First Principles Review logo

First Principles Review

Organization
sno-ai
first-principles-review

MANUAL-ONLY: challenge a product idea, design, PRD, or architecture from first principles. Use only when the user names this skill. Research first, then write a local review and PRD handoff.

Overview

Publishersno-ai
Repositorysno-station-skills
Skill namefirst-principles-review
Stars
604
Forks
415
Bundled files
9
LicenseApache-2.0
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.

  • 9 bundled files

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

  • Open source

    Published by sno-ai on GitHub. Read the source before you install it.

Installation

Install the First Principles Review 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/sno-ai/sno-station-skills/tree/main/skills/J-peer-review-and-audit/first-principles-review/skill
  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/sno-ai/sno-station-skills.git /tmp/sno-station-skills
mkdir -p .claude/skills
cp -r /tmp/sno-station-skills/skills/J-peer-review-and-audit/first-principles-review/skill .claude/skills/first-principles-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable First Principles Review 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 First Principles Review 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 First Principles Review 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.

First-Principles Reviewer

Run before a proposal hardens into requirements or source code. The owner is whoever owns the work and decides what it should be; often that is the user. A PRD is a product requirements document. Judge the problem framing, constraints, and solution shape. Source code is evidence about the incumbent, not the main review target; route source-defect review to peer-review.

Invocation Gate

Proceed only when the human explicitly invokes this skill ($first-principles-review or /first-principles-review) or names it in the current request. Do not infer invocation from the presence of a PRD or design.

Workflow

  1. Freeze the boundary. Identify the input, record its hash when it is a file, choose a local report path, and do not modify the reviewed input. Use reports/<input-stem>-first-principles-review.md unless the human names another path. Use a distinct report filename when the default already exists. If a named input is missing or unreadable, locate the canonical artifact, repair access within authority, and continue the review. Work on independent evidence meanwhile; ask only for an input that only the owner can supply. Never invent the missing artifact or claim a completed review without reading it.

  2. Research before challenging. Read the relevant product intent, prior decisions, incumbent behavior, immediate code/design dependencies, and current external solutions. Record every source and every material gap. When current external facts matter, browse. Stop when another source cannot change a premise state, the disposition, or the next evidence-producing action. Record that stopping boundary.

  3. Re-derive the outcome. State what the user or system must achieve without borrowing the proposed implementation.

  4. Classify constraints. Mark each claim as hard constraint, owner preference, or inherited assumption. Cite evidence. A physical, legal, published-contract, measured economic, or explicit owner limit may be hard; familiarity is not.

  5. Challenge premises. Build a ledger of load-bearing premises. Mark each evidence-backed, unproven, inherited, or falsified. Apply removal, inversion, substitution, do-nothing, and incumbent comparison where they can change the decision. A settled owner decision stays settled unless a specific new fact changes its basis. Name that fact before challenging the ruling; never relabel the ruling as inherited.

  6. Construct real alternatives. Consider eliminating the need, reusing an incumbent or native capability, making the smallest viable change, and redesigning from true constraints. Include only materially distinct candidates. Do not force novelty or a candidate count.

  7. Choose a disposition. Use exactly one: PROCEED, REFRAME, SIMPLIFY, REPLACE, SPLIT, TEST-FIRST, or STOP. For SPLIT, record at least two independently buildable outcomes inside the single handoff object. PROCEED means evidence is strong enough to enter PRD authoring, not to skip implementation or production verification. Use TEST-FIRST only when a missing fact could change the problem framing or selected direction before PRD authoring. Repeated benchmarks and rollout checks belong in acceptance implications or falsifiers and do not by themselves block PROCEED.

  8. Recommend one direction. Compare the current proposal and surviving alternatives on outcome fit, complexity, failure surface, reversibility, time to evidence, and migration cost. Name observable evidence that would overturn the recommendation.

  9. Write and validate the report. Follow references/report-contract.md, including its embedded JSON handoff. Run:

    bash
    python3 <skill-dir>/scripts/validate-report.py <report.md>
    python3 <skill-dir>/scripts/extract-prd-handoff.py <report.md> > <handoff.json>

    <skill-dir> is the folder that contains this SKILL.md. Both scripts need python3.

  10. Ask only after the report exists. Keep questions out of the report. If a genuine owner decision survives research, ask one decision at a time in chat. Otherwise hand the report and extracted block to whoever writes the PRD (a PRD-writing skill, if one is installed).

Judgment Rules

  • By default this review is one pass (a project may choose otherwise): do not rerun it to confirm edits, and do not turn its output into a new review target. Whoever acts on the report records how each recommendation was handled, proves fixes deterministically, and continues.
  • The report is the record of the review. Do not prewrite or self-author a PROCEED result before this workflow has inspected the evidence.
  • Verified fact, inference, and unknown are different claims. Label them separately.
  • A recommendation without falsifiers is advocacy, not review.
  • No research or no challenged premise is an instrument failure, not a clean result.
  • PROCEED means the proposal survived meaningful challenge; it does not mean exhaustive proof or production readiness.
  • Preserve rejected alternatives and why they lost so the PRD author does not re-derive them.
  • When existing source is supplied, use it to establish incumbent behavior, constraints, and coupling. Route source defects to peer-review.
  • The report is bounded and non-exhaustive. Say so explicitly.

Output

Create one independent local Markdown report. Report the exact path. Do not edit a target PRD or automatically invoke a PRD skill. The embedded handoff is the downstream contract; prose remains the human record.

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 First Principles Review AI skill do?

MANUAL-ONLY: challenge a product idea, design, PRD, or architecture from first principles. Use only when the user names this skill. Research first, then write a local review and PRD handoff.

Why use First Principles Review on TypingMind?

Because you install it once and use it with any model. First Principles Review 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 First Principles Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sno-ai/sno-station-skills/tree/main/skills/J-peer-review-and-audit/first-principles-review/skill. 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 First Principles Review?

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 First Principles Review?

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

Is the First Principles Review AI skill free?

Yes. It is published on GitHub by sno-ai under the Apache-2.0 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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