problem-solving
Universal sequential thinking patterns for complex problem analysis
When & Why to Use This Skill
This Claude skill provides a universal sequential thinking framework designed for structured problem analysis and solution development. It enables agents to tackle complex, cross-domain challenges by applying systematic patterns such as decomposition, abstraction, and analogy, ensuring that every step of the reasoning process is documented and verifiable.
Use Cases
- Complex System Decomposition: Breaking down large-scale technical or business problems into smaller, manageable components like UI, logic, and data layers.
- Cross-Domain Problem Solving: Utilizing abstraction to identify core principles and applying analogies from known solutions to solve novel challenges in unfamiliar fields.
- Strategic Decision Documentation: Recording architectural choices and the underlying reasoning to build a reusable organizational knowledge base and decision trail.
- Systematic Hypothesis Testing: Implementing a multi-step verification process to test assumptions and validate solutions during the development or debugging phase.
| name | problem-solving |
|---|---|
| description | Universal sequential thinking patterns for complex problem analysis |
| license | MIT |
| compatibility | opencode |
| related_knowledge_management | For storing problem-solving insights, use skill `knowledge-management` |
| related_issue_tracking | For tracking problem-solving tasks, use skill `issue-tracking` |
Problem Solving
What I Do
Provide universal patterns for structured problem analysis and solution development that work across different domains and projects.
Universal Problem-Solving Framework
Sequential Thinking Process
# Universal problem-solving workflow
from sequential_thinking import sequential_thinking
result = sequential_thinking(
thought="Analyze the problem from multiple angles",
nextThoughtNeeded=True,
thoughtNumber=1,
totalThoughts=5,
isRevision=False
)
Universal Thought Patterns
Analysis Patterns:
- Decomposition: Break problems into smaller components
- Abstraction: Identify core principles independent of implementation
- Analogy: Find similar problems with known solutions
- Verification: Test hypotheses systematically
Cross-Domain Examples
# Universal problem analysis
thoughts = [
{
"thought": "Identify core requirements independent of technology",
"type": "abstraction"
},
{
"thought": "Break into UI, logic, and data components",
"type": "decomposition"
},
{
"thought": "Compare with similar authentication systems",
"type": "analogy"
}
]
When to Use Me
Use this skill when:
- Analyzing complex, cross-domain problems
- Creating reusable solution patterns
- Standardizing problem-solving approaches
- Building organizational problem-solving frameworks
Universal Integration
Decision Documentation
# Universal decision recording
store_memory(
type="decision",
title="Universal architecture choice",
content="Chose X over Y because of Z reasons",
tags=["architecture", "decision", "universal"],
relationships=["ADDRESSES:problem-123"]
)
Pattern Extraction
# Universal pattern extraction
if solution_is_reusable:
store_memory(
type="code_pattern",
title="Universal solution pattern",
content="Reusable code and explanation",
tags=["pattern", "universal", domain_tags]
)
Best Practices
- Standardization: Use consistent thought patterns across projects
- Documentation: Record all major decisions and insights
- Reusability: Extract patterns from specific solutions
- Collaboration: Share problem-solving approaches across teams
Compatibility
Works with:
- Any complex problem domain
- Cross-project knowledge systems
- Organizational learning frameworks
- Universal solution libraries