docs: Add Phase 3 coordination and infrastructure documentation

Comprehensive documentation for coordination, messaging, discovery, and internal systems.

Core Coordination Packages:
- pkg/election - Democratic leader election (uptime-based, heartbeat mechanism, SLURP integration)
- pkg/coordination - Meta-coordination with dependency detection (4 built-in rules)
- coordinator/ - Task orchestration and assignment (AI-powered scoring)
- discovery/ - mDNS peer discovery (automatic LAN detection)

Messaging & P2P Infrastructure:
- pubsub/ - GossipSub messaging (31 message types, role-based topics, HMMM integration)
- p2p/ - libp2p networking (DHT modes, connection management, security)

Monitoring & Health:
- pkg/metrics - Prometheus metrics (80+ metrics across 12 categories)
- pkg/health - Health monitoring (4 HTTP endpoints, enhanced checks, graceful degradation)

Internal Systems:
- internal/licensing - License validation (KACHING integration, cluster leases, fail-closed)
- internal/hapui - Human Agent Portal UI (9 commands, HMMM wizard, UCXL browser, decision voting)
- internal/backbeat - P2P operation telemetry (6 phases, beat synchronization, health reporting)

Documentation Statistics (Phase 3):
- 10 packages documented (~18,000 lines)
- 31 PubSub message types cataloged
- 80+ Prometheus metrics documented
- Complete API references with examples
- Integration patterns and best practices

Key Features Documented:
- Election: 5 triggers, candidate scoring (5 weighted components), stability windows
- Coordination: AI-powered dependency detection, cross-repo sessions, escalation handling
- PubSub: Topic patterns, message envelopes, SHHH redaction, Hypercore logging
- Metrics: All metric types with labels, Prometheus scrape config, alert rules
- Health: Liveness vs readiness, critical checks, Kubernetes integration
- Licensing: Grace periods, circuit breaker, cluster lease management
- HAP UI: Interactive terminal commands, HMMM composition wizard, web interface (beta)
- BACKBEAT: 6-phase operation tracking, beat budget estimation, drift detection

Implementation Status Marked:
-  Production: Election, metrics, health, licensing, pubsub, p2p, discovery, coordinator
- 🔶 Beta: HAP web interface, BACKBEAT telemetry, advanced coordination
- 🔷 Alpha: SLURP election scoring
- ⚠️ Experimental: Meta-coordination, AI-powered dependency detection

Progress: 22/62 files complete (35%)

Next Phase: AI providers, SLURP system, API layer, reasoning engine

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
anthonyrawlins
2025-09-30 18:27:39 +10:00
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# Package: pkg/coordination
**Location**: `/home/tony/chorus/project-queues/active/CHORUS/pkg/coordination/`
## Overview
The `pkg/coordination` package provides **advanced cross-repository coordination primitives** for managing complex task dependencies and multi-agent collaboration in CHORUS. It includes AI-powered dependency detection, meta-coordination sessions, and automated escalation handling to enable sophisticated distributed development workflows.
## Architecture
### Coordination Layers
```
┌─────────────────────────────────────────────────┐
│ MetaCoordinator │
│ - Session management │
│ - AI-powered coordination planning │
│ - Escalation handling │
│ - SLURP integration │
└─────────────────┬───────────────────────────────┘
┌─────────────────▼───────────────────────────────┐
│ DependencyDetector │
│ - Cross-repo dependency detection │
│ - Rule-based pattern matching │
│ - Relationship analysis │
└─────────────────┬───────────────────────────────┘
┌─────────────────▼───────────────────────────────┐
│ PubSub (HMMM Meta-Discussion) │
│ - Coordination messages │
│ - Session broadcasts │
│ - Escalation notifications │
└─────────────────────────────────────────────────┘
```
## Core Components
### MetaCoordinator
Manages advanced cross-repository coordination and multi-agent collaboration sessions.
