
decomposition-reconstruction
Breaks complex systems into atomic components, maps their relationships, and reconstructs them in optimized configurations to identify bottlenecks, critical failure points, and redesign opportunities. Use when dealing with complex systems that need simplification, identifying bottlenecks or critical failure points, redesigning architecture or processes for better performance, breaking down problems that feel overwhelming, analyzing dependencies to understand ripple effects, or when optimization requires understanding how parts interact.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/lyndonkl/claude --skill decomposition-reconstruction- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads decomposition-reconstruction automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Decomposition & Reconstruction
Workflow
Copy this checklist and track your progress:
Decomposition & Reconstruction Progress:
- [ ] Step 1: Define the system and goal
- [ ] Step 2: Decompose into components and relationships
- [ ] Step 3: Analyze component properties and interactions
- [ ] Step 4: Reconstruct for insight or optimization
- [ ] Step 5: Validate and deliver recommendations
Step 1: Define the system and goal
Ask user to describe the system (what are we analyzing), current problem or goal (what needs improvement, understanding, or redesign), boundaries (what's in scope vs out of scope), and success criteria (what would "better" look like). Clear boundaries prevent endless decomposition. See Scoping Questions for clarification prompts.
Step 2: Decompose into components and relationships
Break system into atomic parts that can't be meaningfully subdivided further. Identify relationships (dependencies, data flow, control flow, temporal ordering). Choose decomposition strategy based on system type. See Decomposition Strategies and resources/template.md for structured process.
Step 3: Analyze component properties and interactions
For each component, identify key properties (cost, time, complexity, reliability, etc.). Map interactions (which components depend on which). Identify critical paths, bottlenecks, or vulnerable points. For complex analysis → See resources/methodology.md for dependency mapping and critical path techniques.
Step 4: Reconstruct for insight or optimization
Based on goal, either: (a) Identify critical components (bottleneck, single point of failure, highest cost driver), (b) Redesign configuration (reorder, parallelize, eliminate, combine components), or (c) Simplify (remove unnecessary components). See Reconstruction Patterns for common approaches.
Step 5: Validate and deliver recommendations
Self-assess using resources/evaluators/rubric_decomposition_reconstruction.json (minimum score ≥ 3.5). Present decomposition-reconstruction.md with clear component breakdown, analysis findings (bottlenecks, dependencies), and actionable recommendations with expected impact.
Scoping Questions
To define the system:
- What is the system we're analyzing? (Be specific: "checkout flow" not "website")
- Where does it start and end? (Boundaries)
- What's in scope vs out of scope? (Prevents endless decomposition)
To clarify the goal:
- What problem are we solving? (Slow performance, high cost, complexity, unreliability)
- What would success look like? (Specific target: "reduce latency to <500ms", "cut costs by 30%")
- Are we optimizing, understanding, or redesigning?
To understand constraints:
- What can't we change? (Legacy systems, budget limits, regulatory requirements)
- What's the time horizon? (Quick wins vs long-term redesign)
- Who are the stakeholders? (Engineering, business, customers)
Decomposition Strategies
Choose based on system type:
Functional Decomposition
When: Business processes, software features, workflows Approach: Break down by function or task Example: E-commerce checkout → Browse products | Add to cart | Enter shipping | Payment | Confirmation
Structural Decomposition
When: Architecture, organizations, physical systems Approach: Break down by component or module Example: Web app → Frontend (React) | API (Node.js) | Database (PostgreSQL) | Cache (Redis)
Data Flow Decomposition
When: Pipelines, ETL processes, information systems Approach: Break down by data transformations Example: Analytics pipeline → Ingest raw events | Clean & validate | Aggregate metrics | Store in warehouse | Visualize in dashboard
Temporal Decomposition
When: Processes with sequential stages, timelines, user journeys Approach: Break down by time or sequence Example: Customer onboarding → Day 1: Signup | Day 2-7: Tutorial | Day 8-30: First value moment | Day 31+: Retention
Cost/Resource Decomposition
When: Budget analysis, resource allocation, optimization Approach: Break down by cost center or resource type Example: AWS bill → Compute ($5K) | Storage ($2K) | Data transfer ($1K) | Other ($500)
Depth guideline: Stop decomposing when further breakdown doesn't reveal useful insights or actionable opportunities.
