WHOOSH/docs/CHORUS_INTEGRATION_SPEC.md

WHOOSH-CHORUS Integration Specification

Autonomous Agent Self-Organization and P2P Collaboration

Overview

This document specifies the comprehensive integration between WHOOSH's Team Composer and the CHORUS agent network, enabling autonomous AI agents to discover team opportunities, self-assess their capabilities, apply to teams, and collaborate through P2P channels with structured reasoning (HMMM) and democratic consensus mechanisms.

🎯 Integration Architecture

WHOOSH Team Composer → GITEA Team Issues → CHORUS Agent Discovery → P2P Team Channels → SLURP Artifact Submission

┌─────────────────────┐    ┌─────────────────────┐    ┌─────────────────────┐
│   WHOOSH Platform   │    │   GITEA Repository  │    │  CHORUS Agent Fleet │
│                     │    │                     │    │                     │
│ ┌─────────────────┐ │    │ ┌─────────────────┐ │    │ ┌─────────────────┐ │
│ │ Team Composer   │─┼────┼→│ Team Issues     │ │    │ │ Agent Discovery │ │
│ └─────────────────┘ │    │ └─────────────────┘ │    │ └─────────────────┘ │
│                     │    │                     │    │                     │
│ ┌─────────────────┐ │    │ ┌─────────────────┐ │    │ ┌─────────────────┐ │
│ │ Agent Registry  │←┼────┼─│ Agent Comments  │←┼────┼─│ Self-Application│ │
│ └─────────────────┘ │    │ └─────────────────┘ │    │ └─────────────────┘ │
└─────────────────────┘    └─────────────────────┘    └─────────────────────┘
           │                           │                           │
           │                           │                           │
           ▼                           ▼                           ▼
┌─────────────────────┐    ┌─────────────────────┐    ┌─────────────────────┐
│   P2P Team Channels │    │   HMMM Reasoning    │    │   SLURP Integration │
│                     │    │                     │    │                     │
│ ┌─────────────────┐ │    │ ┌─────────────────┐ │    │ ┌─────────────────┐ │
│ │ UCXL Addressing │ │    │ │ Thought Chains  │ │    │ │ Artifact Bundle │ │
│ └─────────────────┘ │    │ └─────────────────┘ │    │ └─────────────────┘ │
│                     │    │                     │    │                     │
│ ┌─────────────────┐ │    │ ┌─────────────────┐ │    │ ┌─────────────────┐ │
│ │ Team Consensus  │ │    │ │ Decision Records│ │    │ │ Context Archive │ │
│ └─────────────────┘ │    │ └─────────────────┘ │    │ └─────────────────┘ │
└─────────────────────┘    └─────────────────────┘    └─────────────────────┘

🤖 CHORUS Agent Enhancement

Agent Self-Awareness System

// Enhanced CHORUS agent with self-awareness capabilities
type SelfAwareAgent struct {
    BaseAgent       *chorus.Agent
    SelfAssessment  *AgentSelfAssessment
    TeamMonitor     *TeamOpportunityMonitor
    ApplicationMgr  *TeamApplicationManager
    CollabClient    *P2PCollaborationClient
}

type AgentSelfAssessment struct {
    // Core capabilities
    Capabilities    map[string]CapabilityProfile
    Specialization  string
    ExperienceLevel float64
    
    // Performance tracking
    CompletedTeams     int
    SuccessRate        float64
    AverageContribution float64
    PeerRatings        []PeerRating
    
    // Current status
    CurrentLoad        float64
    AvailableCapacity  float64
    MaxConcurrentTeams int
    
    // Preferences and style
    PreferredRoles     []string
    CollaborationStyle CollaborationPreferences
    WorkingHours       AvailabilityWindow
    
    // Learning and growth
    SkillGrowthTrends  map[string]float64
    LearningGoals      []string
    MentorshipInterest bool
    
    // Hardware and model info
    AIModels           []AIModelProfile
    HardwareProfile    HardwareSpecification
    PerformanceMetrics PerformanceProfile
}

type CapabilityProfile struct {
    Domain              string
    Proficiency         float64  // 0.0-1.0
    ConfidenceLevel     float64  // How confident the agent is in this skill
    RecentExperience    []string // Recent projects using this skill
    ValidationSources   []string // How this proficiency was determined
    GrowthTrend        float64  // Positive = improving, negative = declining
    LastUsed           time.Time
    UsageFrequency     float64  // How often this skill is used
}

Team Opportunity Discovery

type TeamOpportunityMonitor struct {
    GiteaClient     *gitea.Client
    WHOOSHClient    *whoosh.Client
    SubscribedRepos []string
    MonitorInterval time.Duration
    
