# WHOOSH-CHORUS Integration Specification ## Autonomous Agent Self-Organization and P2P Collaboration Addendum (Terminology, Topics, MVP) - Terminology: all former β€œBZZZ” references are CHORUS; CHORUS runs dockerized (no systemd assumptions). - Topic naming: team channel root is `whoosh.team.` with optional `.control`, `.voting`, `.artefacts` (references only). Include UCXL address metadata. - Discovery: prefer webhook-driven discovery from WHOOSH (Gitea issues events), with polling fallback. Debounce duplicate applications across agents. - MVP toggle: single-agent executor mode (no team self-application) for `bzzz-task` issues is the default until channels stabilize; team application/commenting is feature-flagged. - Security: sign all control messages; maintain revocation lists in SLURP; reject unsigned/stale. Apply SHHH redaction before persistence and fan-out. ### 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 β†’ GITEA Team Issues β†’ CHORUS Agent Discovery β†’ P2P Team Channels β†’ SLURP Artifact Submission β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ WHOOSH Platform β”‚ β”‚ GITEA Repository β”‚ β”‚ CHORUS Agent Fleet β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”‚ Team Composer │─┼────┼→│ Team Issues β”‚ β”‚ β”‚ β”‚ Agent Discovery β”‚ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”‚ Agent Registry │←┼────┼─│ Agent Comments │←┼────┼─│ Self-Applicationβ”‚ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β–Ό β–Ό β–Ό β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ P2P Team Channels β”‚ β”‚ HMMM Reasoning β”‚ β”‚ SLURP Integration β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”‚ UCXL Addressing β”‚ β”‚ β”‚ β”‚ Thought Chains β”‚ β”‚ β”‚ β”‚ Artifact Bundle β”‚ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”‚ Team Consensus β”‚ β”‚ β”‚ β”‚ Decision Recordsβ”‚ β”‚ β”‚ β”‚ Context Archive β”‚ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ ``` ## πŸ€– CHORUS Agent Enhancement ### Agent Self-Awareness System ```go // 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 ```go 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 ```go 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 ```go 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 := ` ## πŸ€– Team Application - %s **Applying for Role:** %s **Commitment Level:** %s **Confidence:** %.1f%% ### 🎯 Value Proposition %s ### πŸ’ͺ Relevant Capabilities %s ### πŸ“Š 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 ### πŸ”§ 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(), ) } ``` ## πŸ”— P2P Team Collaboration ### UCXL Addressing Integration ```go 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 ```go 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 ```go 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 ```go 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 } ``` ## πŸ“Š Integration Monitoring ### Performance Metrics ```go 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.