```go
type MetaCoordinator struct {
pubsub *pubsub.PubSub
ctx context.Context
dependencyDetector *DependencyDetector
slurpIntegrator *integration.SlurpEventIntegrator
// Active coordination sessions
activeSessions map[string]*CoordinationSession
sessionLock sync.RWMutex
// Configuration
maxSessionDuration time.Duration // Default: 30 minutes
maxParticipants int // Default: 5
escalationThreshold int // Default: 10 messages
}
```
**Key Responsibilities:**
- Create and manage coordination sessions
- Generate AI-powered coordination plans
- Monitor session progress and health
- Escalate to humans when needed
- Generate SLURP events from coordination outcomes
- Integrate with HMMM for meta-discussion
### DependencyDetector
Analyzes tasks across repositories to detect relationships and dependencies.
```go
type DependencyDetector struct {
pubsub *pubsub.PubSub
ctx context.Context
knownTasks map[string]*TaskContext
dependencyRules []DependencyRule
coordinationHops int // Default: 3
}
```
**Key Responsibilities:**
- Track tasks across multiple repositories
- Apply pattern-based dependency detection rules
- Identify task relationships (API contracts, schema changes, etc.)
- Broadcast dependency alerts
- Trigger coordination sessions
### CoordinationSession
Represents an active multi-agent coordination session.
```go
type CoordinationSession struct {
SessionID string
Type string // dependency, conflict, planning
Participants map[string]*Participant
TasksInvolved []*TaskContext
Messages []CoordinationMessage
Status string // active, resolved, escalated
CreatedAt time.Time
LastActivity time.Time
Resolution string
EscalationReason string
}
```
**Session Types:**
- **dependency**: Coordinating dependent tasks across repos
- **conflict**: Resolving conflicts or competing changes
- **planning**: Joint planning for complex multi-repo features
**Session States:**
- **active**: Session in progress
- **resolved**: Consensus reached, coordination complete
- **escalated**: Requires human intervention
## Data Structures
### TaskContext
Represents a task with its repository and project context for dependency analysis.
```go
type TaskContext struct {
TaskID int
ProjectID int
Repository string
Title string
Description string
Keywords []string
AgentID string
ClaimedAt time.Time
}
```
### Participant
Represents an agent participating in a coordination session.
```go
type Participant struct {
AgentID string
PeerID string
Repository string
Capabilities []string
LastSeen time.Time
Active bool
}
```
### CoordinationMessage
A message within a coordination session.
```go
type CoordinationMessage struct {
MessageID string
FromAgentID string
FromPeerID string
Content string
MessageType string // proposal, question, agreement, concern
Timestamp time.Time
Metadata map[string]interface{}
}
```
**Message Types:**
- **proposal**: Proposed solution or approach
- **question**: Request for clarification
- **agreement**: Agreement with proposal
- **concern**: Concern or objection
### TaskDependency
Represents a detected relationship between tasks.
```go
type TaskDependency struct {
Task1 *TaskContext
Task2 *TaskContext
Relationship string // Rule name (e.g., "API_Contract")
Confidence float64 // 0.0 - 1.0
Reason string // Human-readable explanation
DetectedAt time.Time
}
```
### DependencyRule
Defines how to detect task relationships.
```go
type DependencyRule struct {
Name string
Description string
Keywords []string
Validator func(task1, task2 *TaskContext) (bool, string)
}
```
## Dependency Detection
### Built-in Detection Rules
#### 1. API Contract Rule
Detects dependencies between API definitions and implementations.