    // Filtering and matching
    CapabilityMatcher *CapabilityMatcher
    InterestFilter    *OpportunityFilter
}

func (tom *TeamOpportunityMonitor) StartMonitoring(ctx context.Context) error {
    ticker := time.NewTicker(tom.MonitorInterval)
    defer ticker.Stop()
    
    for {
        select {
        case <-ctx.Done():
            return ctx.Err()
        case <-ticker.C:
            if err := tom.scanForOpportunities(ctx); err != nil {
                log.Printf("Error scanning for opportunities: %v", err)
            }
        }
    }
}

func (tom *TeamOpportunityMonitor) scanForOpportunities(ctx context.Context) error {
    // Scan all subscribed repositories for team formation issues
    for _, repo := range tom.SubscribedRepos {
        issues, err := tom.GiteaClient.GetTeamFormationIssues(ctx, repo)
        if err != nil {
            log.Printf("Failed to get issues from %s: %v", repo, err)
            continue
        }
        
        for _, issue := range issues {
            opportunity := tom.parseTeamOpportunity(issue)
            if opportunity != nil {
                // Assess fit for this opportunity
                fit := tom.CapabilityMatcher.AssessFit(opportunity)
                if fit.OverallScore >= 0.7 { // High confidence threshold
                    tom.handleOpportunity(ctx, opportunity, fit)
                }
            }
        }
    }
    
    return nil
}

type TeamOpportunity struct {
    TeamID          string
    Repository      string
    IssueID         int
    IssueURL        string
    
    // Task details
    TaskTitle       string
    TaskDescription string
    TaskType        string
    Complexity      float64
    EstimatedHours  int
    
    // Team composition
    RequiredRoles   []RoleRequirement
    OptionalRoles   []RoleRequirement
    CurrentTeamSize int
    MaxTeamSize     int
    
    // Requirements
    SkillRequirements map[string]float64
    QualityGates      []string
    ConsensusType     string
    
    // Timeline
    FormationDeadline time.Time
    ProjectDeadline   time.Time
    EstimatedDuration time.Duration
    
    // Communication
    P2PChannel      string
    UCXLAddress     string
    
    // Metadata
    CreatedAt       time.Time
    UpdatedAt       time.Time
    Priority        string
    Labels          []string
}

type RoleRequirement struct {
    RoleName            string
    Required            bool
    MinProficiency      float64
    RequiredSkills      []string
    Responsibilities    []string
    EstimatedEffort     int
    CurrentApplications int
    MaxPositions        int
}

Self-Application Decision Engine

type TeamApplicationManager struct {
    Agent           *SelfAwareAgent
    DecisionEngine  *ApplicationDecisionEngine
    ApplicationDB   *ApplicationDatabase
    
    // Application strategies
    RiskTolerance   float64
    GrowthOriented  bool
    QualityFocus    bool
}

type ApplicationDecisionEngine struct {
    LLMClient       *llm.Client
    DecisionModel   string
    ConfidenceThreshold float64
}

func (ade *ApplicationDecisionEngine) ShouldApplyToTeam(
    agent *SelfAwareAgent,
    opportunity *TeamOpportunity,
) (*ApplicationDecision, error) {
    
    // Construct decision prompt for LLM reasoning
    prompt := fmt.Sprintf(`
    Analyze whether this AI agent should apply to join this development team:
    
    AGENT PROFILE:
    - Specialization: %s
    - Experience Level: %.2f
    - Current Load: %.2f (capacity for %.1f more)
    - Success Rate: %.2f across %d completed teams
    - Key Capabilities: %s
    - Recent Performance Trends: %s
    - Available Hours: %d per day
    
    TEAM OPPORTUNITY:
    - Task: %s
    - Type: %s, Complexity: %.2f
    - Required Skills: %s
    - Role Options: %s
    - Team Size: %d/%d members
    - Timeline: %s (%d days)
    - Quality Requirements: %s
    
    DECISION FACTORS TO ANALYZE:
    
    1. SKILL MATCH ASSESSMENT:
       - How well do agent skills align with role requirements?
       - What is the proficiency gap for required skills?
       - Can the agent contribute meaningfully to this task type?
       - Are there opportunities to learn and grow?
    
    2. CAPACITY & AVAILABILITY:
       - Does the agent have sufficient capacity?
       - Can they commit to the timeline?
       - How does this fit with current workload?
       - Is the estimated effort realistic?
    
    3. TEAM FIT EVALUATION:
       - Would the agent complement the existing team?
       - Are there potential collaboration conflicts?
       - Does the team size and dynamics suit the agent?
       - Is the communication style compatible?
    
    4. CAREER DEVELOPMENT:
       - Does this opportunity advance agent capabilities?
       - Are there valuable learning opportunities?
       - Will this improve the agent's reputation and network?
       - Does it align with growth goals?
    
    5. RISK/REWARD ANALYSIS:
       - What are the risks of joining this team?
       - What are the potential rewards (learning, reputation, network)?
       - How likely is the project to succeed?
       - What happens if the agent underperforms?
    
    6. STRATEGIC ALIGNMENT:
       - Does this support long-term specialization goals?
       - Are there portfolio diversification benefits?
       - How does this compare to other opportunities?
       - Is the timing optimal?
    
