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.
npx agentmods add skills/tupe12334/instinct/first-principlesnpx skills add tupe12334/instinct --skill first-principlesgit clone --depth 1 https://github.com/tupe12334/instinctWrote 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.
[](https://agentmods.dev/skills/tupe12334/instinct/first-principles)<a href="https://agentmods.dev/skills/tupe12334/instinct/first-principles"><img src="https://agentmods.dev/badge/skills/tupe12334/instinct/first-principles.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00021 | $0.02087 |
| Opus 5 | $0.00010 | $0.01043 |
| Sonnet 5 | $0.00004 | $0.00417 |
| Haiku 4.5 | $0.00002 | $0.00209 |
Grade A, and why
first-principles 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
First-Principles Thinking
Overview
First-principles thinking is a reasoning method that decomposes a problem to its most basic, verified truths and reconstructs a solution from there — rather than reasoning by analogy from what others have done. It was practiced by Aristotle and is closely associated with how physicists approach novel problems.
Conventional thinking: First-principles thinking:
"Others do X, so we do X" Problem
↓ ↓
Analogy / copy Ask: what is fundamentally true here?
↓ ↓
Incremental tweak Strip assumptions → bedrock facts
↓
Rebuild solution from facts up
↓
Novel or superior solution
The key discipline is distinguishing what is actually true from what is conventionally assumed.
Core Concepts
Assumptions vs. Fundamental Truths
An assumption is any constraint accepted without verification: cost, time, materials, method. A fundamental truth is a fact that would hold regardless of convention — physics, math, verified data, human need. First-principles thinking hunts for assumptions masquerading as truths.
Decomposition
Breaking a problem into its component parts until you reach irreducible elements. You cannot decompose "battery is expensive" further by analogy; you can decompose it into: cathode material cost, anode material cost, electrolyte cost, manufacturing overhead — each of which can be addressed independently.
Reconstruction
Once you hold only verified facts, you rebuild a solution unconstrained by how it has been done before. The reconstruction step is creative and deliberate — the facts constrain what is possible, not what should be built.
The Socratic Test
For each constraint or belief, ask: "How do I know this is true?" If the answer is "everyone does it this way" or "we've always done it this way," it is an assumption, not a truth. Valid answers cite data, physical laws, or direct measurement.
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.
- 3d ago First seen · 137 lines · 21 tokens per session scan A c3de84beb829
first-principles is a skill published in the GitHub repository tupe12334/instinct (1 stars, last pushed 17d ago), licensed MIT. It adds 21 tokens to every session and 2,087 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 2026-08-31.
Other skills, from other repositories
thinking-model-router
When unsure which thinking skill fits, map domain and problem type, then return NONE or one primary skill by default (at most three complementary).
thinking-red-team
For authorized security review of code, auth, or APIs you control, model the attacker, map the attack surface, and report only findings with a reproducible exploit path and verified mitigation.
thinking-scientific-method
When a symptom has several plausible causes, rank falsifiable hypotheses and run the cheapest discriminating observation first; prefer least-assumptive survivors only after evidence fit.
thinking-systems
When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.
thinking-circle-of-competence
Use when a specific claim may lack grounding. Check evidence boundary, size wrongness cost, then answer, fetch, or abstain — never confabulate.
thinking-five-whys-plus
When a fault is localized and the proximate cause is known but the systemic root is not, chain evidence-linked whys with a counterfactual stop and a countermeasure.