task-decomposition
Task Decomposition breaks down large, complex projects into small, independently completable units with clear success criteria and dependency mappings. Use this skill when addressing requests to plan projects, decompose features, create subtasks, split work, or organize large tasks into step-by-step plans. It applies vertical slicing, horizontal layering, workflow decomposition, and component decomposition techniques to ensure each atomic task takes a few hours and has a clear definition of done.
git clone --depth 1 https://github.com/rohitg00/skillkit /tmp/task-decomposition && cp -r /tmp/task-decomposition/packages/core/src/methodology/packs/planning/task-decomposition ~/.claude/skills/task-decompositionSKILL.md
# Task Decomposition
You are breaking down a complex task into smaller, atomic units. Each unit should be independently completable and verifiable.
## Core Principle
**If a task feels too big, it is too big. Break it down until each piece is obvious.**
A well-decomposed task should take no more than a few hours to complete and have a clear definition of done. Aim for tasks that are small, independent, testable, and clearly scoped.
## Decomposition Techniques
### 1. Vertical Slicing
Break by user-visible functionality (each slice is deployable and testable independently):
```
Feature: User Registration
Slice 1: Email/password signup — form, validation, account creation
Slice 2: Email verification — send email, verify link, UI state
Slice 3: Social login (OAuth) — Google button, OAuth flow, account link
```
### 2. Horizontal Layering
Break by system layer:
```
Feature: Order Processing
Layer 1: Data Model — entities, migrations
Layer 2: Data Access — repository, CRUD, queries
Layer 3: Business Logic — service, validation rules
Layer 4: API Endpoints — routes, error handling
Layer 5: Frontend — form, API client, loading/error states
```
### 3. Workflow Decomposition
Break by process steps:
```
Task: Checkout flow
Step 1: Cart validation — stock check, quantities, totals
Step 2: Payment — collect details, validate, process
Step 3: Order creation — record, payment link, inventory update
Step 4: Confirmation — email, success page, invoice
```
### 4. Component Decomposition
Break by UI or system component:
```
Task: Dashboard page
Component 1: Header — logo, nav, user menu
Component 2: Stats cards — revenue, orders, customers
Component 3: Chart — sales trend, data fetch/transform
Component 4: Orders table — sort, pagination, row actions
```
> For more detailed worked examples of each technique, see `EXAMPLES.md`.
## Task Template
For each decomposed task, define:
```markdown
## Task: [Brief Title]
**Description:**
[What needs to be done in 1-2 sentences]
**Files to Create/Modify:**
- [ ] path/to/file1.ts
- [ ] path/to/file2.ts
**Steps:**
1. [First specific step]
2. [Second specific step]
3. [Third specific step]
**Done When:**
- [ ] [Success criterion 1]
- [ ] [Success criterion 2]
- [ ] Tests pass
**Dependencies:**
- Requires: [Other task if any]
- Blocks: [What this enables]
```
## Dependency Management
### Identify Dependencies
```
Task Graph:
[Data Model] ──┬──▶ [Repository]
│
└──▶ [API Types]
│
[Repository] ──────────▶ [Service]
│
[API Types] ──────────────────┤
▼
[API Endpoints]
```
### Minimize Dependencies
- Prefer tasks that can run in parallel
- Use interfaces to decouple dependencies
- Start with foundational tasks first
### Order by Dependencies
```
Phase 1 (No dependencies):
- Task A: Data model
- Task B: API type definitions
- Task C: UI component skeletons
Phase 2 (Depends on Phase 1):
- Task D: Repository (needs A)
- Task E: API client (needs B)
- Task F: UI logic (needs C)
Phase 3 (Depends on Phase 2):
- Task G: Service (needs D)
- Task H: Connected UI (needs E, F)
```
## Decomposition Checklist
For each task, verify:
- [ ] **Atomic?** — Can be done without interruption
- [ ] **Clear?** — Scope is unambiguous
- [ ] **Testable?** — Know when it's done
- [ ] **Independent?** — Minimal dependencies
- [ ] **Small?** — Less than half a day
## Integration with Other Skills
- Use **design-first** to understand the full scope before decomposing
- Use **verification-gates** to define checkpoints between phases
- Use **testing/red-green-refactor** to implement each taskManages work transitions between team members or agents by creating structured handoff documents, summarizing project status, documenting key decisions, blockers, and open questions, and generating onboarding briefs. Use when someone needs to hand off, hand over, or transition a project; pass work to another person or agent; brief a colleague taking over; prepare a shift change summary; or onboard someone mid-task. Produces ready-to-use handoff documents covering current status, next steps, known issues, technical context, and communication templates for both planned and unplanned transfers.
Coordinates parallel investigation threads to simultaneously explore multiple hypotheses or root causes across different system areas. Use when debugging production incidents, slow API performance, multi-system integration failures, or complex bugs where the root cause is unclear and multiple plausible theories exist; when serial troubleshooting is too slow; or when multiple investigators can divide root-cause analysis work. Provides structured phases for problem decomposition, thread assignment, sync points with Continue/Pivot/Converge decisions, and final report synthesis.
Performs a structured five-stage code review covering requirements compliance, correctness, code quality, testing, and security/performance. Each stage uses targeted checklists and categorized feedback (Blocker/Major/Minor/Nit) with actionable suggestions and rationale. Use when the user asks for code review, PR feedback, pull request review, or wants their code checked for bugs, style issues, or vulnerabilities — triggered by phrases like "review my code", "check this PR", "review my changes", "pull request review", or "code feedback".
Applies the scientific method to debugging by helping users form specific, testable hypotheses, design targeted experiments, and systematically confirm or reject theories to find root causes. Use when a user says their code isn't working, they're getting an error, something broke, they want to troubleshoot a bug, or they're trying to figure out what's causing an issue. Concrete actions include isolating failing components, forming and testing hypotheses, analyzing error messages, tracing execution paths, and interpreting test results to narrow down root causes.
Performs systematic root cause analysis to identify the true source of bugs, errors, and unexpected behavior through structured investigation phases — not just treating symptoms. Use when a user reports a bug, crash, error, or broken behavior and needs to debug, troubleshoot, or investigate why something is not working; especially for complex or intermittent issues across multiple components. Applies the Five Whys method, hypothesis-driven testing, stack trace analysis, git blame/log evidence gathering, and causal chain documentation to isolate and confirm root causes before applying any fix.
Applies systematic tracing and isolation techniques to pinpoint exactly where a bug originates in code. Use when a bug is hard to locate, code is not working as expected, an error or crash appears with unclear cause, a regression was introduced between recent commits, or you need to narrow down which component, function, or line is faulty. Covers binary search debugging, git bisect for regressions, strategic logging with [TRACE] patterns, data and control flow tracing, component isolation, minimal reproduction cases, conditional breakpoints, and watch expressions across TypeScript, SQL, and bash.
Creates and structures SKILL.md files for AI coding agents, including YAML frontmatter, trigger phrases, directive instructions, decision trees, code examples, and verification checklists. Use when the user asks to write a new skill, create a skill file, author agent capabilities, generate skill documentation, or define a skill template for Claude Code agents.
Guides the creation of technical design documents before writing code, producing architecture diagrams, data models, API interface definitions, implementation plans, and multi-option trade-off analyses. Use when the user asks to plan a feature, architect a system, design an API, explore implementation approaches, or requests a technical design or spec before coding — especially for complex features involving multiple components, ambiguous requirements, or significant architectural changes.