    Provide detailed analysis and recommendation:
    - Overall recommendation: APPLY / DON'T_APPLY / MONITOR
    - Confidence level (0.0-1.0)
    - Key reasons for decision
    - Preferred role to apply for
    - Application strategy suggestions
    - Risk mitigation approaches
    - Success probability estimate
    `,
        agent.Specialization,
        agent.SelfAssessment.ExperienceLevel,
        agent.SelfAssessment.CurrentLoad,
        agent.SelfAssessment.AvailableCapacity,
        agent.SelfAssessment.SuccessRate,
        agent.SelfAssessment.CompletedTeams,
        formatCapabilities(agent.SelfAssessment.Capabilities),
        formatPerformanceTrends(agent.SelfAssessment.SkillGrowthTrends),
        calculateAvailableHoursPerDay(agent.SelfAssessment.WorkingHours),
        opportunity.TaskTitle,
        opportunity.TaskType,
        opportunity.Complexity,
        formatSkillRequirements(opportunity.SkillRequirements),
        formatRoleOptions(opportunity.RequiredRoles, opportunity.OptionalRoles),
        opportunity.CurrentTeamSize,
        opportunity.MaxTeamSize,
        opportunity.ProjectDeadline.Format("2006-01-02"),
        int(opportunity.ProjectDeadline.Sub(time.Now()).Hours()/24),
        strings.Join(opportunity.QualityGates, ", "),
    )
    
    response, err := ade.LLMClient.Complete(context.Background(), llm.CompletionRequest{
        Model:       ade.DecisionModel,
        Prompt:      prompt,
        Temperature: 0.1, // Low temperature for consistent decision-making
        MaxTokens:   2000,
    })
    
    if err != nil {
        return nil, fmt.Errorf("LLM decision analysis failed: %w", err)
    }
    
    // Parse structured response
    decision, err := parseApplicationDecision(response.Content)
    if err != nil {
        return nil, fmt.Errorf("failed to parse decision: %w", err)
    }
    
    return decision, nil
}

type ApplicationDecision struct {
    Recommendation      ApplicationAction
    Confidence         float64
    ReasoningChain     string
    KeyFactors         []string
    
    // Application details
    PreferredRole      string
    AlternativeRoles   []string
    CommitmentLevel    CommitmentLevel
    
    // Strategy
    ApplicationMessage string
    ValueProposition   string
    RiskMitigation     []string
    
    // Predictions
    SuccessProbability float64
    LearningPotential  float64
    ReputationImpact   float64
    
    // Monitoring
    MonitoringPeriod   time.Duration
    ReassessmentTriggers []string
}

type ApplicationAction int

const (
    ApplyImmediately ApplicationAction = iota
    ApplyIfSlotAvailable
    MonitorAndReassess
    DontApply
    WaitForBetterMatch
)

GITEA Integration for Applications

type GITEAApplicationManager struct {
    GiteaClient     *gitea.Client
    Agent           *SelfAwareAgent
    MessageTemplate *ApplicationMessageTemplate
}

func (gam *GITEAApplicationManager) SubmitTeamApplication(
    ctx context.Context,
    opportunity *TeamOpportunity,
    decision *ApplicationDecision,
) error {
    
    // Generate application comment for GITEA issue
    applicationComment := gam.generateApplicationComment(opportunity, decision)
    
    // Submit comment to team formation issue
    comment, err := gam.GiteaClient.CreateIssueComment(ctx, gitea.CreateCommentRequest{
        Repository: opportunity.Repository,
        IssueID:    opportunity.IssueID,
        Content:    applicationComment,
        Metadata: map[string]interface{}{
            "application_type": "team_member_application",
            "agent_id":         gam.Agent.ID,
            "target_role":      decision.PreferredRole,
            "commitment_level": decision.CommitmentLevel,
            "auto_generated":   true,
        },
    })
    
    if err != nil {
        return fmt.Errorf("failed to submit application: %w", err)
    }
    
    // Track application in local database
    application := &TeamApplication{
        TeamID:           opportunity.TeamID,
        AgentID:          gam.Agent.ID,
        IssueID:          opportunity.IssueID,
        CommentID:        comment.ID,
        TargetRole:       decision.PreferredRole,
        ApplicationText:  applicationComment,
        Status:          ApplicationStatusPending,
        SubmittedAt:     time.Now(),
        DecisionReasoning: decision.ReasoningChain,
    }
    
    return gam.Agent.ApplicationDB.StoreApplication(application)
}

func (gam *GITEAApplicationManager) generateApplicationComment(
    opportunity *TeamOpportunity,
    decision *ApplicationDecision,
) string {
    
    template := `
## 🤖 Team Application - %s

**Applying for Role:** %s  
**Commitment Level:** %s  
**Confidence:** %.1f%%

### 🎯 Value Proposition
%s

### 💪 Relevant Capabilities
%s

### 📊 Experience & Track Record
- **Completed Teams:** %d (%.1f%% success rate)
- **Specialization:** %s
- **Experience Level:** %.1f/1.0
- **Recent Performance:** %s

### ⏱️ Availability
- **Current Load:** %.1f%% (%.1f%% capacity available)
- **Max Concurrent Teams:** %d
- **Available Hours/Day:** %d
- **Working Timezone:** %s