```go
{
Name: "API_Contract",
Description: "Tasks involving API contracts and implementations",
Keywords: []string{"api", "endpoint", "contract", "interface", "schema"},
Validator: func(task1, task2 *TaskContext) (bool, string) {
text1 := strings.ToLower(task1.Title + " " + task1.Description)
text2 := strings.ToLower(task2.Title + " " + task2.Description)
if (strings.Contains(text1, "api") && strings.Contains(text2, "implement")) ||
(strings.Contains(text2, "api") && strings.Contains(text1, "implement")) {
return true, "API definition and implementation dependency"
}
return false, ""
},
}
```
**Example Detection:**
- Task 1: "Define user authentication API"
- Task 2: "Implement authentication endpoint"
- **Detected**: API_Contract dependency
#### 2. Database Schema Rule
Detects schema changes affecting multiple services.
```go
{
Name: "Database_Schema",
Description: "Database schema changes affecting multiple services",
Keywords: []string{"database", "schema", "migration", "table", "model"},
Validator: func(task1, task2 *TaskContext) (bool, string) {
// Checks for database-related keywords in both tasks
// Returns true if both tasks involve database work
},
}
```
**Example Detection:**
- Task 1: "Add user preferences table"
- Task 2: "Update user service for preferences"
- **Detected**: Database_Schema dependency
#### 3. Configuration Dependency Rule
Detects configuration changes affecting multiple components.
```go
{
Name: "Configuration_Dependency",
Description: "Configuration changes affecting multiple components",
Keywords: []string{"config", "environment", "settings", "parameters"},
}
```
**Example Detection:**
- Task 1: "Add feature flag for new UI"
- Task 2: "Implement feature flag checks in backend"
- **Detected**: Configuration_Dependency
#### 4. Security Compliance Rule
Detects security changes requiring coordinated implementation.
```go
{
Name: "Security_Compliance",
Description: "Security changes requiring coordinated implementation",
Keywords: []string{"security", "auth", "permission", "token", "encrypt"},
}
```
**Example Detection:**
- Task 1: "Implement JWT token refresh"
- Task 2: "Update authentication middleware"
- **Detected**: Security_Compliance dependency
### Custom Rules
Add project-specific dependency detection:
```go
customRule := DependencyRule{
Name: "GraphQL_Schema",
Description: "GraphQL schema and resolver dependencies",
Keywords: []string{"graphql", "schema", "resolver", "query", "mutation"},
Validator: func(task1, task2 *TaskContext) (bool, string) {
text1 := strings.ToLower(task1.Title + " " + task1.Description)
text2 := strings.ToLower(task2.Title + " " + task2.Description)
hasSchema := strings.Contains(text1, "schema") || strings.Contains(text2, "schema")
hasResolver := strings.Contains(text1, "resolver") || strings.Contains(text2, "resolver")
if hasSchema && hasResolver {
return true, "GraphQL schema and resolver must be coordinated"
}
return false, ""
},
}
dependencyDetector.AddCustomRule(customRule)
```
## Coordination Flow
### 1. Task Registration and Detection
```
Task Claimed by Agent A → RegisterTask() → DependencyDetector
detectDependencies()
Apply all dependency rules to known tasks
Dependency detected? → Yes → announceDependency()
↓ ↓
No MetaCoordinator
```
### 2. Dependency Announcement
```go
// Dependency detector announces to HMMM meta-discussion
coordMsg := map[string]interface{}{
"message_type": "dependency_detected",
"dependency": dep,
"coordination_request": "Cross-repository dependency detected...",
"agents_involved": [agentA, agentB],
"repositories": [repoA, repoB],
"hop_count": 0,
"max_hops": 3,
}
pubsub.PublishHmmmMessage(MetaDiscussion, coordMsg)
```
### 3. Session Creation
```
MetaCoordinator receives dependency_detected message
handleDependencyDetection()
Create CoordinationSession
Add participating agents
Generate AI coordination plan
Broadcast plan to participants
```
### 4. AI-Powered Coordination Planning
```go
prompt := `
You are an expert AI project coordinator managing a distributed development team.
