triz-analysis

name	triz-analysis
description	Run a systematic TRIZ contradiction audit against a Rust codebase, architecture, or workflow to identify hidden trade-offs and innovation opportunities. Use when facing design trade-offs, contradictory requirements, or needing to identify innovation opportunities through systematic contradiction analysis. Triggers: 'TRIZ audit', 'contradiction analysis', 'innovation audit', 'trade-off analysis', 'hidden trade-offs'.
category	analysis
license	MIT
metadata	{"author":"d-oit","version":"0.2.10","adapted-from":"d-o-hub/github-template-ai-agents","tags":"triz analysis innovation contradiction rust architecture audit"}

TRIZ Analysis — Rust Edition

Systematic innovation audit for Rust codebases, workspace architectures, and CI/CD pipelines.

When to Use

• Auditing a Rust workspace for technical contradictions
• Reviewing scripts/, CI pipelines, or Cargo.toml manifests for hidden trade-offs
• Analyzing an architecture for scalability vs. complexity bottlenecks
• Performing a swarm-based TRIZ audit on a Rust project
• Reviewing unsafe boundaries, async vs. sync, or tokio::spawn vs. spawn_blocking choices

Input Requirements

• Target Scope: The specific directory, pipeline, or framework to analyze (e.g., crates/, scripts/, .github/workflows/, agent-coordination).
• Language Focus: Rust-specific patterns (ownership, async, traits, lifetimes).

Output Convention

All agent-generated analysis must be written to analysis/ using:

analysis/triz-<scope>-YYYY-MM-DD.md

Example: analysis/triz-scripts-2026-06-18.md

Audit Process

1. SCOPE SCAN: Examine the target scope for existing pain points or trade-offs.
2. CONTRADICTION DISCOVERY: Identify technical contradictions: "Improving [X] in this scope causes [Y] to worsen."
3. PRINCIPLE MAPPING: Map discovered contradictions to TRIZ inventive principles.
4. INNOVATION ROADMAP: Propose specific Rust-idiomatic changes based on TRIZ resolutions.
5. REPORT: Document findings in analysis/.

Core Protocol

Contradiction-First Approach

1. SCAN the scope
2. IDENTIFY contradiction: "Improving [X] causes [Y] to worsen"
3. CHECK if contradiction is real or apparent
4. RESOLVE using separation principles
5. DOCUMENT findings in analysis/

Ideal Final Result (IFR) for Rust Audits

"The ideal Rust system performs its function with zero unsafe, zero clones, zero contention"

1. What is the ideal outcome for this scope?
2. What prevents reaching it? (current type/ownership/CI constraints)
3. Which constraints are real vs assumed?
4. Could the borrow checker enforce correctness instead of runtime checks?

Contradiction Matrix (Rust-Specific)

Improving	vs Worsening	→ Principle	Rust Pattern
Throughput	vs Latency	#7, #13, #17	Batching, parking_lot::RwLock, lock-free channels
API ergonomics	vs Binary size	#1, #15	Feature flags, #[cfg], trait-based DI
Compile time	vs Runtime perf	#13, #35	LTO off, cargo-bloat profile tuning
Safety	vs Performance	#12, #4	unsafe minimization, scoped SIMD
Genericity	vs Compile time	#2, #6	Trait specialization, sealed traits
Async surface	vs Blocking cost	#1, #15	spawn_blocking, tokio::task::yield_now
Build matrix	vs CI minutes	#1, #9	cargo-hack, workspace inheritance
Test coverage	vs Test runtime	#13, #35	cargo-nextest sharding, proptest shrinking

Software Contradiction Matrix (General)

Improving	vs Worsening	→ Principle
Functionality	vs Complexity	#1, #9, #15
Performance	vs Maintainability	#7, #13, #17
Flexibility	vs Simplicity	#6, #2, #3
Security	vs Usability	#12, #4, #17
Scalability	vs Resource Cost	#1, #13, #35

Separation Principles (Rust Mapping)

Strategy	When	Rust Pattern
Time	Different behavior at stages	Lifecycle generics, OnceCell, Phased init
Space	Different behavior in context	Crate features, cfg flags, target_arch
Condition	Different by input	Trait objects, sealed traits, match
System-level	New component resolves	Newtype wrapper, sidecar crate, separate binary

Integration with Other Skills

• agent-coordination: Orchestrate as a swarm sub-task where multiple agents analyze different crates or pipelines in parallel.
• task-decomposition: Use to break a large workspace audit into smaller scoped TRIZ analyses.
• anti-ai-slop: Apply after TRIZ resolutions to keep the rewrite idiomatic and not boilerplate-heavy.

Quality Checklist

• Target scope clearly defined
• Discovered contradictions explicitly stated
• Recommendations mapped to TRIZ inventive principles
• Rust-idiomatic pattern suggested (not just generic advice)
• Findings saved to analysis/triz-<scope>-YYYY-MM-DD.md

Rationalizations

Rationalization	Reality
"This Rust code compiles, no contradictions exist"	Compilation proves type safety, not design trade-offs. Many crates have hidden coupling or unsafe audit gaps.
"TRIZ is too theoretical for Rust"	TRIZ principles map directly to Rust patterns: segmentation = crate split, taking out = extract trait, asymmetry = PhantomData.
"Just run clippy, that catches everything"	Clippy catches idiomatic violations; TRIZ catches architectural contradictions clippy cannot see.

Red Flags

• Skipping the contradiction statement and jumping straight to solutions
• Defining contradictions too vaguely to map to specific TRIZ principles
• Not saving findings to analysis/ as specified
• Proposing non-idiomatic Rust (e.g., dynamic dispatch where static would do)

Reference Files

• references/principles.md - All 40 TRIZ principles with software examples
• references/patterns.md - Common software contradiction patterns and resolutions
• references/evolution.md - TRIZ evolution trends for system design
• The Rust Performance Book
• Rust API Guidelines

Related Skills

• triz-solver - Apply TRIZ principles to solve specific problems
• task-decomposition - Break audits into scoped sub-tasks
• goap-agent - Use TRIZ in Phase 1 (Analyze) of GOAP
• anti-ai-slop - Audit rewritten code for boilerplate and over-abstraction