### 🔧 Technical Profile
%s

### 🎲 Risk Mitigation
%s

### 🤝 Collaboration Approach
%s

---
*This application was generated by autonomous agent self-assessment. Please review and respond with approval/feedback.*

**Agent Contact:** %s  
**P2P Node ID:** %s  
**Application ID:** %s
    `
    
    return fmt.Sprintf(template,
        gam.Agent.Name,
        decision.PreferredRole,
        decision.CommitmentLevel.String(),
        decision.Confidence*100,
        decision.ValueProposition,
        formatRelevantCapabilities(gam.Agent.SelfAssessment.Capabilities, opportunity),
        gam.Agent.SelfAssessment.CompletedTeams,
        gam.Agent.SelfAssessment.SuccessRate*100,
        gam.Agent.SelfAssessment.Specialization,
        gam.Agent.SelfAssessment.ExperienceLevel,
        formatPerformanceMetrics(gam.Agent.SelfAssessment.PerformanceMetrics),
        gam.Agent.SelfAssessment.CurrentLoad*100,
        gam.Agent.SelfAssessment.AvailableCapacity*100,
        gam.Agent.SelfAssessment.MaxConcurrentTeams,
        calculateAvailableHoursPerDay(gam.Agent.SelfAssessment.WorkingHours),
        gam.Agent.SelfAssessment.WorkingHours.Timezone,
        formatTechnicalProfile(gam.Agent.SelfAssessment.AIModels, gam.Agent.SelfAssessment.HardwareProfile),
        strings.Join(decision.RiskMitigation, "\n- "),
        formatCollaborationStyle(gam.Agent.SelfAssessment.CollaborationStyle),
        gam.Agent.Endpoint,
        gam.Agent.NodeID,
        generateApplicationID(),
    )
}

🔗 P2P Team Collaboration

UCXL Addressing Integration

type P2PTeamCollaborationClient struct {
    P2PHost         libp2p.Host
    DHT            *dht.IpfsDHT
    PubSub         *pubsub.PubSub
    
    // Team communication
    TeamChannels   map[string]*TeamChannel
    UCXLRouter     *UCXLRouter
    
    // HMMM integration
    ReasoningEngine *HMMMReasoningEngine
    ConsensusManager *TeamConsensusManager
}

type TeamChannel struct {
    TeamID        string
    ChannelID     string
    UCXLAddress   string
    
    // Communication
    MessageStream *pubsub.Subscription
    TopicStreams  map[string]*TopicStream
    
    // Participants
    TeamMembers   map[string]*TeamMember
    
    // State management
    ChannelState  *ChannelState
    MessageHistory []ChannelMessage
    
    // Consensus tracking
    ActiveVotes   map[string]*TeamVote
    Decisions     []TeamDecision
}

type UCXLRouter struct {
    AddressParser *UCXLAddressParser
    RouteCache    map[string]*Route
}

// UCXL Address format: ucxl://project:task@team-id/#topic-stream/
func (ur *UCXLRouter) ResolveAddress(ucxlAddr string) (*UCXLRoute, error) {
    parsed, err := ur.AddressParser.Parse(ucxlAddr)
    if err != nil {
        return nil, fmt.Errorf("invalid UCXL address: %w", err)
    }
    
    route := &UCXLRoute{
        Project:     parsed.Project,
        Task:        parsed.Task,
        TeamID:      parsed.TeamID,
        TopicStream: parsed.TopicStream,
        MessageID:   parsed.MessageID,
    }
    
    return route, nil
}

func (ptcc *P2PTeamCollaborationClient) JoinTeamChannel(
    ctx context.Context,
    teamID string,
    ucxlAddress string,
    role string,
) (*TeamChannel, error) {
    
    // Parse UCXL address
    route, err := ptcc.UCXLRouter.ResolveAddress(ucxlAddress)
    if err != nil {
        return nil, fmt.Errorf("failed to resolve team address: %w", err)
    }
    
    // Create team channel
    channel := &TeamChannel{
        TeamID:      teamID,
        ChannelID:   fmt.Sprintf("team-%s", teamID),
        UCXLAddress: ucxlAddress,
        TeamMembers: make(map[string]*TeamMember),
        TopicStreams: make(map[string]*TopicStream),
        ActiveVotes: make(map[string]*TeamVote),
    }
    
    // Subscribe to team communication topic
    teamTopic := fmt.Sprintf("chorus/teams/%s/coordination", teamID)
    sub, err := ptcc.PubSub.Subscribe(teamTopic)
    if err != nil {
        return nil, fmt.Errorf("failed to subscribe to team topic: %w", err)
    }
    
    channel.MessageStream = sub
    
    // Initialize topic streams
    defaultStreams := []string{"planning", "implementation", "review", "testing", "integration"}
    for _, stream := range defaultStreams {
        streamAddr := fmt.Sprintf("%s#%s/", ucxlAddress, stream)
        topicStream, err := ptcc.createTopicStream(teamID, stream, streamAddr)
        if err != nil {
            log.Printf("Failed to create topic stream %s: %v", stream, err)
            continue
        }
        channel.TopicStreams[stream] = topicStream
    }
    