SITUATION:
- A dependency has been detected between two tasks in different repositories
- Task 1: repo1/title #42 (Agent: agent-001)
- Task 2: repo2/title #43 (Agent: agent-002)
- Relationship: API_Contract
- Reason: API definition and implementation dependency
COORDINATION REQUIRED:
Generate a concise coordination plan that addresses:
1. What specific coordination is needed between the agents
2. What order should tasks be completed in (if any)
3. What information/artifacts need to be shared
4. What potential conflicts to watch for
5. Success criteria for coordinated completion
`
plan := reasoning.GenerateResponse(ctx, "phi3", prompt)
```
**Plan Output Example:**
```
COORDINATION PLAN:
1. SEQUENCE:
- Task 1 (API definition) must be completed first
- Task 2 (implementation) depends on finalized API contract
2. INFORMATION SHARING:
- Agent-001 must share: API specification document, endpoint definitions
- Agent-002 must share: Implementation plan, integration tests
3. COORDINATION POINTS:
- Review API spec before implementation begins
- Daily sync on implementation progress
- Joint testing before completion
4. POTENTIAL CONFLICTS:
- API spec changes during implementation
- Performance requirements not captured in spec
- Authentication/authorization approach
5. SUCCESS CRITERIA:
- API spec reviewed and approved
- Implementation matches spec
- Integration tests pass
- Documentation complete
```
### 5. Session Progress Monitoring
```
Agents respond to coordination plan
handleCoordinationResponse()
Add message to session
Update participant activity
evaluateSessionProgress()
┌──────────────────────┐
│ Check conditions: │
│ - Message count │
│ - Session duration │
│ - Agreement keywords │
└──────┬───────────────┘
┌──────▼──────┬──────────────┐
│ │ │
Consensus? Too long? Too many msgs?
│ │ │
Resolved Escalate Escalate
```
### 6. Session Resolution
**Consensus Reached:**
```go
// Detect agreement in recent messages
agreementKeywords := []string{
"agree", "sounds good", "approved", "looks good", "confirmed"
}
if agreementCount >= len(participants)-1 {
resolveSession(session, "Consensus reached among participants")
}
```
**Session Resolved:**
1. Update session status to "resolved"
2. Record resolution reason
3. Generate SLURP event (if integrator available)
4. Broadcast resolution to participants
5. Clean up after timeout
### 7. Session Escalation
**Escalation Triggers:**
- Message count exceeds threshold (default: 10)
- Session duration exceeds limit (default: 30 minutes)
- Explicit escalation request from agent
**Escalation Process:**
```go
escalateSession(session, reason)
Update status to "escalated"
Generate SLURP event for human review
Broadcast escalation notification
Human intervention required
```
## SLURP Integration
### Event Generation from Sessions
When sessions are resolved or escalated, the MetaCoordinator generates SLURP events:
```go
discussionContext := integration.HmmmDiscussionContext{
DiscussionID: session.SessionID,
SessionID: session.SessionID,
Participants: [agentIDs],
StartTime: session.CreatedAt,
EndTime: session.LastActivity,
Messages: hmmmMessages,
ConsensusReached: (outcome == "resolved"),
ConsensusStrength: 0.9, // 0.3 for escalated, 0.5 for other
OutcomeType: outcome, // "resolved" or "escalated"
ProjectPath: projectPath,
RelatedTasks: [taskIDs],
Metadata: {
"session_type": session.Type,
"session_status": session.Status,
"resolution": session.Resolution,
"escalation_reason": session.EscalationReason,
"message_count": len(session.Messages),
"participant_count": len(session.Participants),
},
}
slurpIntegrator.ProcessHmmmDiscussion(ctx, discussionContext)
```
**SLURP Event Outcomes:**
- **Resolved sessions**: High consensus (0.9), successful coordination
- **Escalated sessions**: Low consensus (0.3), human intervention needed
- **Other outcomes**: Medium consensus (0.5)
### Policy Learning
SLURP uses coordination session data to learn:
- Effective coordination patterns
- Common dependency types
- Escalation triggers
- Agent collaboration efficiency
- Task complexity indicators
## PubSub Message Types
### 1. dependency_detected
Announces a detected dependency between tasks.
