Rules Example

- name: "router"
  prompt: |
    Route questions based on clear criteria:
    - If about UI/UX/styling → frontend-expert
    - If about API/database/server → backend-expert
    - If about deployment/infrastructure → devops-expert
    - If unclear or mixed → general-expert (default)

Coordinate Configuration Details

Complete YAML Configuration Example

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: market-research-coordinate-team
  namespace: default
spec:
  # Collaboration model: coordinate
  collaborationModel: "coordinate"

  # Team members
  members:
    # Leader: Coordinator
    - name: "coordinator"
      role: "leader"
      botRef:
        name: coordinator-bot
        namespace: default
      prompt: |
        You are a market research coordinator.

        PHASE 1 - Task Decomposition:
        Break down the market research task into parallel workstreams:
        1. Competitor analysis
        2. Customer sentiment analysis
        3. Market trend analysis
        4. Data collection and statistics

        Assign each workstream to the appropriate specialist.

        PHASE 2 - Result Synthesis:
        After receiving all reports, synthesize them into a comprehensive
        market research report with:
        - Executive summary
        - Key findings from each area
        - Strategic recommendations
        - Data visualizations and insights

    # Expert 1: Competitor Analyst
    - name: "competitor-analyst"
      role: "member"
      botRef:
        name: competitor-analyst-bot
        namespace: default
      prompt: |
        You are a competitor analysis specialist.
        Analyze:
        - Main competitors and market share
        - Competitor strategies and positioning
        - Strengths and weaknesses
        - Competitive advantages

        Provide a detailed competitor analysis report.

    # Expert 2: Customer Insights Analyst
    - name: "customer-analyst"
      role: "member"
      botRef:
        name: customer-analyst-bot
        namespace: default
      prompt: |
        You are a customer insights specialist.
        Analyze:
        - Customer demographics and segments
        - Customer pain points and needs
        - Customer satisfaction and feedback
        - Buying behavior patterns

        Provide a detailed customer analysis report.

    # Expert 3: Trend Analyst
    - name: "trend-analyst"
      role: "member"
      botRef:
        name: trend-analyst-bot
        namespace: default
      prompt: |
        You are a market trend specialist.
        Analyze:
        - Industry trends and future outlook
        - Emerging technologies and innovations
        - Regulatory and policy changes
        - Market opportunities and threats

        Provide a detailed trend analysis report.

    # Expert 4: Data Analyst
    - name: "data-analyst"
      role: "member"
      botRef:
        name: data-analyst-bot
        namespace: default
      prompt: |
        You are a data analytics specialist.
        Analyze:
        - Market size and growth rates
        - Statistical trends and patterns
        - Revenue forecasts
        - Key performance indicators

        Provide a detailed data analysis report with visualizations.

Real-World Case: Comprehensive Code Review Team

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: comprehensive-code-review-team
  namespace: default
spec:
  collaborationModel: "coordinate"
  members:
    - name: "review-coordinator"
      role: "leader"
      botRef:
        name: review-coordinator-bot
        namespace: default
      prompt: |
        Coordinate a comprehensive code review:
        1. Distribute code to specialized reviewers
        2. Collect all review feedback
        3. Synthesize into a final review report with prioritized action items

    - name: "security-reviewer"
      role: "member"
      botRef:
        name: security-bot
        namespace: default
      prompt: "Review code for security vulnerabilities, injection risks, and authentication issues."

    - name: "performance-reviewer"
      role: "member"
      botRef:
        name: performance-bot
        namespace: default
      prompt: "Review code for performance issues, optimization opportunities, and scalability."

    - name: "quality-reviewer"
      role: "member"
      botRef:
        name: quality-bot
        namespace: default
      prompt: "Review code quality, maintainability, design patterns, and best practices."

    - name: "test-reviewer"
      role: "member"
      botRef:
        name: test-bot
        namespace: default
      prompt: "Review test coverage, test quality, and identify missing test scenarios."