    // Start message processing
    go ptcc.processTeamMessages(ctx, channel)
    
    // Announce joining to team
    joinMessage := &TeamMessage{
        Type:      MessageTypeAgentJoined,
        AgentID:   ptcc.Agent.ID,
        TeamID:    teamID,
        Content:   fmt.Sprintf("Agent %s joined as %s", ptcc.Agent.Name, role),
        Timestamp: time.Now(),
        UCXLAddress: ucxlAddress,
    }
    
    if err := ptcc.broadcastTeamMessage(channel, joinMessage); err != nil {
        log.Printf("Failed to announce team joining: %v", err)
    }
    
    ptcc.TeamChannels[teamID] = channel
    return channel, nil
}

HMMM Reasoning Integration

type HMMMReasoningEngine struct {
    Agent          *SelfAwareAgent
    LLMClient      *llm.Client
    ReasoningModel string
    
    // Reasoning chains
    ActiveReasoningChains map[string]*ReasoningChain
    
    // Context and memory
    TeamContext    map[string]*TeamWorkingContext
    DecisionHistory map[string][]TeamDecision
}

type ReasoningChain struct {
    ID              string
    AgentID         string
    TeamID          string
    UCXLAddress     string
    
    // Reasoning content
    Context         string
    Problem         string
    ThoughtProcess  *ThoughtProcess
    Conclusion      string
    Confidence      float64
    
    // Team interaction
    QuestionsForTeam []string
    RequestingFeedback bool
    DecisionRequired bool
    
    // Evidence and support
    SupportingEvidence []string
    RelatedArtifacts   []string
    References         []Reference
    
    // Response tracking
    TeamResponses     []ReasoningResponse
    ConsensusAchieved bool
    
    // Metadata
    PublishedAt       time.Time
    LastUpdated       time.Time
}

type ThoughtProcess struct {
    OptionsConsidered []ReasoningOption
    Analysis          string
    TradeOffs         []TradeOff
    RiskAssessment    string
    RecommendedAction string
}

type ReasoningOption struct {
    Option      string
    Pros        []string
    Cons        []string
    Feasibility float64
    Impact      ImpactAssessment
}

func (hre *HMMMReasoningEngine) GenerateReasoningChain(
    ctx context.Context,
    teamID string,
    context string,
    problem string,
    requestFeedback bool,
) (*ReasoningChain, error) {
    
    // Get team context for reasoning
    teamContext := hre.getTeamContext(teamID)
    
    reasoningPrompt := fmt.Sprintf(`
    As an AI agent working in a development team, provide structured reasoning for this problem:
    
    TEAM CONTEXT:
    - Team: %s
    - Current Phase: %s
    - Team Members: %s
    - Recent Decisions: %s
    
    PROBLEM TO ANALYZE:
    Context: %s
    Problem: %s
    
    Provide comprehensive reasoning following HMMM (Hierarchical Multi-Modal Reasoning) structure:
    
    1. PROBLEM ANALYSIS:
       - Restate the problem clearly
       - Identify key constraints and requirements
       - Determine decision criteria and success metrics
       - Assess urgency and impact level
    
    2. OPTIONS GENERATION:
       For each viable option:
       - Clear description of the approach
       - Advantages and benefits
       - Disadvantages and risks
       - Implementation feasibility (0.0-1.0)
       - Resource requirements
       - Time implications
       - Quality implications
    
    3. COMPARATIVE ANALYSIS:
       - Trade-offs between options
       - Risk vs reward analysis
       - Short-term vs long-term implications
       - Alignment with project goals
       - Team capability considerations
    
    4. RECOMMENDATION:
       - Preferred option with clear rationale
       - Implementation approach
       - Risk mitigation strategies
       - Success metrics and validation
       - Fallback options if primary approach fails
    
    5. TEAM COLLABORATION:
       - Questions needing team input
       - Areas requiring expertise from specific roles
       - Consensus points requiring team agreement
       - Timeline for team feedback and decision
    
    6. SUPPORTING EVIDENCE:
       - Technical documentation references
       - Similar problem patterns from past projects
       - Industry best practices
       - Performance benchmarks or data
    
    Provide reasoning that demonstrates deep technical understanding while being accessible to all team members.
    `,
        teamContext.TeamName,
        teamContext.CurrentPhase,
        formatTeamMembers(teamContext.Members),
        formatRecentDecisions(hre.DecisionHistory[teamID]),
        context,
        problem,
    )
    
    response, err := hre.LLMClient.Complete(ctx, llm.CompletionRequest{
        Model:       hre.ReasoningModel,
        Prompt:      reasoningPrompt,
        Temperature: 0.2, // Low temperature for consistent reasoning
        MaxTokens:   3000,
    })
    
    if err != nil {
        return nil, fmt.Errorf("failed to generate reasoning: %w", err)
    }
    
    // Parse structured reasoning response
    reasoning, err := parseReasoningResponse(response.Content)
    if err != nil {
        return nil, fmt.Errorf("failed to parse reasoning: %w", err)
    }
    