Component Relationship Types
After decomposition, map relationships:
1. Dependency (A requires B):
- API service depends on database
- Frontend depends on API
- Critical for: Identifying cascading failures, understanding change impact
2. Data flow (A sends data to B):
- User input → Validation → Database → API response
- Critical for: Tracing information, finding transformation bottlenecks
3. Control flow (A triggers B):
- Button click triggers form submission
- Payment success triggers order fulfillment
- Critical for: Understanding execution paths, identifying race conditions
4. Temporal ordering (A before B in time):
- Authentication before authorization
- Compile before deploy
- Critical for: Sequencing, finding parallelization opportunities
5. Resource sharing (A and B compete for C):
- Multiple services share database connection pool
- Teams share budget
- Critical for: Identifying contention, resource constraints
Reconstruction Patterns
Pattern 1: Bottleneck Identification
Goal: Find what limits system throughput or speed Approach: Measure component properties (time, cost, capacity), identify critical path or highest value Example: DB query takes 80% of request time → Optimize DB query first
Pattern 2: Simplification
Goal: Reduce complexity by removing unnecessary parts Approach: Question necessity of each component, eliminate redundant or low-value parts Example: Workflow has 5 approval steps, 3 are redundant → Remove 3 steps
Pattern 3: Reordering
Goal: Improve efficiency by changing sequence Approach: Identify dependencies, move independent tasks earlier or parallel Example: Run tests parallel to build instead of sequential → Reduce CI time
Pattern 4: Parallelization
Goal: Increase throughput by doing work concurrently Approach: Find independent components, execute simultaneously Example: Fetch user data and product data in parallel instead of serial → Cut latency in half
Pattern 5: Substitution
Goal: Replace weak component with better alternative Approach: Identify underperforming component, find replacement Example: Replace synchronous API call with async message queue → Improve reliability
Pattern 6: Consolidation
Goal: Reduce overhead by combining similar components Approach: Find redundant or overlapping components, merge them Example: Consolidate 3 microservices doing similar work into 1 → Reduce operational overhead
Pattern 7: Modularization
Goal: Improve maintainability by separating concerns Approach: Identify tightly coupled components, separate with clear interfaces Example: Extract auth logic from monolith into separate service → Enable independent scaling
When NOT to Use This Skill
Skip decomposition-reconstruction if:
- System is already simple (3-5 obvious components, no complex interactions)
- Problem is not about system structure (purely execution issue, not design issue)
- You need creativity/ideation (not analysis) - use brainstorming instead
- System is poorly understood (need discovery/research first, not decomposition)
- Changes are impossible (no point analyzing if you can't act on findings)
Use instead:
- Simple system → Direct analysis or observation
- Execution problem → Project management, process improvement
- Need ideas → Brainstorming, design thinking
- Unknown system → Discovery interviews, research
- Unchangeable → Workaround planning, constraint optimization
Common Patterns by Domain
Software Architecture:
- Decompose: Modules, services, layers, data stores
- Reconstruct for: Microservices migration, performance optimization, reducing coupling
Business Processes:
- Decompose: Steps, decision points, handoffs, approvals
- Reconstruct for: Cycle time reduction, automation opportunities, removing waste
Problem Solving:
- Decompose: Sub-problems, dependencies, unknowns, constraints
- Reconstruct for: Task sequencing, identifying blockers, finding parallelizable work
Cost Optimization:
- Decompose: Cost centers, line items, resource usage
- Reconstruct for: Identifying biggest cost drivers, finding quick wins
User Experience:
- Decompose: User journey stages, interactions, pain points
- Reconstruct for: Simplifying flows, removing friction, improving conversion
System Reliability:
- Decompose: Components, failure modes, dependencies
- Reconstruct for: Identifying single points of failure, improving resilience
Quick Reference
Process:
- Define system and goal → Set boundaries
- Decompose → Break into components and relationships
- Analyze → Measure properties, map interactions
- Reconstruct → Optimize, simplify, or redesign
- Validate → Check against rubric, deliver recommendations
Decomposition strategies:
- Functional (by task), Structural (by component), Data flow, Temporal, Cost/Resource
Reconstruction patterns:
- Bottleneck ID, Simplification, Reordering, Parallelization, Substitution, Consolidation, Modularization
Resources:
- resources/template.md - Structured decomposition process with templates
- resources/methodology.md - Advanced techniques (dependency graphs, critical path analysis, hierarchical decomposition)
- resources/evaluators/rubric_decomposition_reconstruction.json - Quality checklist
Deliverable: decomposition-reconstruction.md with component breakdown, analysis, and recommendations
FAQ
What does the decomposition-reconstruction skill do?
Breaks complex systems into atomic components, maps their relationships, and reconstructs them in optimized configurations to identify bottlenecks, critical failure points, and redesign opportunities. Use when dealing with complex systems that need simplification, identifying bottlenecks or critical failure points, redesigning architecture or processes for better performance, breaking down problems that feel overwhelming, analyzing dependencies to understand ripple effects, or when optimization requires understanding how parts interact.
How do I install decomposition-reconstruction?
Run npx skills add https://github.com/lyndonkl/claude --skill decomposition-reconstruction in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/decomposition-reconstruction/ (personal) or .claude/skills/decomposition-reconstruction/ (project).
Which AI agents can use decomposition-reconstruction?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is decomposition-reconstruction safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains decomposition-reconstruction?
It is published by lyndonkl in lyndonkl/claude. It has 96 recorded installs.
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