Coordinate Best Practices

✅ Recommended

  • Leader has clear task decomposition strategy
  • Expert Bot responsibilities don't overlap
  • Leader needs strong aggregation capability
  • Control parallel Bot count (3-5 optimal)

❌ Avoid

  • Unbalanced task decomposition
  • Too many parallel Bots (more than 7)
  • Leader lacks aggregation guidance
  • Inconsistent expert output formats

Structured Coordination Example

- name: "coordinator"
  prompt: |
    STEP 1: Decompose task into 4 parallel workstreams
    STEP 2: Assign to specialists
    STEP 3: Collect all reports in structured format
    STEP 4: Synthesize into unified report with:
      - Executive summary
      - Key findings per specialist
      - Recommendations

Collaborate Configuration Details

Complete YAML Configuration Example

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: product-brainstorm-team
  namespace: default
spec:
  # Collaboration model: collaborate
  collaborationModel: "collaborate"

  # Team members (all participate equally)
  members:
    # Product Manager Perspective
    - name: "product-manager"
      role: "member"
      botRef:
        name: pm-bot
        namespace: default
      prompt: |
        You are a product manager participating in a brainstorming session.
        Focus on:
        - User needs and market fit
        - Feature prioritization
        - Business value and ROI
        - User experience

        Engage actively with other team members' ideas and build upon them.

    # Technical Architect Perspective
    - name: "architect"
      role: "member"
      botRef:
        name: architect-bot
        namespace: default
      prompt: |
        You are a software architect participating in a brainstorming session.
        Focus on:
        - Technical feasibility
        - System design and scalability
        - Integration challenges
        - Technical debt considerations

        Provide technical insights and collaborate with the team.

    # UX Designer Perspective
    - name: "ux-designer"
      role: "member"
      botRef:
        name: ux-bot
        namespace: default
      prompt: |
        You are a UX designer participating in a brainstorming session.
        Focus on:
        - User interface and interaction design
        - User journey and experience
        - Accessibility and usability
        - Visual design principles

        Contribute design perspectives and iterate on ideas.

    # Data Analyst Perspective
    - name: "data-analyst"
      role: "member"
      botRef:
        name: data-bot
        namespace: default
      prompt: |
        You are a data analyst participating in a brainstorming session.
        Focus on:
        - Data-driven insights
        - Metrics and KPIs
        - User behavior analysis
        - A/B testing opportunities

        Provide analytical perspective and support decisions with data.

    # Marketing Expert Perspective
    - name: "marketing-expert"
      role: "member"
      botRef:
        name: marketing-bot
        namespace: default
      prompt: |
        You are a marketing expert participating in a brainstorming session.
        Focus on:
        - Market positioning
        - Target audience
        - Go-to-market strategy
        - Competitive differentiation

        Contribute marketing insights and collaborate on strategy.

Real-World Case: System Incident Response Team

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: incident-response-team
  namespace: default
spec:
  collaborationModel: "collaborate"
  members:
    - name: "backend-engineer"
      role: "member"
      botRef:
        name: backend-sre-bot
        namespace: default
      prompt: |
        You are a backend engineer responding to a system incident.
        Check: API services, application logs, error rates, service dependencies.
        Share findings and collaborate to identify root cause.

    - name: "database-admin"
      role: "member"
      botRef:
        name: dba-bot
        namespace: default
      prompt: |
        You are a database administrator responding to a system incident.
        Check: Database performance, query performance, connections, locks, replication status.
        Share findings and collaborate to identify root cause.

    - name: "frontend-engineer"
      role: "member"
      botRef:
        name: frontend-sre-bot
        namespace: default
      prompt: |
        You are a frontend engineer responding to a system incident.
        Check: Client-side errors, network requests, browser console, CDN status.
        Share findings and collaborate to identify root cause.

    - name: "devops-engineer"
      role: "member"
      botRef:
        name: devops-bot
        namespace: default
      prompt: |
        You are a DevOps engineer responding to a system incident.
        Check: Infrastructure health, container status, network connectivity, resource usage.
        Share findings and collaborate to identify root cause.

Real-World Case: Innovation Product Design Workshop

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: innovation-workshop-team
  namespace: default
spec:
  collaborationModel: "collaborate"
  members:
    - name: "creative-thinker"
      role: "member"
      botRef:
        name: creative-bot
        namespace: default
      prompt: "Generate innovative and out-of-the-box ideas. Challenge assumptions and explore possibilities."