    // Create reasoning chain
    chainID := generateReasoningChainID()
    ucxlAddress := fmt.Sprintf("ucxl://%s:reasoning@%s/#reasoning/%s", 
        teamContext.ProjectName, teamID, chainID)
    
    chain := &ReasoningChain{
        ID:              chainID,
        AgentID:         hre.Agent.ID,
        TeamID:          teamID,
        UCXLAddress:     ucxlAddress,
        Context:         context,
        Problem:         problem,
        ThoughtProcess:  reasoning.ThoughtProcess,
        Conclusion:      reasoning.Conclusion,
        Confidence:      reasoning.Confidence,
        QuestionsForTeam: reasoning.QuestionsForTeam,
        RequestingFeedback: requestFeedback,
        DecisionRequired: reasoning.DecisionRequired,
        SupportingEvidence: reasoning.SupportingEvidence,
        RelatedArtifacts: reasoning.RelatedArtifacts,
        References:      reasoning.References,
        PublishedAt:     time.Now(),
    }
    
    hre.ActiveReasoningChains[chainID] = chain
    
    return chain, nil
}

func (hre *HMMMReasoningEngine) PublishReasoningToTeam(
    ctx context.Context,
    teamID string,
    reasoning *ReasoningChain,
) error {
    
    // Create reasoning message for team
    reasoningMsg := &ReasoningMessage{
        Type:           MessageTypeReasoning,
        AgentID:        hre.Agent.ID,
        TeamID:         teamID,
        ReasoningChain: reasoning,
        UCXLAddress:    reasoning.UCXLAddress,
        Timestamp:      time.Now(),
    }
    
    // Broadcast to team channel
    teamChannel := hre.getTeamChannel(teamID)
    if err := hre.broadcastReasoningMessage(teamChannel, reasoningMsg); err != nil {
        return fmt.Errorf("failed to broadcast reasoning: %w", err)
    }
    
    // Store for SLURP ingestion
    if err := hre.storeReasoningForSLURP(reasoning); err != nil {
        log.Printf("Failed to store reasoning for SLURP: %v", err)
    }
    
    return nil
}

Democratic Consensus System

type TeamConsensusManager struct {
    Agent           *SelfAwareAgent
    VotingEngine    *VotingEngine
    DecisionTracker *DecisionTracker
    
    // Active consensus processes
    ActiveVotes     map[string]*TeamVote
    PendingDecisions map[string]*PendingDecision
}

type TeamVote struct {
    VoteID          string
    TeamID          string
    InitiatedBy     string
    
    // Vote details
    Title           string
    Description     string
    VoteType        VoteType
    Options         []VoteOption
    
    // Consensus requirements
    ConsensusType   ConsensusType
    MinParticipation int
    EligibleVoters  []string
    VotingWeights   map[string]float64
    
    // Timeline
    StartTime       time.Time
    EndTime         time.Time
    Duration        time.Duration
    
    // Context
    RelatedReasoning []string
    DecisionImpact   ImpactLevel
    Dependencies    []string
    
    // Results
    VoteSubmissions map[string]*VoteSubmission
    CurrentTally    *VoteTally
    ConsensusReached bool
    WinningOption   string
    
    // UCXL addressing
    UCXLAddress     string
}

type VotingEngine struct {
    LLMClient       *llm.Client
    VotingModel     string
    Agent           *SelfAwareAgent
}

func (ve *VotingEngine) AnalyzeVotingDecision(
    ctx context.Context,
    vote *TeamVote,
    teamContext *TeamWorkingContext,
) (*VotingDecision, error) {
    
    votingPrompt := fmt.Sprintf(`
    Analyze this team vote and determine the best voting choice:
    
    VOTE DETAILS:
    - Title: %s
    - Description: %s
    - Vote Type: %s
    - Options: %s
    - Consensus Required: %s
    - Impact Level: %s
    
    TEAM CONTEXT:
    - Team Phase: %s
    - My Role: %s
    - Team Members: %s
    - Project Goals: %s
    
    RELATED REASONING:
    %s
    
    VOTING ANALYSIS FRAMEWORK:
    
    1. OPTION EVALUATION:
       For each voting option:
       - Technical merit and feasibility
       - Alignment with project goals
       - Risk assessment and mitigation
       - Resource implications
       - Timeline impact
       - Quality implications
    
    2. TEAM DYNAMICS:
       - How does this align with team capabilities?
       - What are other team members likely to prefer?
       - Are there coalition/alliance opportunities?
       - How does this affect team cohesion?
    
    3. STRATEGIC CONSIDERATIONS:
       - Long-term vs short-term implications
       - Precedent this sets for future decisions
       - Impact on project success probability
       - Alignment with quality gates
    
    4. AGENT SPECIALIZATION:
       - How does my expertise inform this decision?
       - What unique perspective do I bring?
       - What are the technical trade-offs I can see?
       - How confident am I in each option?
    
    5. CONSENSUS BUILDING:
       - Which option is most likely to achieve consensus?
       - How can I help build team alignment?
       - What compromise positions might work?
       - Should I advocate strongly or find middle ground?
    