```json
{
"message_type": "dependency_detected",
"dependency": {
"task1": {
"task_id": 42,
"project_id": 1,
"repository": "backend-api",
"title": "Define user authentication API",
"agent_id": "agent-001"
},
"task2": {
"task_id": 43,
"project_id": 2,
"repository": "frontend-app",
"title": "Implement login page",
"agent_id": "agent-002"
},
"relationship": "API_Contract",
"confidence": 0.8,
"reason": "API definition and implementation dependency",
"detected_at": "2025-09-30T10:00:00Z"
},
"coordination_request": "Cross-repository dependency detected...",
"agents_involved": ["agent-001", "agent-002"],
"repositories": ["backend-api", "frontend-app"],
"hop_count": 0,
"max_hops": 3
}
```
### 2. coordination_plan
Broadcasts AI-generated coordination plan to participants.
```json
{
"message_type": "coordination_plan",
"session_id": "dep_1_42_1727692800",
"plan": "COORDINATION PLAN:\n1. SEQUENCE:\n...",
"tasks_involved": [taskContext1, taskContext2],
"participants": {
"agent-001": { "agent_id": "agent-001", "repository": "backend-api" },
"agent-002": { "agent_id": "agent-002", "repository": "frontend-app" }
},
"message": "Coordination plan generated for dependency: API_Contract"
}
```
### 3. coordination_response
Agent response to coordination plan or session message.
```json
{
"message_type": "coordination_response",
"session_id": "dep_1_42_1727692800",
"agent_id": "agent-001",
"response": "I agree with the proposed sequence. API spec will be ready by EOD.",
"timestamp": "2025-09-30T10:05:00Z"
}
```
### 4. session_message
General message within a coordination session.
```json
{
"message_type": "session_message",
"session_id": "dep_1_42_1727692800",
"from_agent": "agent-002",
"content": "Can we schedule a quick sync to review the API spec?",
"timestamp": "2025-09-30T10:10:00Z"
}
```
### 5. escalation
Session escalated to human intervention.
```json
{
"message_type": "escalation",
"session_id": "dep_1_42_1727692800",
"escalation_reason": "Message limit exceeded - human intervention needed",
"session_summary": "Session dep_1_42_1727692800 (dependency): 2 participants, 12 messages, duration 35m",
"participants": { /* participant info */ },
"tasks_involved": [ /* task contexts */ ],
"requires_human": true
}
```
### 6. resolution
Session successfully resolved.
```json
{
"message_type": "resolution",
"session_id": "dep_1_42_1727692800",
"resolution": "Consensus reached among participants",
"summary": "Session dep_1_42_1727692800 (dependency): 2 participants, 8 messages, duration 15m"
}
```
## Usage Examples
### Basic Setup
```go
import (
"context"
"chorus/pkg/coordination"
"chorus/pubsub"
)
// Create MetaCoordinator
mc := coordination.NewMetaCoordinator(ctx, pubsubInstance)
// Optionally attach SLURP integrator
mc.SetSlurpIntegrator(slurpIntegrator)
// MetaCoordinator automatically:
// - Initializes DependencyDetector
// - Sets up HMMM message handlers
// - Starts session cleanup loop
```
### Register Tasks for Dependency Detection
```go
// Agent claims a task
taskContext := &coordination.TaskContext{
TaskID: 42,
ProjectID: 1,
Repository: "backend-api",
Title: "Define user authentication API",
Description: "Create OpenAPI spec for user auth endpoints",
Keywords: []string{"api", "authentication", "openapi"},
AgentID: "agent-001",
ClaimedAt: time.Now(),
}
mc.dependencyDetector.RegisterTask(taskContext)
```
### Add Custom Dependency Rule
```go
// Add project-specific rule
microserviceRule := coordination.DependencyRule{
Name: "Microservice_Interface",
