Nm Tome Triz

v1.0.0

Apply TRIZ cross-domain analogical reasoning to find solutions from adjacent fields

⭐ 0· 95·1 current·1 all-time

by@athola

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for athola/nm-tome-triz.

Previewing Install & Setup.

Prompt PreviewInstall & Setup

Install the skill "Nm Tome Triz" (athola/nm-tome-triz) from ClawHub.
Skill page: https://clawhub.ai/athola/nm-tome-triz
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install nm-tome-triz

ClawHub CLI

Package manager switcher

npx clawhub@latest install nm-tome-triz

Security Scan

Capability signals

Crypto

These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.

VirusTotal

Benign

View report →

OpenClaw

Benign

high confidence

✓

Purpose & Capability

Name, description, and content all describe applying TRIZ-style cross-domain analogies; the skill requests no binaries, env vars, or installs that would be disproportionate to that goal.

✓

Instruction Scope

SKILL.md stays on-topic: it instructs the agent to abstract problems, identify contradictions, map fields (mentions Semantic Scholar's taxonomy), and search for analogues. It does not instruct the agent to read unrelated files, exfiltrate data, or require credentials. Note: it suggests using external literature/search resources but does not require or configure any specific API keys.

✓

Install Mechanism

No install spec and no code files — instruction-only. This has the lowest risk surface because nothing is downloaded or written to disk by the skill itself.

✓

Credentials

The skill declares no environment variables, secrets, or config paths. There are no disproportionate credential or system-access requests relative to the stated purpose.

✓

Persistence & Privilege

always:false and default autonomous invocation settings are used. The skill does not request permanent presence or modification of other skills or system-wide settings.

Assessment

This is an instruction-only TRIZ helper that asks the agent to reason by analogy and (optionally) consult literature taxonomies like Semantic Scholar. It does not request credentials or install code. If you rely on it to query external databases, confirm your agent has appropriate, trusted web/search capabilities and be aware it may use public web searches to find analogues. If you want it to use a specific API (e.g., Semantic Scholar) you should provide and vet any API keys separately before enabling such behavior.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🦞 Clawdis

latestvk9793b3an2x79fr8wm0xbp7w1d858tjp

95downloads

0stars

1versions

Updated 6d ago

v1.0.0

MIT-0

Night Market Skill — ported from claude-night-market/tome. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

TRIZ Cross-Domain Analysis

When To Use

Stuck on a problem and need perspectives from other domains
Exploring cross-domain analogies for inventive solutions

When NOT To Use

Standard code search or literature review (use other tome channels)
Problems with obvious, well-known solutions

Apply Altshuller's Theory of Inventive Problem Solving to find solutions from adjacent fields.

Depth Levels

Depth	Fields	Analysis
light	1	Contradiction only
medium	2	Contradiction + field mapping
deep	3	Full matrix + principles
maximum	5	Distant fields + full TRIZ

Workflow

Abstract the problem into TRIZ formulation
Identify technical contradiction
Map to adjacent fields using Semantic Scholar's field taxonomy
Search for solved analogues in those fields
Build bridge mappings with rationale

Field Mapping Strategy

Software architecture: civil engineering, biology
Data structures: logistics, materials science
Algorithms: operations research, genetics
Security: military strategy, immunology
Financial: game theory, ecology

Comments

Loading comments...