Agent Skills: TRIZ Skill

|

UncategorizedID: thepexcel/agent-skills/triz

Install this agent skill to your local

pnpm dlx add-skill https://github.com/ThepExcel/agent-skills/tree/HEAD/triz

Skill Files

Browse the full folder contents for triz.

Download Skill

Loading file tree…

triz/SKILL.md

Skill Metadata

Name
triz
Description
|

TRIZ Skill

Systematic innovation via Theory of Inventive Problem Solving. AI-enhanced.

Problem Routing

| Problem Type | Tool | Reference | |-------------|------|-----------| | "Improve A but B worsens" | Contradiction Matrix | 40-principles.md | | "Need opposite properties" | Separation Principles | Below | | "System not working" | Su-Field Analysis | advanced.md | | "How will tech evolve?" | Evolution Trends | advanced.md | | "What do others do?" | FOS (cross-industry) | ai-prompts.md | | "Very complex problem" | ARIZ Algorithm | ai-prompts.md |

6-Step Process

1. DEFINE IFR    → "The [system] ITSELF [does X] WITHOUT [cost/harm]"
2. IDENTIFY      → What contradiction? (Technical or Physical)
3. MAP           → Which of 39 parameters? [39-parameters.md]
4. RETRIEVE      → Matrix suggests which principles?
5. GENERATE      → Apply each principle specifically
6. EVALUATE      → Feasibility? Implementation?

Step 1: Ideal Final Result (IFR)

"The [object] ITSELF [performs function] WITHOUT [cost/harm/complexity]"

Formula: Ideality = Benefits / (Cost + Harm)

Examples:

  • "The pipe itself prevents leaks" (not: add sensors)
  • "The code itself fixes bugs" (not: add more tests)

Step 2: Identify Contradiction

Technical: Improving A worsens B

"If we [improve A], then [B gets worse]"
→ ถ้าเราทำให้รถเร็วขึ้น, ประสิทธิภาพน้ำมันแย่ลง

Physical: Same element needs opposite properties

"[Element] must be [Property] for X AND [Opposite] for Y"
→ API ต้อง complex (power users) AND simple (beginners)

Step 3: Map to 39 Parameters

See 39-parameters.md. Common ones:

| # | Parameter | Software Equivalent | |---|-----------|---------------------| | 9 | Speed | Performance, latency | | 27 | Reliability | Uptime, MTBF | | 33 | Ease of operation | UX, usability | | 36 | Complexity | Code complexity | | 39 | Productivity | Throughput |

Step 4: Top 10 Principles

| # | Principle | Modern Example | |---|-----------|----------------| | 1 | Segmentation | Microservices | | 2 | Taking Out | Separation of concerns | | 10 | Preliminary Action | Caching | | 13 | The Other Way Round | Event-driven vs polling | | 15 | Dynamics | Adaptive algorithms | | 24 | Intermediary | Middleware, adapters | | 25 | Self-Service | Self-healing systems | | 35 | Parameter Changes | Transform data format |

Full list: 40-principles.md

Step 5: Physical Contradiction → Separation

| Separation | Strategy | Example | |------------|----------|---------| | In Time | Different times | Landing gear: extend/retract | | In Space | Different locations | Pencil: hard core, soft eraser | | In Condition | Different conditions | Smart glass: transparent/opaque | | In Scale | Different levels | Water: liquid macro, molecules nano |

Creative Mode: FOS/MOS

Function Oriented Search (FOS): Find how OTHER industries solve same function.

1. ABSTRACT → "Remove ice" → "Separate materials"
2. SEARCH → Find 5+ industries with similar function
3. TRANSFER → Adapt mechanism to your problem

Method Oriented Search (MOS): Apply known method to NEW domains.

See ai-prompts.md for detailed prompts.

Output Format

## Problem: [Restated]

## IFR: "The [system] itself [does X] without [cost/harm]"

## Contradiction:
- Type: Technical / Physical
- Improving: Parameter #__
- Worsening: Parameter #__

## Principles: [#, #, #]

## Solutions:
### Principle #X: [Name]
- Application: [How]
- Idea: [Concrete solution]
- Feasibility: High/Medium/Low

## Next Steps:
1. [Prototype which solution]
2. [Validation approach]

References

| Type | File | Content | |------|------|---------| | Core | 40-principles.md | All 40 principles + examples | | Core | 39-parameters.md | All 39 parameters | | Advanced | advanced.md | Su-Field, 76 Standards, ARIZ, Evolution | | AI | ai-prompts.md | Ready-to-use prompt templates | | AI | methodology.md | TRIZ + LLM integration | | Examples | examples.md | Case studies (Samsung, SpaceX, Netflix) |

Related Skills

  • /generate-creative-ideas — Complement with broader brainstorming
  • /deep-research — Research cross-industry solutions (FOS/MOS)
  • /boost-intel — Evaluate trade-offs systematically
  • /problem-solving — Structure the problem before applying TRIZ