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 skills add ysskrishna/ai-agent-skills --skill first-principles-thinkinggit clone --depth 1 https://github.com/ysskrishna/ai-agent-skillsWrote 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/ysskrishna/ai-agent-skills/first-principles-thinking)<a href="https://agentmods.dev/skills/ysskrishna/ai-agent-skills/first-principles-thinking"><img src="https://agentmods.dev/badge/skills/ysskrishna/ai-agent-skills/first-principles-thinking/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ysskrishna/ai-agent-skills/first-principles-thinking"><img src="https://agentmods.dev/badge/skills/ysskrishna/ai-agent-skills/first-principles-thinking.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00132 | $0.00747 |
| Opus 5 | $0.00066 | $0.00374 |
| Sonnet 5 | $0.00026 | $0.00149 |
| Haiku 4.5 | $0.00013 | $0.00075 |
Grade A, and why
first-principles-thinking 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 9d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
First Principles Thinking
Question inherited baggage. Rebuild only from bedrock you can defend.
How to run it with this skill: one clearly headed section per step in this order: Surface → Question → Bedrock → Rebuild → Implications.
Setup (run before starting)
In one short block:
- Reconstruction target — belief, cost, design, or strategy to ground
- Default pass — Surface → Question → Bedrock → Rebuild → Implications (state this line)
If immutable constraints (physics, law, budget) are unclear, ask at most 3 questions in one message, then proceed. Note unknowns or working guesses in plain language (no bracket tags in Setup).
The Steps
Surface
State the conventional answer or analogy people rely on. List loaded words or hidden comparisons ("like Uber for…").
Question
For each major assumption: Assumption: … — Why believed? (authority, analogy, experience) — What if false?
Bedrock
List fundamental truths that survive scrutiny — physics, logic identities, legal musts, documented preferences of real users, arithmetic. Label each [FUNDAMENTAL] vs [STILL ASSUMPTION].
Prefer three or more honest bedrock items when that is credible; if fewer are honest, say why in one line.
Rebuild
From only [FUNDAMENTAL] items, derive conclusions in numbered steps. No smuggled analogies; if you need a new premise, add it to Bedrock first with a tag.
Implications
So what for decisions: what changes vs the conventional path? Cost of being wrong if a tagged assumption fails.
Add a short vs convention contrast (a few bullets or a two-column mini-summary) if it clarifies the decision.
Execution Rules
- Rebuild cannot cite "industry standard" as a premise unless translated into a fundamental (e.g. "buyers require SLA X because regulation Y").
- If bedrock is too thin to rebuild, say insufficient grounding and list what evidence would fix it.
- Avoid faux profundity; keep steps short and checkable.
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.
- 9d ago First seen · 82 lines · 132 tokens per session scan A f3d3b188387f
first-principles-thinking is a skill published in the GitHub repository ysskrishna/ai-agent-skills (8 stars, last pushed 3mo ago), licensed MIT. It adds 132 tokens to every session and 747 once invoked, about $0.0007 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.
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