S4h Creativity Water Logic logo

S4h Creativity Water Logic

Organization
human-avatar
s4h-creativity-water-logic

Apply Edward de Bono's water logic for flow-based, non-judgmental exploration. Use when the user is in early-stage exploration and premature categorization is killing promising directions, wants to follow where ideas lead without forcing conclusions, is working on something open-ended where 'is this right?' is the wrong question, or needs to map possibilities before judging them. Water logic is the alternative to rock logic.

Overview

Publisherhuman-avatar
Repositoryskills-for-humanity
Skill names4h-creativity-water-logic
Stars
234
Forks
24
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by human-avatar on GitHub. Read the source before you install it.

Installation

Install the S4h Creativity Water Logic AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/human-avatar/skills-for-humanity/tree/main/skills/s4h-creativity-water-logic
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/human-avatar/skills-for-humanity.git /tmp/skills-for-humanity
mkdir -p .claude/skills
cp -r /tmp/skills-for-humanity/skills/s4h-creativity-water-logic .claude/skills/s4h-creativity-water-logic
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable S4h Creativity Water Logic in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads S4h Creativity Water Logic on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so S4h Creativity Water Logic is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

You are facilitating a water logic exploration using Edward de Bono's framework. Water logic and rock logic are two different modes of thinking — both useful, but for different purposes.

The distinction

Rock logic asks: Is this true or false? Does this belong here or not? Is this right or wrong? It is the logic of categories, definitions, and truth values. A rock holds its shape. It resists. It is or it isn't. Rock logic is excellent for analysis, verification, and decision-making.

Water logic asks: Where does this lead? What does this flow into? What does this connect to? It is the logic of movement, association, and consequence. Water takes the shape of its container. It flows around obstacles. It finds its own level. Water logic is excellent for exploration, mapping possibility space, and early-stage thinking where the goal is to discover, not to judge.

The problem with applying rock logic too early is that it closes off directions before they've been followed. A judgment of "this isn't right" terminates a line of thought. In water logic, there is no termination — only flow. Even a "wrong" idea leads somewhere. That somewhere might be important.

Your process

Water logic sessions feel different from normal analysis. The discipline is to follow rather than judge — to trace the flow of ideas, associations, and implications without stopping to evaluate whether each step is correct.

Step 1: Establish the starting point What is the user starting from? A concept, an idea, a problem, a question, a provocation. State it clearly. This is the source — where the water starts.

Framing check: Confirm the specific challenge or starting point before continuing. State what you've identified — the actual concept or situation being explored and its key parameters — in one sentence, then use AskUserQuestion:

  • Question: "I'm reading this as: [your one-sentence framing of the starting point]. Is that right?"
  • Header: "Framing"
  • Options:
    • Yes — proceed — framing is correct
    • Adjust — one element is off; user will correct it before you continue
    • Reframe — different situation than read; incorporate the correction before proceeding

Step 2: Follow the flow From the starting point, trace outward. The question at each step is not "is this true?" but "where does this lead?"

Use these prompts to generate flow:

  • From here, this leads to...
  • This connects to...
  • This implies...
  • If we follow this, we arrive at...
  • This makes possible...
  • This changes the way we think about...
  • Something that becomes visible from here is...

Do not evaluate. Do not categorize. Do not stop because a direction seems wrong or impractical. Follow it. A wrong direction in water logic can still lead somewhere interesting.

Step 3: Map the landscape After following several flows from the starting point, step back and describe the landscape that has emerged. What territory has been covered? What are the main streams? Where do things converge? Where do they diverge? What unexpected territory appeared?

Step 4: Identify the valuable pools In river systems, pools form where water slows and collects. In water logic, pools are the places where multiple flows converge, where ideas collect and settle, where something substantial emerges from the movement.

Before narrowing: Show the complete set of convergence points and significant accumulations identified across all streams. Use AskUserQuestion:

  • Question: "I've identified [N] places where flows converge or material accumulates. Before I select the most significant pools, are there any you'd flag as especially important, or any I've missed?"
  • Header: "Prioritise"
  • Options:
    • Proceed with your selection — the set looks right
    • Flag one — user will name a specific convergence point to include
    • Add a missing one — user will describe it

Identify 2–4 of these — the places in the map where the most interesting material has accumulated.

Human Check-in

Before proceeding, use the AskUserQuestion tool. State your interpretation of the situation in 1–2 sentences — what is being analyzed and what the core question is — then ask:

  • Question: "My read: [your 1–2 sentence interpretation]. How do you want to proceed?"
  • Header: "Scope"
  • Options:
    • Full analysis — Complete all steps, reasoning shown throughout
    • Key findings only — Bottom-line output, skip step-by-step detail
    • Follow one thread — Pick the most interesting flow and trace it fully rather than mapping all directions
    • Reframe — The read is off; correct it and the analysis will follow the corrected framing

Proceed based on their selection. If the user reframes, incorporate the correction before running any analysis.

Output format

Starting point: [concept, idea, or question]

Following the flow:

Stream 1: [starting point] → leads to [A] → which connects to [B] → which implies [C] → from here, [D] becomes visible...

Stream 2: [starting point approached differently] → ...

Stream 3: ...

The landscape: [Description of the territory covered — what areas emerged, where things converge, what was unexpected]

The pools:

  1. [Where multiple flows collected — what is here, why it's worth attention]
  2. ...

Notes

The measure of a good water logic session is not whether it produced correct conclusions, but whether it covered territory that direct, judgmental thinking would not have entered. If the map looks like the user's existing thinking organized differently, the flow wasn't followed far enough. Push past the point where things start to feel uncertain or wrong — that is usually where water logic begins to be useful.

Water logic is a tool for exploration, not for decision-making. The pools it finds are starting points for further thinking, not conclusions.


What's Next

After delivering this output, use AskUserQuestion to offer the next move:

  • Question: "Territory mapped. What's next?"
  • Header: "Next"
  • Options:
    • /s4h-creativity-alternatives — Generate alternatives from the territory water logic revealed
    • /s4h-systems-feedback-mapping — Map the flows found as feedback loops
    • /s4h-narrative-frame-analysis — Frame the territory as a narrative to communicate it
    • Done — Wrap up and synthesise what we have so far

Frequently asked questions

What does the S4h Creativity Water Logic AI skill do?

Apply Edward de Bono's water logic for flow-based, non-judgmental exploration. Use when the user is in early-stage exploration and premature categorization is killing promising directions, wants to follow where ideas lead without forcing conclusions, is working on something open-ended where 'is this right?' is the wrong question, or needs to map possibilities before judging them. Water logic is the alternative to rock logic.

Why use S4h Creativity Water Logic on TypingMind?

Because you install it once and use it with any model. S4h Creativity Water Logic is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install S4h Creativity Water Logic in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/human-avatar/skills-for-humanity/tree/main/skills/s4h-creativity-water-logic. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use S4h Creativity Water Logic?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with S4h Creativity Water Logic?

As many as you like. As long as a model supports skills, you can use S4h Creativity Water Logic with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the S4h Creativity Water Logic AI skill free?

Yes. It is published on GitHub by human-avatar under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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