gh-gsornsen-mycelium-plugins-mycelium-core/commands/team-status.md

allowed-tools, description, argument-hint

allowed-tools	description	argument-hint
Bash(redis-cli:*), Read, Glob, mcp__RedisMCPServer__*	Multi-agent coordination status check. Shows agent workload, active tasks, and team health with formatted progress bars and statistics.	agent-type

Multi-Agent Team Status

Check current workload and coordination status of Claude Code subagents with formatted visualization.

Context

Command arguments: $ARGS

Coordination Method: Redis MCP with JSON serialization and datetime handling

Your Task

Display formatted team status using Redis coordination data with proper JSON parsing:

Implementation

1. Parse command arguments to determine display mode:

   • No arguments: Show overview of all agents
   • Agent type specified: Show detailed view of that agent

2. Query Redis with JSON parsing:

   • Get all agent statuses from agents:status hash
   • Get heartbeat data from agents:heartbeat hash
   • Parse JSON values using the pattern from RedisCoordinationHelper
   • Restore datetime fields (fields ending in _at or containing timestamp)

3. Display formatted output matching these patterns:

Overview Mode (No Arguments)

=== Multi-Agent Team Status ===
Coordination Method: Redis MCP

Agent Workload:
  project-manager      ██████████ 100% | 1 active task
  platform-engineer    ██████████ 100% | 1 active task
  ai-engineer          ████████░░ 80% | 2 active tasks
  data-engineer        ████░░░░░░ 40% | 1 active task
  python-pro           ░░░░░░░░░░ 0% | available

Task Distribution:
  Total Active: 5 tasks
  Average Load: 64%
  Load Variance: 35% (⚠️ unbalanced)

Heartbeat Status:
  ✅ All agents reporting healthy

Last Updated: 2025-11-07 20:45:30

Progress Bar Format:

• 10 blocks: █ for used capacity, ░ for available
• Calculate blocks: Math.round(workload / 10)
• Show percentage and task count
• Add "(at capacity)" warning if workload >= 100

Workload Indicators:

• 0%: "available"
• 1-100%: "N active task(s)"
• ≥100%: "N active tasks (at capacity)"

Balance Status:

• Variance < 20%: "✅ balanced"
• Variance ≥ 20%: "⚠️ unbalanced"

Heartbeat Freshness:

• Age ≤ 60 minutes: Healthy
• Age > 60 minutes: Warn with specific age (Xh Ym or Ym format)

Detailed Mode (Agent Type Argument)

When user specifies agent type (e.g., /team-status project-manager):

=== Agent Status: project-manager ===

Current Status: BUSY (100% capacity)

Active Tasks (1):
  1. smart-onboarding-coordination
     - Progress: 45%
     - Duration: 2h 15m
     - Description: Coordinating Smart Onboarding implementation

Recent History (from status data):
  - Current workload: 100%
  - Task count: 1
  - Last updated: 5m ago

Circuit Breaker: ✅ CLOSED (healthy)
Last Heartbeat: 5m ago

Task Display:

• Show task ID or name
• Display progress if available
• Calculate duration from started_at if present
• Show description if available

Heartbeat Age Calculation:

• Compare timestamp to current time
• Format as "Xh Ym" (hours + minutes) or "Ym" (minutes only)
• Warn if age > 60 minutes

JSON Parsing Logic

Implement this parsing pattern (from RedisCoordinationHelper):

def parse_redis_value(raw_value: str) -> dict:
    """Parse Redis value with JSON deserialization and datetime restoration."""
    try:
        parsed = json.loads(raw_value)

        # Handle non-dict values (wrap in dict)
        if not isinstance(parsed, dict):
            return {"value": parsed}

        # Restore datetime fields
        for key, value in parsed.items():
            if isinstance(value, str) and (key.endswith("_at") or "timestamp" in key.lower()):
                try:
                    # Convert ISO format string to datetime
                    parsed[key] = datetime.fromisoformat(value)
                except ValueError:
                    # Not a valid datetime, keep as string
                    pass

        return parsed

    except json.JSONDecodeError:
        # Not JSON, return as plain value
        return {"value": raw_value}

Statistics Calculations

Load Variance (standard deviation):

def calculate_variance(workload_values: list[int]) -> float:
    """Calculate standard deviation of workload values."""
    if not workload_values:
        return 0.0

    mean = sum(workload_values) / len(workload_values)
    squared_diffs = [(val - mean) ** 2 for val in workload_values]
    variance = sum(squared_diffs) / len(workload_values)

    return variance ** 0.5  # Standard deviation

Duration Formatting:

def format_duration(start_time: datetime) -> str:
    """Format duration from start time to now."""
    delta = datetime.now() - start_time

    total_seconds = int(delta.total_seconds())
    hours = total_seconds // 3600
    minutes = (total_seconds % 3600) // 60

    if hours > 0:
        return f"{hours}h {minutes}m"
    else:
        return f"{minutes}m"

Error Handling

No Redis Connection:

⚠️  No coordination infrastructure detected

To enable real-time agent coordination:

Option 1 (Recommended): Deploy Redis Stack
  mycelium deploy start --yes

Option 2: Create coordination directory
  mkdir -p .claude/coordination/
  # Agents will create status files here

Empty Redis Data:

⚠️  No agents currently coordinating

To enable real-time agent coordination:
  Option 1: Deploy Redis Stack (recommended)
    mycelium deploy start --yes

  Option 2: Create coordination directory
    mkdir -p .claude/coordination/

Agent Not Found (in detailed mode):