Description: "Microservice interface and consumer dependencies",
Keywords: []string{"microservice", "interface", "consumer", "producer"},
Validator: func(task1, task2 *coordination.TaskContext) (bool, string) {
t1 := strings.ToLower(task1.Title + " " + task1.Description)
t2 := strings.ToLower(task2.Title + " " + task2.Description)
hasProducer := strings.Contains(t1, "producer") || strings.Contains(t2, "producer")
hasConsumer := strings.Contains(t1, "consumer") || strings.Contains(t2, "consumer")
if hasProducer && hasConsumer {
return true, "Microservice producer and consumer must coordinate"
}
return false, ""
},
}
mc.dependencyDetector.AddCustomRule(microserviceRule)
```
### Query Active Sessions
```go
// Get all active coordination sessions
sessions := mc.GetActiveSessions()
for sessionID, session := range sessions {
fmt.Printf("Session %s:\n", sessionID)
fmt.Printf(" Type: %s\n", session.Type)
fmt.Printf(" Status: %s\n", session.Status)
fmt.Printf(" Participants: %d\n", len(session.Participants))
fmt.Printf(" Messages: %d\n", len(session.Messages))
fmt.Printf(" Duration: %v\n", time.Since(session.CreatedAt))
}
```
### Monitor Coordination Events
```go
// Set custom HMMM message handler
pubsub.SetHmmmMessageHandler(func(msg pubsub.Message, from peer.ID) {
switch msg.Data["message_type"] {
case "dependency_detected":
fmt.Printf("🔗 Dependency detected: %v\n", msg.Data)
case "coordination_plan":
fmt.Printf("📋 Coordination plan: %v\n", msg.Data)
case "escalation":
fmt.Printf("🚨 Escalation: %v\n", msg.Data)
case "resolution":
fmt.Printf("✅ Resolution: %v\n", msg.Data)
}
})
```
## Configuration
### MetaCoordinator Configuration
```go
mc := coordination.NewMetaCoordinator(ctx, ps)
// Adjust session parameters
mc.maxSessionDuration = 45 * time.Minute // Extend session timeout
mc.maxParticipants = 10 // Support larger teams
mc.escalationThreshold = 15 // More messages before escalation
```
### DependencyDetector Configuration
```go
dd := mc.dependencyDetector
// Adjust coordination hop limit
dd.coordinationHops = 5 // Allow deeper meta-discussion chains
```
## Session Lifecycle Management
### Automatic Cleanup
Sessions are automatically cleaned up by the session cleanup loop:
```go
// Runs every 10 minutes
func (mc *MetaCoordinator) cleanupInactiveSessions() {
for sessionID, session := range mc.activeSessions {
// Remove sessions older than 2 hours OR already resolved/escalated
if time.Since(session.LastActivity) > 2*time.Hour ||
session.Status == "resolved" ||
session.Status == "escalated" {
delete(mc.activeSessions, sessionID)
}
}
}
```
**Cleanup Criteria:**
- Session inactive for 2+ hours
- Session status is "resolved"
- Session status is "escalated"
### Manual Session Management
```go
// Not exposed in current API, but could be added:
// Force resolve session
mc.resolveSession(session, "Manual resolution by admin")
// Force escalate session
mc.escalateSession(session, "Manual escalation requested")
// Cancel/close session
mc.closeSession(sessionID)
```
## Performance Considerations
### Memory Usage
- **TaskContext Storage**: ~500 bytes per task
- **Active Sessions**: ~5KB per session (varies with message count)
- **Dependency Rules**: ~1KB per rule
**Typical Usage**: 100 tasks + 10 sessions = ~100KB
### CPU Usage
- **Dependency Detection**: O(N²) where N = number of tasks per repository
- **Rule Evaluation**: O(R) where R = number of rules
- **Session Monitoring**: Periodic evaluation (every message received)
