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Macrothink

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LilMGenius
macrothink

User-invoked read-only pass for checking whether the current direction is tunnel-visioned: strip the session's bait, fan out 2 to 5 same-model fresh reads, and report divergence first without treating convergence as proof.

Overview

PublisherLilMGenius
Repositorypaperthin
Skill namemacrothink
Stars
1.3K
Forks
118
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 LilMGenius on GitHub. Read the source before you install it.

Installation

Install the Macrothink 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/LilMGenius/paperthin/tree/main/skills/depth/macrothink
  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/LilMGenius/paperthin.git /tmp/paperthin
mkdir -p .claude/skills
cp -r /tmp/paperthin/skills/depth/macrothink .claude/skills/macrothink
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Macrothink 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 Macrothink 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 Macrothink 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.

Step back from the session's chosen path and ask several fresh reads what the current direction might be missing.

Goal

macrothink checks the live decision or direction in hand, not the artifact that describes it. It is for moments when the session may have inherited a framing from examples, wording, prior turns, or a first plausible answer.

The product is a spread of independent reads. Divergence is the signal. Convergence is reassurance, never proof.

Workflow

This skill is not model-invoked automatically. When a user explicitly invokes it, the invoked run may create the bounded fresh sub-sessions below; they are read-only inputs to this pass, not separate authority to change the plan.

  1. Name the current direction: the decision the session is about to keep building on.
  2. Strip the prompt to the underlying problem: goal, constraints, and known facts. Remove the session's own examples, suggested answer, preferred naming, and framing-specific wording.
  3. Fan out independent fresh reads of that stripped restatement: 2 to 5, default 3. Same model is allowed because this pass does not claim cross-model verification.
  4. Collect each read without correcting it toward the session's current direction.
  5. Classify each read against the current direction:
    • divergent-incompatible: challenges a premise the direction depends on.
    • divergent-compatible: adds or reframes something useful without discarding the direction.
    • convergent: independently lands near the current direction.
  6. Cluster before reporting: when several reads diverge in the same direction, name the shared root they point at — the pattern behind the divergences is the finding, and the individual reads sit under it as evidence. Do not report five specifics that are one gap seen five times.
  7. Report divergent-incompatible first, then divergent-compatible, then convergent. Label convergence as reassurance only.
  8. Return control to the main session. This skill is read-only and advisory; it does not rewrite the plan or pick the final answer.

Rules

  • Divergence first. The most important output is the strongest divergent-incompatible finding, if any.
  • Roots over instances. A spread of specific divergences that share one underlying gap is one finding, not many; naming the root is what makes the pass actionable beyond the cases the reads happened to hit.
  • No majority vote or averaging. Do not pick a winner by count, smooth away disagreement, or present agreement as consensus.
  • Same model is allowed. The pass looks for session-framing blind spots, not model-independent truth.
  • User-invoked fan-out only. Do not trigger this skill automatically. If the user invokes it, bounded read-only fresh sub-sessions are allowed to produce the required reads.
  • Not consensus verification. Do not say the direction is verified, proved, validated, or settled by same-model convergence.
  • Convergence is reassurance, not proof. It means this pass did not surface a better angle; it does not certify correctness.
  • Read-only / advisory. Surface candidates and risks; leave decisions and edits to the main workflow.

Verification

Before finishing, confirm:

  1. The restatement removed the session's bait while preserving real constraints.
  2. Every read was classified as divergent-incompatible, divergent-compatible, or convergent.
  3. Divergences sharing one root were reported as that root, with the individual reads as evidence under it.
  4. The report put divergent-incompatible findings first.
  5. Any convergence was described as reassurance, not proof.
  6. The report did not use consensus, majority, averaging, verified, or proved wording.

Frequently asked questions

What does the Macrothink AI skill do?

User-invoked read-only pass for checking whether the current direction is tunnel-visioned: strip the session's bait, fan out 2 to 5 same-model fresh reads, and report divergence first without treating convergence as proof.

Why use Macrothink on TypingMind?

Because you install it once and use it with any model. Macrothink 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 Macrothink in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LilMGenius/paperthin/tree/main/skills/depth/macrothink. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Macrothink?

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 Macrothink?

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

Is the Macrothink AI skill free?

Yes. It is published on GitHub by LilMGenius 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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