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Prism 3way

Community
Cranot
prism-3way

Three orthogonal analytical operations (WHERE/WHEN/WHY) + cross-operation synthesis. Each operation attacks the problem from a fundamentally different angle. The disagreements between the three ARE the valuable output. Works on any domain — code, business, strategy, design, text.

Overview

PublisherCranot
Repositorysuper-hermes
Skill nameprism-3way
Stars
504
Forks
31
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 Cranot on GitHub. Read the source before you install it.

Installation

Install the Prism 3way 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/Cranot/super-hermes/tree/master/skills/prism-3way
  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/Cranot/super-hermes.git /tmp/super-hermes
mkdir -p .claude/skills
cp -r /tmp/super-hermes/skills/prism-3way .claude/skills/prism-3way
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prism 3way 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 Prism 3way 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 Prism 3way 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.

Prism 3-Way — WHERE / WHEN / WHY + Synthesis

When to Use

Use when one angle is not enough and the artifact is not necessarily code — a business plan, a strategy doc, a research note, an architecture as well as a source file. Three fixed orthogonal operations run independently and are then cross-referenced, so it is the right choice when the user wants coverage and wants to know which findings are corroborated. For a single tailored lens use /prism-scan; for a self-designed pipeline use /prism-full.

You perform FOUR operations on the artifact. Each operation is independent — do NOT let earlier operations influence later ones. The synthesis at the end cross-references all three.

OPERATION 1: WHERE (Structural Archaeology)

Excavate the artifact layer by layer. Start at the surface (what's immediately visible), dig to the foundation (what everything rests on), then examine the sediment between layers.

For each layer: name what's visible, what it hides, and what it rests on. Find dead patterns — things that USED to matter but were replaced. Find fault lines — where layers from different eras meet badly. Derive the conservation law: what trade-off persists across ALL layers? Format: A × B = Constant.

OPERATION 2: WHEN (Temporal Simulation)

Run the artifact forward through 3-5 concrete cycles of change (maintenance, growth, evolution, external pressure). For each cycle:

  • What breaks?
  • What calcifies into permanent behavior that nobody questions?
  • What knowledge is lost?

After all cycles: what predictions became received wisdom without being validated? What new fragilities emerged that the original design couldn't anticipate? Derive the conservation law governing temporal evolution.

OPERATION 3: WHY (Structural Impossibility)

Identify three desirable properties this artifact simultaneously claims to provide. Prove these three properties CANNOT all coexist — show where maximizing any two forces sacrifice of the third.

Engineer an improvement that would fix the core tension. Prove the improvement recreates the problem at a deeper level. Engineer a second improvement. Derive the conservation law: the structural invariant that persists through every improvement attempt.

SYNTHESIS: Cross-Operation Integration

Now cross-reference all three operations. Classify findings as:

STRUCTURAL CERTAINTIES — findings that ALL three operations independently discovered (these are real):

STRONG SIGNALS — findings from 2 of 3 operations:

UNIQUE PERSPECTIVES — findings from only 1 operation that the other 2 are structurally incapable of seeing:

For each unique perspective, explain WHY the other operations missed it.

Derive the META-conservation law: what is the relationship between the three conservation laws you found? Are they the same law in different vocabularies, or genuinely different constraints?

End with: the ONE insight that could ONLY emerge from the three-way integration — something no single analysis could produce alone.

Frequently asked questions

What does the Prism 3way AI skill do?

Three orthogonal analytical operations (WHERE/WHEN/WHY) + cross-operation synthesis. Each operation attacks the problem from a fundamentally different angle. The disagreements between the three ARE the valuable output. Works on any domain — code, business, strategy, design, text.

Why use Prism 3way on TypingMind?

Because you install it once and use it with any model. Prism 3way 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 Prism 3way in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Cranot/super-hermes/tree/master/skills/prism-3way. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Prism 3way?

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 Prism 3way?

As many as you like. As long as a model supports skills, you can use Prism 3way with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Prism 3way AI skill free?

Yes. It is published on GitHub by Cranot 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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