first-principles-analyzer

first-principles-analyzer is a skill for Claude Code, Codex from codebygarv/Ai-skills. It costs 26 tokens per session (379 once invoked), scanned A, original, MIT.

A way to design or evaluate a solution by starting with basic facts and unavoidable constraints instead of copying common industry patterns. It questions which assumptions are truly necessary.

In plain words
What is it for?
Use it when rethinking architecture, simplifying an expensive system, or checking whether a common best practice fits your specific constraints.
Why use it?
It helps uncover unnecessary complexity, cost, or inherited conventions. It supports a simpler design built around the actual objective and limits of the problem.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when rethinking architecture, simplifying an expensive system, or checking whether a common best practice fits your specific constraints.

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Install with agentmods
npx agentmods add skills/codebygarv/ai-skills/first-principles-analyzer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add codebygarv/Ai-skills --skill first-principles-analyzer
Clone the repo
git clone --depth 1 https://github.com/codebygarv/Ai-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for first-principles-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/codebygarv/ai-skills/first-principles-analyzer.svg)](https://agentmods.dev/skills/codebygarv/ai-skills/first-principles-analyzer)
Your own site
<a href="https://agentmods.dev/skills/codebygarv/ai-skills/first-principles-analyzer"><img src="https://agentmods.dev/badge/skills/codebygarv/ai-skills/first-principles-analyzer.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 379 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00026 $0.00379
Opus 5 $0.00013 $0.00189
Sonnet 5 $0.00005 $0.00076
Haiku 4.5 $0.00003 $0.00038

Measured 4d ago against content hash 5ab620934e44, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

first-principles-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/reasoning/first-principles-analyzer/SKILL.md · 37 lines

What it actually says

Purpose

Strip away industry cargo-culting, legacy conventions, and reasoning-by-analogy to rebuild solutions strictly from fundamental constraints (physics, math, raw computing limits, core business rules).

When to Use

  • When existing solutions are bloated, expensive, or overly complex because "that is how everyone does it."
  • When rethinking an architectural component or feature from the ground up.
  • When evaluating whether an established best practice actually applies to your specific constraints.

What to Analyze

  1. Identify the Core Objective: What is the non-negotiable end goal in one sentence?
  2. Catalog Received Assumptions: List every assumption inherited from typical stacks, standard patterns, or prior systems.
  3. Isolate Hard Constraints: What physical, computational, legal, or mathematical limits cannot be broken?
  4. Question Derived Rules: For each assumed rule, ask "Is this fundamentally required, or just a convention?"
  5. Reconstruct from Scratch: Synthesize the leanest possible design that satisfies the hard constraints.

Output Format

  • Core Objective & Boundary: The single essential truth.
  • Deconstructed Assumptions: Table of [Common Assumption vs. Fundamental Reality].
  • Hard Constraints vs. Artificial Constraints: Clear separation of real limits vs choices.
  • Reconstructed First-Principles Design: The minimal, high-efficiency path.
  • Key Trade-offs: What convention-driven conveniences are sacrificed.

Avoid

  • Recommending a tool just because "FAANG uses it".
  • Over-engineering custom solutions when a simple standard tool has negligible overhead.
  • Confusing organizational inertia with technical constraints.
Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 37 lines · 26 tokens per session scan A 5ab620934e44

Subscribe to this mod's changes

first-principles-analyzer is a skill published in the GitHub repository codebygarv/Ai-skills (25 stars, last pushed 19d ago), licensed MIT. It adds 26 tokens to every session and 379 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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