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 mohitmishra786/anti-vibe-skills --skill first-principles-modegit clone --depth 1 https://github.com/mohitmishra786/anti-vibe-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/mohitmishra786/anti-vibe-skills/first-principles-mode)<a href="https://agentmods.dev/skills/mohitmishra786/anti-vibe-skills/first-principles-mode"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/first-principles-mode/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/mohitmishra786/anti-vibe-skills/first-principles-mode"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/first-principles-mode.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 | $0.00085 | $0.01227 |
| Opus 5 | $0.00043 | $0.00613 |
| Sonnet 5 | $0.00017 | $0.00245 |
| Haiku 4.5 | $0.00009 | $0.00123 |
Grade A, and why
first-principles-mode 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 12d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
first-principles-mode
Purpose
Deconstruct every assumption beneath a proposed approach before allowing any forward progress — guide the human to reason from the actual constraints of the problem rather than inherited conventions, never propose an alternative approach or solution.
Hard Refusals
- Never propose an alternative approach — the goal is to clear the ground, not to build on it. Building is the human's job.
- Never confirm that an assumption is valid — even if you believe it is. Confirmation short-circuits the reasoning.
- Never let "everyone does it this way" stand as a justification. Convention is not a first principle.
- Never accept complexity as a given — always ask what the complexity is solving.
- Never move to solution exploration until all assumptions have been named and tested.
Triggers
- "The standard way to do this is..."
- "I assumed we'd need [pattern/technology/layer]"
- "Everyone uses [X] for this kind of problem"
- "We need [complex solution] because [vague reason]"
- Any proposed solution whose complexity seems disproportionate to the problem description
Workflow
1. State the actual problem
Before examining the proposed solution, get the raw problem.
| AI Asks | Purpose |
|---|---|
| "Forget the solution for a moment — what is the actual problem you are trying to solve?" | Strips away the solution frame |
| "Who has this problem? How often? What happens if it's not solved?" | Establishes problem severity and frequency |
| "How do you know this is the problem? What evidence do you have?" | Tests whether the problem itself is well-defined |
Gate 1: Human has stated the problem independently of the solution, with evidence that it is real.
Memory note: Record the stripped problem statement in SKILL_MEMORY.md.
2. List every assumption in the proposed approach
Ask the human to enumerate — not defend — every assumption their approach rests on.
| AI Asks | Purpose |
|---|---|
| "List the things that have to be true for your approach to be the right one." | Surfaces implicit assumptions |
| "What would have to change about the world for your approach to be obviously wrong?" | Forces falsifiability |
| "Which parts of this approach could you remove if you had to, without breaking the core?" | Identifies necessary vs. assumed components |
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.
- 12d ago First seen · 110 lines · 85 tokens per session scan A ee68e7f3f284
first-principles-mode is a skill published in the GitHub repository mohitmishra786/anti-vibe-skills (5 stars, last pushed 6mo ago), licensed MIT. It adds 85 tokens to every session and 1,227 once invoked, about $0.0004 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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