❌ Agent 'unknown-agent' not found

Available agents:
  - project-manager
  - platform-engineer
  - ai-engineer
  - data-engineer
  - python-pro

Stale Heartbeats (age > 60 minutes):

Heartbeat Status:
  ⚠️  Stale heartbeats detected:
    - ai-engineer: last seen 2h 15m ago
    - ml-engineer: last seen 3h 42m ago
    - python-pro: last seen 1h 5m ago

MCP Tool Usage

Use these MCP tools to query Redis:

// Get all agent statuses
const agentStatuses = await mcp__RedisMCPServer__hgetall({
  name: "agents:status"
});

// Get specific agent status
const status = await mcp__RedisMCPServer__hget({
  name: "agents:status",
  key: "ai-engineer"
});

// Get all heartbeats
const heartbeats = await mcp__RedisMCPServer__hgetall({
  name: "agents:heartbeat"
});

// Get specific heartbeat
const heartbeat = await mcp__RedisMCPServer__hget({
  name: "agents:heartbeat",
  key: "ai-engineer"
});

Display Requirements

1. Sort agents by workload (highest to lowest) in overview mode
2. Calculate total statistics (total tasks, average load, variance)
3. Format progress bars with 10 blocks (█ and ░ characters)
4. Check heartbeat freshness and warn if stale (>60 min)
5. Handle missing data gracefully (show 0% workload, "available" status)
6. Parse JSON correctly (handle both JSON strings and plain values)
7. Restore datetime fields (fields ending in _at or containing timestamp)
8. Format timestamps as human-readable durations (e.g., "2h 15m")

Integration Notes

This command integrates with:

• RedisCoordinationHelper library for JSON serialization patterns
• mycelium deploy command for Redis Stack deployment
• Agent heartbeat mechanisms for health monitoring
• Workload management for task distribution

Expected Behavior

Query Redis MCP Server:

1. Check if MCP server is available
2. Query agents:status hash for all agent data
3. Query agents:heartbeat hash for heartbeat timestamps
4. Parse JSON data with datetime restoration
5. Display formatted output with statistics

Handle Parsing Errors:

• If JSON parsing fails, wrap value in {"value": raw_value}
• If datetime parsing fails, keep as string
• If Redis query fails, show helpful error with deployment instructions

Calculate Statistics:

• Sort agents by workload (descending)
• Sum total active tasks
• Calculate average workload percentage
• Calculate load variance (standard deviation)
• Determine balance status (< 20% = balanced)

Check Heartbeat Health:

• Parse heartbeat timestamps
• Calculate age in minutes
• Warn if any heartbeat > 60 minutes old
• Format age as "Xh Ym" or "Ym"

Example Outputs

Scenario 1: Active Team

=== Multi-Agent Team Status ===
Coordination Method: Redis MCP

Agent Workload:
  ai-engineer          ██████████ 100% | 3 active tasks (at capacity)
  data-engineer        ████████░░ 80% | 2 active tasks
  python-pro           ████░░░░░░ 40% | 1 active task
  performance-eng      ░░░░░░░░░░ 0% | available

Task Distribution:
  Total Active: 6 tasks
  Average Load: 55%
  Load Variance: 38% (⚠️ unbalanced)

Heartbeat Status:
  ✅ All agents reporting healthy

Last Updated: 2025-11-07 20:45:30

Scenario 2: Stale Heartbeats

=== Multi-Agent Team Status ===
Coordination Method: Redis MCP

Agent Workload:
  project-manager      ██████████ 100% | 1 active task

Task Distribution:
  Total Active: 1 task
  Average Load: 100%
  Load Variance: 0% (✅ balanced)

Heartbeat Status:
  ⚠️  Stale heartbeats detected:
    - project-manager: last seen 25 days ago

Last Updated: 2025-11-07 20:45:30

Scenario 3: Detailed Agent View

=== Agent Status: ai-engineer ===

Current Status: BUSY (85% capacity)

Active Tasks (2):
  1. train-voice-model
     - Progress: 35%
     - Duration: 4h 23m
     - Description: Training custom voice model

  2. evaluate-checkpoint
     - Progress: 70%
     - Duration: 45m
     - Description: Evaluating model checkpoint

Recent History (from status data):
  - Current workload: 85%
  - Task count: 2
  - Last updated: 2m ago

Circuit Breaker: ✅ CLOSED (healthy)
Last Heartbeat: 2m ago

Scenario 4: No Agents

=== Multi-Agent Team Status ===
Coordination Method: Redis MCP

⚠️  No agents currently coordinating

To enable real-time agent coordination:
  Option 1: Deploy Redis Stack (recommended)
    mycelium deploy start --yes

  Option 2: Create coordination directory
    mkdir -p .claude/coordination/

Implementation Steps

When user runs /team-status:

1. Parse arguments: Extract agent type from $ARGS if provided
2. Query Redis MCP:
   • Call mcp__RedisMCPServer__hgetall for agents:status
   • Call mcp__RedisMCPServer__hgetall for agents:heartbeat
3. Parse JSON data:
   • Use parse_redis_value() logic for each value
   • Restore datetime fields
4. Determine display mode:
   • If agent type specified: Show detailed view
   • Otherwise: Show overview with all agents
5. Format output:
   • Create progress bars (10 blocks)
   • Calculate statistics (total, average, variance)
   • Check heartbeat freshness (warn if >60 min)
   • Display timestamp
6. Handle errors:
   • Show helpful message if Redis unavailable
   • Show empty state if no agents
   • Show agent not found if invalid agent type

Now implement this formatted team status display with proper JSON parsing and error handling.