Principle Attack The Premise

Community

jtaroreh

principle-attack-the-premise

Apply when handed a problem, constraint, or design you are tempted to accept as given. Ask if the premise is false, the constraint is self-imposed, or a simpler framing eliminates the work entirely.

Overview

Publisher	jtaroreh
Repository	`agystack`
Skill name	`principle-attack-the-premise`
Stars	120
Forks	12
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 jtaroreh on GitHub. Read the source before you install it.

Installation

Install the Principle Attack The Premise AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/jtaroreh/agystack/tree/main/skills/principle-attack-the-premise
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.

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/jtaroreh/agystack.git /tmp/agystack
mkdir -p .claude/skills
cp -r /tmp/agystack/skills/principle-attack-the-premise .claude/skills/principle-attack-the-premise

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Principle Attack The Premise 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 Principle Attack The Premise 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 Principle Attack The Premise 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.

Attack the Premise

Before solving a problem, ask whether the premise is valid. The highest-leverage engineering decision is often not how to build something, but recognizing that building it is unnecessary.

Why: Engineers naturally optimize within the constraints they are handed. Many constraints are accidents of history, misunderstandings, or self-imposed boundaries. Accepting false premises produces complex workarounds for problems that should not exist.

Test the Shared Assumption Directly

When debating between Option A and Option B, uncover the hidden shared premise. Debates over competing implementations often take an unproven assumption for granted.

Uncover the hidden premise. Identify what both Option A and Option B assume to be true. Both options might assume that an operation is too slow, that dual writes are necessary, or that backward compatibility must be maintained indefinitely.
Test the shared assumption directly. Run a spike, profile the operation, or take a direct empirical measurement before debating implementation details. A 10-minute microbenchmark or prototype can prove whether the assumed constraint exists in reality.
Reject false dilemmas. If direct testing disproves the premise, discard both Option A and Option B. A simpler framing eliminates unnecessary complexity and deletes the need for either implementation.

Questions to Ask

When handed a requirement, question, or design constraint, ask:

Is the stated problem the actual problem?
Is the constraint real, or assumed?
What happens if we do nothing or delete the component causing the problem?
Is there an entirely different framing where this requirement disappears?

Common False Premises

"We need a cache here." Why is the underlying operation slow? Profile it first. Make it fast enough that caching is redundant.
"We need to support both formats." Why? Verify whether external callers exist. Migrate all internal call sites and delete the legacy format.
"We need a background queue for this." Can the operation be made synchronous and fast instead? Measure the actual latency before adding queue infrastructure.
"How do we make this migration backwards-compatible?" Check if all consumers are within the same repository. Migrate call sites atomically instead of building a compatibility layer.

Premise Checks

Distinguish hard external constraints (hardware limits, physics, external API contracts) from internal choices.
Challenge "we have always done it this way" and "the user asked for X" (when the user wants Y and X was their guessed solution).
If direct measurement proves an assumed constraint false, surface the finding immediately rather than quietly implementing the complex solution.

Frequently asked questions

What does the Principle Attack The Premise AI skill do?

Apply when handed a problem, constraint, or design you are tempted to accept as given. Ask if the premise is false, the constraint is self-imposed, or a simpler framing eliminates the work entirely.

Why use Principle Attack The Premise on TypingMind?

Because you install it once and use it with any model. Principle Attack The Premise 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 Principle Attack The Premise in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jtaroreh/agystack/tree/main/skills/principle-attack-the-premise. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Principle Attack The Premise?

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 Principle Attack The Premise?

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

Is the Principle Attack The Premise AI skill free?

Yes. It is published on GitHub by jtaroreh 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Attack the Premise

Test the Shared Assumption Directly

Questions to Ask

Common False Premises

Premise Checks

Frequently asked questions

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