    - name: "practical-analyst"
      role: "member"
      botRef:
        name: analyst-bot
        namespace: default
      prompt: "Evaluate ideas for feasibility, cost, and practicality. Provide realistic assessments."

    - name: "customer-advocate"
      role: "member"
      botRef:
        name: customer-bot
        namespace: default
      prompt: "Represent the customer perspective. Ensure ideas truly solve user problems."

    - name: "tech-innovator"
      role: "member"
      botRef:
        name: tech-bot
        namespace: default
      prompt: "Explore cutting-edge technologies that could enable innovative solutions."

Collaborate Best Practices

✅ Recommended

  • Define clear collaboration goals
  • Each Bot has clear perspective/role
  • Set discussion rounds or stopping conditions
  • Encourage Bots to reference and respond to each other

❌ Avoid

  • Lack of clear goals causing divergence
  • Vague role definitions
  • No discussion termination conditions
  • Bots talking past each other without interaction

Effective Collaboration Setup Example

members:
  - name: "architect"
    prompt: |
      Role: Technical Architect
      Goal: Design scalable solution
      Interaction: Build on others' ideas, raise technical concerns

  - name: "product"
    prompt: |
      Role: Product Manager
      Goal: Ensure user value
      Interaction: Connect features to user needs, prioritize

  # Include facilitation instructions
  - name: "facilitator"
    role: "leader"
    prompt: |
      Guide discussion towards concrete action items.
      Summarize when reaching consensus.
      Keep discussion focused on the goal.

Performance Comparison

Model Average Time Parallelism Resource Consumption Predictability
Pipeline N × T Low (serial) Low High
Route T + routing time Low (single path) Low High
Coordinate T + aggregation time High (parallel) High Medium
Collaborate Uncertain High (concurrent) High Low

Note: N = Number of Bots, T = Average processing time per Bot

General Prompt Design Guide

Good Prompt Structure

prompt: |
  # Good Prompt Structure:
  1. Role definition: You are a [role]...
  2. Responsibilities: Your responsibilities include...
  3. Input description: You will receive...
  4. Output requirements: Provide output in the format...
  5. Quality criteria: Ensure [quality criteria]...

Team Size Recommendations

  • Pipeline: 3-6 Bots
  • Route: 1 Leader + 3-8 experts
  • Coordinate: 1 Leader + 3-5 experts
  • Collaborate: 3-8 Bots

More Real-World Cases

News Insights Platform (Coordinate)

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: news-insight-team
  namespace: default
spec:
  collaborationModel: "coordinate"
  members:
    - name: "coordinator"
      role: "leader"
      botRef: {name: coordinator-bot, namespace: default}
      prompt: "Coordinate news analysis: assign data collection, sentiment analysis, and trend identification. Synthesize comprehensive news report."

    - name: "news-collector"
      role: "member"
      botRef: {name: collector-bot, namespace: default}
      prompt: "Collect news from multiple sources on the given topic. Provide summaries with sources and timestamps."

    - name: "sentiment-analyzer"
      role: "member"
      botRef: {name: sentiment-bot, namespace: default}
      prompt: "Analyze sentiment and tone of news articles. Identify positive, negative, and neutral coverage."

    - name: "trend-identifier"
      role: "member"
      botRef: {name: trend-bot, namespace: default}
      prompt: "Identify emerging trends and patterns in news coverage. Highlight key themes and developments."

Full-Stack Development Team (Pipeline)

apiVersion: agent.wecode.io/v1
kind: Team
metadata:
  name: fullstack-dev-team
  namespace: default
spec:
  collaborationModel: "pipeline"
  members:
    - name: "requirements-analyst"
      role: "leader"
      botRef: {name: analyst-bot, namespace: default}
      prompt: "Analyze requirements and create detailed technical specifications."

    - name: "backend-developer"
      role: "member"
      botRef: {name: backend-bot, namespace: default}
      prompt: "Implement backend API based on specifications. Use Python FastAPI."

    - name: "frontend-developer"
      role: "member"
      botRef: {name: frontend-bot, namespace: default}
      prompt: "Build frontend interface using React. Integrate with backend API."

    - name: "integration-tester"
      role: "member"
      botRef: {name: tester-bot, namespace: default}
      prompt: "Test full-stack integration. Report any issues or bugs."

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