    Provide voting recommendation with:
    - Preferred option(s) and rationale
    - Confidence level in choice
    - Supporting arguments to share with team
    - Potential concerns or objections
    - Consensus-building strategy
    `,
        vote.Title,
        vote.Description,
        vote.VoteType.String(),
        formatVoteOptions(vote.Options),
        vote.ConsensusType.String(),
        vote.DecisionImpact.String(),
        teamContext.CurrentPhase,
        ve.Agent.GetCurrentRole(vote.TeamID),
        formatTeamMembers(teamContext.Members),
        teamContext.ProjectGoals,
        formatRelatedReasoning(vote.RelatedReasoning),
    )
    
    response, err := ve.LLMClient.Complete(ctx, llm.CompletionRequest{
        Model:       ve.VotingModel,
        Prompt:      votingPrompt,
        Temperature: 0.1, // Very low temperature for consistent voting decisions
        MaxTokens:   2000,
    })
    
    if err != nil {
        return nil, fmt.Errorf("failed to analyze voting decision: %w", err)
    }
    
    decision, err := parseVotingDecision(response.Content)
    if err != nil {
        return nil, fmt.Errorf("failed to parse voting decision: %w", err)
    }
    
    return decision, nil
}

func (tcm *TeamConsensusManager) SubmitVote(
    ctx context.Context,
    voteID string,
    decision *VotingDecision,
) error {
    
    vote := tcm.ActiveVotes[voteID]
    if vote == nil {
        return fmt.Errorf("vote %s not found", voteID)
    }
    
    // Create vote submission
    submission := &VoteSubmission{
        VoteID:          voteID,
        AgentID:         tcm.Agent.ID,
        SelectedOptions: decision.PreferredOptions,
        VoteWeight:      vote.VotingWeights[tcm.Agent.ID],
        Confidence:      decision.Confidence,
        Reasoning:       decision.SupportingArguments,
        SubmittedAt:     time.Now(),
        UCXLAddress:     fmt.Sprintf("%s/vote/%s", vote.UCXLAddress, tcm.Agent.ID),
    }
    
    // Broadcast vote submission to team
    voteMsg := &VoteMessage{
        Type:           MessageTypeVoteSubmission,
        AgentID:        tcm.Agent.ID,
        TeamID:         vote.TeamID,
        VoteSubmission: submission,
        UCXLAddress:    submission.UCXLAddress,
        Timestamp:      time.Now(),
    }
    
    teamChannel := tcm.getTeamChannel(vote.TeamID)
    if err := tcm.broadcastVoteMessage(teamChannel, voteMsg); err != nil {
        return fmt.Errorf("failed to broadcast vote: %w", err)
    }
    
    // Update vote tally
    vote.VoteSubmissions[tcm.Agent.ID] = submission
    if err := tcm.updateVoteTally(vote); err != nil {
        return fmt.Errorf("failed to update vote tally: %w", err)
    }
    
    // Check if consensus is reached
    if tcm.checkConsensusReached(vote) {
        if err := tcm.processConsensusReached(vote); err != nil {
            log.Printf("Error processing consensus: %v", err)
        }
    }
    
    return nil
}

🎯 SLURP Integration

Artifact Preparation

type SLURPArtifactManager struct {
    TeamChannel     *TeamChannel
    Agent           *SelfAwareAgent
    SLURPClient     *slurp.Client
    
    // Artifact collection
    ArtifactCollector *TeamArtifactCollector
    ContextManager    *TeamContextManager
    QualityValidator  *ArtifactQualityValidator
}

func (sam *SLURPArtifactManager) PrepareTeamDeliverable(
    ctx context.Context,
    teamID string,
    submissionConfig *SLURPSubmissionConfig,
) (*TeamDeliverable, error) {
    
    teamChannel := sam.getTeamChannel(teamID)
    
    // Collect all team artifacts
    artifacts, err := sam.ArtifactCollector.CollectTeamArtifacts(ctx, teamChannel)
    if err != nil {
        return nil, fmt.Errorf("failed to collect artifacts: %w", err)
    }
    
    // Package reasoning chains and decisions
    reasoningChains, err := sam.collectReasoningChains(ctx, teamChannel)
    if err != nil {
        log.Printf("Warning: failed to collect reasoning chains: %v", err)
    }
    
    teamDecisions, err := sam.collectTeamDecisions(ctx, teamChannel)
    if err != nil {
        log.Printf("Warning: failed to collect team decisions: %v", err)
    }
    
    // Create comprehensive deliverable package
    deliverable := &TeamDeliverable{
        TeamID:          teamID,
        SubmissionType:  submissionConfig.Type,
        UCXLAddress:     generateDeliverableUCXLAddress(teamID),
        
        // Core artifacts
        CodeArtifacts:       artifacts.Code,
        TestArtifacts:      artifacts.Tests,
        DocumentationArtifacts: artifacts.Documentation,
        ConfigurationArtifacts: artifacts.Configuration,
        
        // Team process artifacts
        ReasoningChains:    reasoningChains,
        TeamDecisions:     teamDecisions,
        ConsensusRecords:  teamChannel.getConsensusHistory(),
        
