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FirstPrinciples

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danielmiessler
FirstPrinciples

Physics-based reasoning framework (Musk methodology) that deconstructs a problem to irreducible fundamental truths, classifies every element as hard constraint, soft constraint, or assumption, then reconstructs the optimal solution from fundamentals alone. USE WHEN first principles, fundamental truths, challenge assumptions, real constraint, rebuild from scratch, start over, physics first, question everything, reasoning by analogy. NOT FOR structural feedback loops (use SystemsThinking).

Overview

Publisherdanielmiessler
RepositoryLifeOS
Skill nameFirstPrinciples
Stars
19K
Forks
2.5K
Bundled files
3
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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by danielmiessler on GitHub. Read the source before you install it.

Installation

Install the FirstPrinciples 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.
  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/danielmiessler/LifeOS.git /tmp/LifeOS
mkdir -p .claude/skills
cp -r /tmp/LifeOS/LifeOS/install/skills/FirstPrinciples .claude/skills/FirstPrinciples
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable FirstPrinciples 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 FirstPrinciples 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 FirstPrinciples 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.

Customization

Before executing, check for user customizations at: ~/.claude/LIFEOS/USER/CUSTOMIZATIONS/SKILLS/FirstPrinciples/

If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.

🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION)

You MUST send this notification BEFORE doing anything else when this skill is invoked.

  1. Send voice notification:

    bash
    curl -s -X POST http://localhost:31337/notify \
      -H "Content-Type: application/json" \
      -d '{"message": "Running the WORKFLOWNAME workflow in the FirstPrinciples skill to ACTION"}' \
      > /dev/null 2>&1 &
  2. Output text notification:

    Running the **WorkflowName** workflow in the **FirstPrinciples** skill to ACTION...

This is not optional. Execute this curl command immediately upon skill invocation.

FirstPrinciples Skill

What It Does

Breaks a problem down to its fundamental truths and rebuilds the solution from there, instead of copying what already exists. Three steps: DECONSTRUCT (break it into constituent parts and real values), CHALLENGE (classify every element as hard constraint, soft constraint, or unvalidated assumption — only physics is truly immutable), and RECONSTRUCT (build the optimal solution from the fundamentals alone). Outputs a parts breakdown, a constraint table, and a reconstructed solution.

The Core Distinction

Most reasoning is reasoning by analogy — "how did we solve something similar," "what do others do" — then copy it with tweaks. That inherits everyone else's assumptions and treats policy and convention as if they were laws of physics, so you optimize the suitcase instead of inventing wheels. First principles forces the split between what's actually immutable and what's merely inherited, then rebuilds from only the parts that can't change.

  • Reasoning by analogy (default, often wrong): copies existing solutions with slight variations.
  • Reasoning from first principles (this skill): asks "what is this actually made of?" and rebuilds from irreducible facts.

Invoked directly, or by other skills when inherited assumptions may be limiting the solution space — Architects challenging "constraint or convention?", RedTeam and pentesters attacking assumed boundaries, engineers escaping local maxima.

Workflow Routing

Route to the appropriate workflow based on the request.

When executing a workflow, output this notification directly:

Running the **WorkflowName** workflow in the **FirstPrinciples** skill to ACTION...
  • Break problem into fundamental parts → Workflows/Deconstruct.md
  • Challenge assumptions systematically → Workflows/Challenge.md
  • Rebuild solution from fundamentals → Workflows/Reconstruct.md

Constraint Classification

When analyzing any system, classify constraints:

TypeDefinitionExampleCan Change?
HardPhysics/reality"Data can't travel faster than light"No
SoftPolicy/choice"We always use REST APIs"Yes
AssumptionUnvalidated belief"Users won't accept that UX"Maybe false

Rule: Only hard constraints are truly immutable. Soft constraints and assumptions should be challenged.

Integration Pattern

Other skills invoke FirstPrinciples like this:

markdown
## Before Analysis
→ Use FirstPrinciples/Challenge on all stated constraints
→ Classify each as hard/soft/assumption

## When Stuck
→ Use FirstPrinciples/Deconstruct to break down the problem
→ Use FirstPrinciples/Reconstruct to rebuild from fundamentals

## For Adversarial Analysis
→ RedTeam uses FirstPrinciples/Challenge to attack assumptions
→ Pentester uses FirstPrinciples/Deconstruct on security model

Example

Problem: "Cloud hosting costs $10,000/month — that's just what it costs."

  • Deconstruct: What are we actually paying for? (compute, storage, bandwidth, managed services)
  • Challenge: Is managed Kubernetes a hard requirement? Is this region required? The $10K is a market price, not a fundamental cost.
  • Reconstruct: Actual compute need = $2,000. The other $8,000 is convenience we're choosing to pay for.

Output Format

When using FirstPrinciples, output should include:

markdown
## First Principles Analysis: [Topic]

### Deconstruction
- **Constituent Parts**: [List fundamental elements]
- **Actual Values**: [Real costs/metrics, not market prices]

### Constraint Classification
| Constraint | Type | Evidence | Challenge |
|------------|------|----------|-----------|
| [X] | Hard/Soft/Assumption | [Why] | [What if removed?] |

### Reconstruction
- **Fundamental Truths**: [Only the hard constraints]
- **Optimal Solution**: [Built from fundamentals]
- **Form vs Function**: [Are we optimizing the right thing?]

### Key Insight
[One sentence: what assumption was limiting us?]

The Load-Bearing Rules

  • Market prices and industry best-practices are NOT fundamental truths. "Batteries cost $600/kWh" or "hosting costs $10K/mo" are convention, not physics — deconstruct to material/compute cost before accepting them.
  • Optimize function over form — what you're trying to accomplish, not how it's traditionally done (improve the wheel, don't polish the suitcase).
  • Rebuild, don't patch — when the assumptions are wrong, start from the hard constraints rather than fixing the inherited form. Cross-domain solutions from unrelated fields often apply.

Attribution: Framework derived from Elon Musk's first principles methodology as documented by James Clear, Mayo Oshin, and public interviews.

Gotchas

  • Decompose to AXIOMS — fundamental truths, not just simpler components. The value is in finding the irreducible elements.
  • Challenge INHERITED assumptions specifically. What does everyone assume that might be wrong?
  • This is analysis/reasoning, not implementation. "Analyze" = FirstPrinciples. "Fix" = do the work directly.

Execution Log

After completing any workflow, append a single JSONL entry:

bash
echo '{"ts":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'","skill":"FirstPrinciples","workflow":"WORKFLOW_USED","input":"8_WORD_SUMMARY","status":"ok|error","duration_s":SECONDS}' >> ~/.claude/LIFEOS/MEMORY/SKILLS/execution.jsonl

Replace WORKFLOW_USED with the workflow executed, 8_WORD_SUMMARY with a brief input description, and SECONDS with approximate wall-clock time. Log status: "error" if the workflow failed.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the FirstPrinciples AI skill do?

Physics-based reasoning framework (Musk methodology) that deconstructs a problem to irreducible fundamental truths, classifies every element as hard constraint, soft constraint, or assumption, then reconstructs the optimal solution from fundamentals alone. USE WHEN first principles, fundamental truths, challenge assumptions, real constraint, rebuild from scratch, start over, physics first, question everything, reasoning by analogy. NOT FOR structural feedback loops (use SystemsThinking).

Why use FirstPrinciples on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/danielmiessler/LifeOS/tree/main/LifeOS/install/skills/FirstPrinciples. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use FirstPrinciples?

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 FirstPrinciples?

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

Is the FirstPrinciples AI skill free?

Yes. It is published on GitHub by danielmiessler 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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