triz-solver

A software problem-solving method based on TRIZ, the Theory of Inventive Problem Solving, adapted for Rust engineering.

In plain words
What is it for?
Use it when designing Rust systems, refactoring workspaces, resolving borrow-checker or lifetime conflicts, improving agent instructions, or looking for solutions beyond trial and error.
Why use it?
It helps clarify the real problem and resolve trade-offs such as gaining performance while increasing complexity, or satisfying Rust's ownership rules without unnecessary workarounds.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/d-oit/rust-2026-template/triz-solver
Any agent
npx skills add d-oit/rust-2026-template --skill triz-solver
Clone the repo
git clone --depth 1 https://github.com/d-oit/rust-2026-template

Made for: Claude Code, Codex.

Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,121 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00059 $0.02121
Opus 5 $0.00030 $0.01060
Sonnet 5 $0.00012 $0.00424
Haiku 4.5 $0.00006 $0.00212

Measured 3d ago against content hash d3c1cdcebe09, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

triz-solver scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/triz-solver/SKILL.md · 239 lines

How it starts

The opening of the file, as written. The whole thing — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TRIZ Problem Solver — Rust Edition

Systematic innovation methodology for Rust engineering problems.

When to Use

  • Complex Rust problems with apparent trade-offs
  • System design contradictions (improving X worsens Y)
  • Architecture refactoring decisions in a workspace
  • Seeking innovative solutions beyond incremental improvement
  • Agent instruction optimization
  • Stuck on borrow-checker, lifetime, or trait-bound conflicts

Core Protocol

Contradiction-First Approach

1. STATE the problem in one sentence
2. IDENTIFY contradiction: "Improving [X] causes [Y] to worsen"
3. CHECK if contradiction is real or apparent
4. RESOLVE using separation principles
5. VALIDATE no new contradictions introduced

Ideal Final Result (IFR)

"The ideal Rust solution delivers all benefits with zero cost, zero unsafe, zero clones"

1. What is the ideal outcome? (no implementation details)
2. What prevents reaching it? (Rust constraints: ownership, lifetimes, traits)
3. Which constraints are real vs assumed?
4. Can the type system enforce correctness without runtime checks?

40 Inventive Principles (Software Edition)

Top 10 for Rust

# Principle Rust Analogy When to Apply
1 Segmentation Split crate, module, function Monolithic code, complex functions
2 Taking out Extract trait, separate mod Mixed responsibilities in one type
3 Local quality Domain-specific types (Url, UserId) Generic String everywhere
4 Asymmetry Feature-gated impls, sealed traits One-size-fits-all antipattern
5 Merging Batch operations, reduce round-trips Excessive function calls, I/O
6 Universality Shared trait, polymorphism Duplicate implementations
7 Nesting Cow, lifetime hierarchies Flat complex types
12 Inversion Pull-based deps, IoC, callbacks Current push approach failing
13 Dynamics Runtime config, feature flags, hot-reload Static rigid configurations
17 Another dimension Add newtype, wrapper, sidecar Impasse at current abstraction level

Read the full file on GitHub · 239 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 239 lines · 59 tokens per session scan A d3c1cdcebe09

Subscribe to this mod's changes

triz-solver is a skill published in the GitHub repository d-oit/rust-2026-template (10 stars, last pushed 3d ago), licensed MIT. It adds 59 tokens to every session and 2,121 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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