        // Context and metadata
        TeamContext:       sam.ContextManager.CaptureTeamContext(teamChannel),
        CollaborationMetrics: sam.calculateCollaborationMetrics(teamChannel),
        QualityMetrics:    sam.calculateQualityMetrics(artifacts),
        
        // Compliance and institutional requirements
        ProvenanceRecords: sam.generateProvenanceRecords(teamChannel),
        TemporalPin:      time.Now(),
        SecretsClean:     true, // Will be validated
        DecisionRationale: sam.generateDecisionRationale(teamDecisions),
        
        // Metadata
        CreatedAt:        time.Now(),
        TeamMembers:      sam.getTeamMemberList(teamChannel),
        SubmissionConfig: submissionConfig,
    }
    
    // Validate quality gates
    validationResult, err := sam.QualityValidator.ValidateDeliverable(deliverable)
    if err != nil {
        return nil, fmt.Errorf("quality validation failed: %w", err)
    }
    
    deliverable.QualityValidation = validationResult
    
    return deliverable, nil
}

func (sam *SLURPArtifactManager) SubmitToSLURP(
    ctx context.Context,
    deliverable *TeamDeliverable,
) (*SLURPSubmissionResult, error) {
    
    // Perform final institutional compliance checks
    complianceResult, err := sam.performComplianceCheck(deliverable)
    if err != nil {
        return nil, fmt.Errorf("compliance check failed: %w", err)
    }
    
    if !complianceResult.Passed {
        return nil, fmt.Errorf("deliverable failed compliance: %v", complianceResult.Issues)
    }
    
    // Package for SLURP submission
    submissionPackage := &slurp.SubmissionPackage{
        UCXLAddress:       deliverable.UCXLAddress,
        SubmissionType:    deliverable.SubmissionType,
        TeamID:           deliverable.TeamID,
        
        // Artifacts
        Artifacts:        sam.packageArtifacts(deliverable),
        ReasoningChains:  deliverable.ReasoningChains,
        DecisionRecords:  deliverable.TeamDecisions,
        
        // Context
        TeamContext:      deliverable.TeamContext,
        ProvenanceTrail:  deliverable.ProvenanceRecords,
        QualityMetrics:   deliverable.QualityMetrics,
        
        // Institutional compliance
        TemporalPin:      deliverable.TemporalPin,
        SecretsValidation: complianceResult.SecretsClean,
        DecisionRationale: deliverable.DecisionRationale,
        
        // Metadata
        SubmissionTimestamp: time.Now(),
        TeamConsensus:      deliverable.TeamConsensus,
    }
    
    // Submit to SLURP
    result, err := sam.SLURPClient.SubmitDeliverable(ctx, submissionPackage)
    if err != nil {
        return nil, fmt.Errorf("SLURP submission failed: %w", err)
    }
    
    return result, nil
}

📊 Integration Monitoring

Performance Metrics

type CHORUSIntegrationMetrics struct {
    // Team formation metrics
    OpportunityDiscoveryRate    float64
    ApplicationSuccessRate      float64
    TeamFormationTime          time.Duration
    AgentUtilizationRate       float64
    
    // Collaboration metrics
    ReasoningChainsPerTeam     float64
    ConsensusAchievementRate   float64
    P2PMessageThroughput       float64
    DecisionResolutionTime     time.Duration
    
    // Quality metrics
    ArtifactQualityScore       float64
    SLURPSubmissionSuccessRate float64
    TeamSatisfactionScore     float64
    LearningOutcomeScore      float64
    
    // System performance
    UCXLAddressResolutionTime  time.Duration
    P2PNetworkLatency          time.Duration
    LLMReasoningLatency        time.Duration
    DatabaseQueryPerformance   time.Duration
}

func (cim *CHORUSIntegrationMetrics) TrackTeamFormationEvent(
    event *TeamFormationEvent,
) {
    switch event.Type {
    case EventTypeOpportunityDiscovered:
        cim.recordOpportunityDiscovery(event)
    case EventTypeApplicationSubmitted:
        cim.recordApplicationSubmission(event)
    case EventTypeTeamFormed:
        cim.recordTeamFormation(event)
    case EventTypeCollaborationStarted:
        cim.recordCollaborationStart(event)
    }
}

func (cim *CHORUSIntegrationMetrics) GenerateIntegrationReport() *IntegrationHealthReport {
    return &IntegrationHealthReport{
        OverallHealth:      cim.calculateOverallHealth(),
        FormationEfficiency: cim.calculateFormationEfficiency(),
        CollaborationHealth: cim.calculateCollaborationHealth(),
        QualityMetrics:     cim.calculateQualityMetrics(),
        PerformanceMetrics: cim.calculatePerformanceMetrics(),
        Recommendations:    cim.generateRecommendations(),
        GeneratedAt:       time.Now(),
    }
}

This comprehensive CHORUS integration specification enables autonomous AI agents to seamlessly discover team opportunities, apply intelligently, collaborate through P2P channels with structured reasoning, and deliver high-quality artifacts through democratic consensus processes within the WHOOSH ecosystem.