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doanchienthangdev

managing-omega-sprints

by doanchienthangdev

Omega Vibecode Kit

2🍴 1📅 2026年1月21日
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SKILL.md


name: managing-omega-sprints description: Orchestrates AI-native sprint management with autonomous agent coordination and continuous delivery. Use when running development sprints with AI agent teams or coordinating parallel task execution. category: omega triggers:

  • omega sprint
  • sprint planning
  • AI team management
  • agent orchestration

Managing Omega Sprints

Execute AI-native sprint management with autonomous agent orchestration, intelligent task routing, and continuous delivery cycles.

Quick Start

# 1. Define sprint vision
Vision:
  Objective: "Implement OAuth2 authentication"
  Success: ["3 providers", "95% completion rate", "OWASP compliant"]

# 2. Break into agent-executable tasks
Tasks:
  - { id: "types", agent: "architect", tokens: 5K }
  - { id: "google-oauth", agent: "fullstack", tokens: 8K, depends: ["types"] }
  - { id: "tests", agent: "tester", tokens: 6K, depends: ["google-oauth"] }

# 3. Execute with autonomy level
Execution:
  Autonomy: "semi-auto"
  Checkpoints: ["phase-complete", "error-threshold"]
  QualityGates: ["coverage > 80%", "no-critical-bugs"]

Features

FeatureDescriptionGuide
Sprint LifecycleVision, Plan, Execute, Deliver, RetrospectAI-native 5-phase cycle
Task BreakdownAtomic, testable, agent-sized tasksHours not days per task
Agent RoutingMatch tasks to optimal agentsCapability + load scoring
Autonomy LevelsFull-auto to supervised modesBalance speed and oversight
Quality GatesAutomated checkpointsCoverage, security, performance
Parallel ExecutionSwarm-based task processingMaximize parallelization
Sprint AnalyticsVelocity, quality, efficiency metricsContinuous improvement

Common Patterns

Sprint Lifecycle

VISION ──> PLAN ──> EXECUTE ──> DELIVER ──> RETROSPECT
   │         │         │           │             │
   ▼         ▼         ▼           ▼             ▼
 Define   Break into  Agents    Ship to      Learn and
 success  agent-ready  work    production    improve
 criteria   tasks    parallel

Vision Definition

interface SprintVision {
  objective: string;
  businessValue: string;
  successCriteria: SuccessCriterion[];
  scope: {
    included: string[];
    excluded: string[];
    risks: Risk[];
  };
  qualityGates: QualityGate[];
}

const vision: SprintVision = {
  objective: "Implement user authentication with OAuth2",
  businessValue: "Reduce signup friction by 60%",
  successCriteria: [
    { metric: "OAuth providers", target: 3 },
    { metric: "Auth completion rate", target: "95%" },
    { metric: "Security audit", target: "OWASP compliant" }
  ],
  qualityGates: [
    { type: 'coverage', threshold: 80 },
    { type: 'security-scan', threshold: 'no-critical' }
  ]
};

Task Breakdown

interface SprintTask {
  id: string;
  title: string;
  type: 'feature' | 'bugfix' | 'test' | 'docs';
  priority: 'critical' | 'high' | 'medium';
  estimatedTokens: number;
  dependencies: string[];
  suggestedAgent: AgentType;
  acceptanceCriteria: string[];
}

// Layer-based breakdown
const tasks = [
  // Layer 1: Foundation
  { id: 'types', title: 'Define TypeScript interfaces', agent: 'architect' },
  { id: 'schema', title: 'Create DB migrations', depends: ['types'] },

  // Layer 2: Implementation (parallel)
  { id: 'google', title: 'Google OAuth', depends: ['types'] },
  { id: 'github', title: 'GitHub OAuth', depends: ['types'] },

  // Layer 3: Quality
  { id: 'tests', title: 'Integration tests', depends: ['google', 'github'] }
];

Agent Routing

type AgentType = 'architect' | 'fullstack' | 'debugger' | 'tester' | 'reviewer';

const routingRules: Record<TaskType, AgentType[]> = {
  feature: ['fullstack', 'frontend', 'backend'],
  bugfix: ['debugger', 'fullstack'],
  test: ['tester'],
  docs: ['docs-manager'],
  research: ['oracle', 'architect']
};

// Scoring algorithm
function calculateFitScore(agent: Agent, task: Task): number {
  let score = 0;
  score += capabilityMatch * 40;      // Core capabilities
  score += specializationMatch * 30;   // Domain expertise
  score += (1 - loadFactor) * 20;      // Availability
  score += hasContext ? 10 : 0;        // Context continuity
  return score;
}

Autonomy Levels

const autonomyConfigs = {
  'full-auto': {
    checkpoints: [{ trigger: 'phase-complete', action: 'notify' }],
    approvalRequired: ['production-deploy']
  },
  'semi-auto': {
    checkpoints: [
      { trigger: 'task-complete', action: 'notify' },
      { trigger: 'phase-complete', action: 'review', timeout: 3600 }
    ],
    approvalRequired: ['merge-to-main', 'production-deploy']
  },
  'supervised': {
    checkpoints: [{ trigger: 'task-complete', action: 'review' }],
    approvalRequired: ['all-merges', 'all-deploys']
  }
};

Sprint Metrics

interface SprintMetrics {
  velocity: { completed: number; planned: number; ratio: number };
  quality: { bugs: number; coverage: number; score: number };
  efficiency: { totalTokens: number; parallelization: number };
  agents: Map<AgentType, { tasks: number; efficiency: number }>;
}

// Dashboard template
`
SPRINT DASHBOARD: ${name}
────────────────────────────────────
PROGRESS         QUALITY         AGENTS
████████░░ 80%   Coverage: 87%   arch: idle
24/30 tasks      Bugs: 2         dev-1: working
                 Security: OK    tester: queued
`

Retrospective Framework

## Sprint Retrospective

### Summary
- Velocity: X/Y tasks (Z%)
- Quality: Coverage %, Bugs introduced
- Efficiency: Tokens used, Parallelization ratio

### What Went Well
1. [Success] - Why it worked - How to replicate

### What Could Improve
1. [Challenge] - Root cause - Proposed solution

### Action Items
| Action | Priority | Owner |
|--------|----------|-------|
| [Action] | High | [Agent] |

### Learnings to Encode
- [Pattern to add to agent prompts]

Best Practices

DoAvoid
Define clear success criteria before sprintStarting without vision and scope
Break tasks small enough for single-agentTasks with circular dependencies
Enable maximum parallelizationSkipping quality gates under pressure
Set appropriate autonomy based on riskIgnoring retrospective insights
Track metrics consistentlyOver-committing capacity
Run retrospectives after every sprintContext-switching agents unnecessarily
Encode learnings into agent promptsDeploying without automated tests
Use quality gates to prevent regressionsLetting blockers sit unaddressed
Maintain sprint rhythm for predictabilitySkipping the retrospective phase
Celebrate wins to build momentumForgetting to update documentation

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