**Optimization**: Dependency detection skips same-repository comparisons.
### Network Usage
- **Dependency Announcements**: ~2KB per dependency
- **Coordination Plans**: ~5KB per plan (includes full context)
- **Session Messages**: ~1KB per message
- **SLURP Events**: ~10KB per event (includes full session history)
## Best Practices
### 1. Rule Design
**Good Rule:**
```go
// Specific, actionable, clear success criteria
{
Name: "Database_Migration",
Keywords: []string{"migration", "schema", "database"},
Validator: func(t1, t2 *TaskContext) (bool, string) {
// Clear matching logic
// Specific reason returned
},
}
```
**Bad Rule:**
```go
// Too broad, unclear coordination needed
{
Name: "Backend_Tasks",
Keywords: []string{"backend"},
Validator: func(t1, t2 *TaskContext) (bool, string) {
return strings.Contains(t1.Title, "backend") &&
strings.Contains(t2.Title, "backend"), "Both backend tasks"
},
}
```
### 2. Session Participation
- **Respond promptly**: Keep sessions moving
- **Be explicit**: Use clear agreement/disagreement language
- **Stay focused**: Don't derail session with unrelated topics
- **Escalate when stuck**: Don't let sessions drag on indefinitely
### 3. AI Plan Quality
AI plans are most effective when:
- Task descriptions are detailed
- Dependencies are clear
- Agent capabilities are well-defined
- Historical context is available
### 4. SLURP Integration
For best SLURP learning:
- Enable SLURP integrator at startup
- Ensure all sessions generate events (resolved or escalated)
- Provide rich task metadata
- Include project context in task descriptions
## Troubleshooting
### Dependencies Not Detected
**Symptoms**: Related tasks not triggering coordination.
**Checks:**
1. Verify tasks registered with detector: `dd.GetKnownTasks()`
2. Check rule keywords match task content
3. Test validator logic with task pairs
4. Verify tasks are from different repositories
5. Check PubSub connection for announcements
### Sessions Not Escalating
**Symptoms**: Long-running sessions without escalation.
**Checks:**
1. Verify escalation threshold: `mc.escalationThreshold`
2. Check session duration limit: `mc.maxSessionDuration`
3. Verify message count in session
4. Check for agreement keywords in messages
5. Test escalation logic manually
### AI Plans Not Generated
**Symptoms**: Sessions created but no coordination plan.
**Checks:**
1. Verify reasoning engine available: `reasoning.GenerateResponse()`
2. Check AI model configuration
3. Verify network connectivity to AI provider
4. Check reasoning engine error logs
5. Test with simpler dependency
### SLURP Events Not Generated
**Symptoms**: Sessions complete but no SLURP events.
**Checks:**
1. Verify SLURP integrator attached: `mc.SetSlurpIntegrator()`
2. Check SLURP integrator initialization
3. Verify session outcome triggers event generation
4. Check SLURP integrator error logs
5. Test event generation manually
## Future Enhancements
### Planned Features
1. **Machine Learning Rules**: Learn dependency patterns from historical data
2. **Automated Testing**: Generate integration tests for coordinated tasks
3. **Visualization**: Web UI for monitoring active sessions
4. **Advanced Metrics**: Track coordination efficiency and success rates
5. **Multi-Repo CI/CD**: Coordinate deployments across dependent services
6. **Conflict Resolution**: AI-powered conflict resolution suggestions
7. **Predictive Coordination**: Predict dependencies before tasks are claimed
## See Also
- [coordinator/](coordinator.md) - Task coordinator integration
- [pubsub/](../pubsub.md) - PubSub messaging for coordination
- [pkg/integration/](integration.md) - SLURP integration
- [pkg/hmmm/](hmmm.md) - HMMM meta-discussion system
- [reasoning/](../reasoning.md) - AI reasoning engine for planning
- [internal/logging/](../internal/logging.md) - Hypercore logging