task-estimation
Task Estimation
When to use this skill
- Sprint Planning: Decide what work to include in the sprint
- Roadmap creation: Build long-term plans
- Resource planning: Estimate team size and schedule
Instructions
Step 1: Story Points (relative estimation)
Fibonacci sequence: 1, 2, 3, 5, 8, 13, 21
## Story Point guidelines
### 1 Point (Very Small)
- Example: text change, constant value update
- Time: 1-2 hours
- Complexity: very low
- Risk: none
### 2 Points (Small)
- Example: simple bug fix, add logging
- Time: 2-4 hours
- Complexity: low
- Risk: low
### 3 Points (Medium)
- Example: simple CRUD API endpoint
- Time: 4-8 hours
- Complexity: medium
- Risk: low
### 5 Points (Medium-Large)
- Example: complex form implementation, auth middleware
- Time: 1-2 days
- Complexity: medium
- Risk: medium
### 8 Points (Large)
- Example: new feature (frontend + backend)
- Time: 2-3 days
- Complexity: high
- Risk: medium
### 13 Points (Very Large)
- Example: payment system integration
- Time: 1 week
- Complexity: very high
- Risk: high
- **Recommended**: Split into smaller tasks
### 21+ Points (Epic)
- **Required**: Must be split into smaller stories
Step 2: Planning Poker
Process:
- Product Owner explains the story
- Team asks questions
- Everyone picks a card (1, 2, 3, 5, 8, 13)
- Reveal simultaneously
- Explain highest/lowest scores
- Re-vote
- Reach consensus
Example:
Story: "Users can upload a profile photo"
Member A: 3 points (simple frontend)
Member B: 5 points (image resizing needed)
Member C: 8 points (S3 upload, security considerations)
Discussion:
- Use an image processing library
- S3 is already set up
- File size validation needed
Re-vote → consensus on 5 points
Step 3: T-Shirt Sizing (quick estimation)
## T-Shirt sizes
- **XS**: 1-2 Story Points (within 1 hour)
- **S**: 2-3 Story Points (half day)
- **M**: 5 Story Points (1-2 days)
- **L**: 8 Story Points (1 week)
- **XL**: 13+ Story Points (needs splitting)
**When to use**:
- Initial backlog grooming
- Rough roadmap planning
- Quick prioritization
Step 4: Consider risk and uncertainty
Estimation adjustment:
interface TaskEstimate {
baseEstimate: number; // base estimate
risk: 'low' | 'medium' | 'high';
uncertainty: number; // 0-1
finalEstimate: number; // adjusted estimate
}
function adjustEstimate(estimate: TaskEstimate): number {
let buffer = 1.0;
// risk buffer
if (estimate.risk === 'medium') buffer *= 1.3;
if (estimate.risk === 'high') buffer *= 1.5;
// uncertainty buffer
buffer *= (1 + estimate.uncertainty);
return Math.ceil(estimate.baseEstimate * buffer);
}
// Example
const task = {
baseEstimate: 5,
risk: 'medium',
uncertainty: 0.2 // 20% uncertainty
};
const final = adjustEstimate(task); // 5 * 1.3 * 1.2 = 7.8 → 8 points
Output format
Estimation document template
## Task: [Task Name]
### Description
[work description]
### Acceptance Criteria
- [ ] Criterion 1
- [ ] Criterion 2
- [ ] Criterion 3
### Estimation
- **Story Points**: 5
- **T-Shirt Size**: M
- **Estimated Time**: 1-2 days
### Breakdown
- Frontend UI: 2 points
- API Endpoint: 2 points
- Testing: 1 point
### Risks
- Uncertain API response time (medium risk)
- External library dependency (low risk)
### Dependencies
- User authentication must be completed first
### Notes
- Need to discuss design with UX team
Constraints
Required rules (MUST)
- Relative estimation: Relative complexity instead of absolute time
- Team consensus: Agreement from the whole team, not individuals
- Use historical data: Plan based on velocity
Prohibited (MUST NOT)
- Pressuring individuals: Estimates are not promises
- Overly granular estimation: Split anything 13+ points
- Turning estimates into deadlines: estimate ≠ commitment
Best practices
- Break Down: Split big work into smaller pieces
- Reference Stories: Reference similar past work
- Include buffer: Prepare for the unexpected
References
Metadata
Version
- Current version: 1.0.0
- Last updated: 2025-01-01
- Compatible platforms: Claude, ChatGPT, Gemini
Tags
#estimation #agile #story-points #planning-poker #sprint-planning #project-management
Examples
Example 1: Basic usage
Example 2: Advanced usage
Quick Start
Unity3D 스프린트 스토리 추정 시나리오 (bmad-gds 연동):
## Sprint 3 Story Estimation (Unity3D)
### Story: 플레이어 대시 능력 구현
bmad-gds 컨텍스트:
- GDD 참조: "대시 쿨다운 1.5초, 무적 프레임 10f"
- 기술 스택: C# MonoBehaviour, Physics2D, InputSystem
Story Point 산정:
- 기본 대시 이동 로직: 3점 (C# + Physics2D)
- 쿨다운 시스템: 2점 (TimerManager 연동)
- 무적 프레임 + 레이어 마스크: 3점 (충돌 처리 복잡)
- 이펙트 연동 (ParticleSystem): 2점
- 유닛 테스트 작성: 1점
합계: 11점 → 분리 권장 (13점 미만)
리스크:
- Physics2D 상호작용 예측 어려움 (medium risk) → x1.3
- InputSystem 레거시 충돌 가능 (low risk)
최종 추정: 8점 (분리 후 1차 구현)
→ bmad-gds-sprint-planning에 전달
Workflow Context
Unity3D 스토리 복잡도를 추정하고 스프린트 용량을 계획합니다.
- 트리거: JEO Workflow 2 PLAN 단계, bmad-gds-sprint-planning 전
- 연동:
task-estimation→bmad-gds-sprint-planning→bmad-gds-create-story
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