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 Dqz00116/skill-lib --skill layered-first-principles-teachinggit clone --depth 1 https://github.com/Dqz00116/skill-libWrote 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/dqz00116/skill-lib/layered-first-principles-teaching)<a href="https://agentmods.dev/skills/dqz00116/skill-lib/layered-first-principles-teaching"><img src="https://agentmods.dev/badge/skills/dqz00116/skill-lib/layered-first-principles-teaching/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/dqz00116/skill-lib/layered-first-principles-teaching"><img src="https://agentmods.dev/badge/skills/dqz00116/skill-lib/layered-first-principles-teaching.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 | $0.00028 | $0.00809 |
| Opus 5.5 | $0.00011 | $0.00324 |
| Sonnet 5.5 | $0.00006 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
layered-first-principles-teaching 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 1mo 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Layered First Principles Teaching
Overview
Transform complex concepts into progressive, first-principles explanations that build understanding layer by layer.
When to Use
Use when:
- You need to explain a complex concept to someone with less domain knowledge
- You're designing training materials, tutorials, or educational content
- You're preparing a technical presentation and need progressive disclosure
- A topic has multiple abstraction layers that require cognitive scaffolding
- You need to bridge the gap between intuitive understanding and technical depth
Don't use when:
- The concept is simple and doesn't benefit from layered decomposition
- You need quick reference documentation or a terse answer
- The audience already has deep expertise and only needs edge cases or implementation details
Quick Start
# Explain a concept progressively
kimi layered-first-principles-teaching "Explain blockchain"
# Target specific audience
kimi layered-first-principles-teaching "Explain transformers" --audience beginner
# Output to file
kimi layered-first-principles-teaching "Explain consensus algorithms" --output ./tutorial.md
Output Structure
Generated explanations contain 6 standard sections:
| Section | Content | Purpose |
|---|---|---|
| Opening | One-sentence essence + intuitive analogy | Immediate understanding |
| First Principles | Problem essence, why existing solutions fail | Foundation building |
| Progressive Layers | 3-4 layers from intuition to technical detail | Scaffolding learning |
| Analogies | Cross-domain comparisons | Relating to known concepts |
| Visualizations | ASCII diagrams, mental models | Spatial understanding |
| Summary | Key takeaways + further reading | Retention & next steps |
Audience Levels
| Level | Characteristics | Approach |
|---|---|---|
| Beginner | No prior knowledge | Heavy analogies, minimal jargon, focus on "why" |
| Intermediate | Some domain knowledge | Balance of intuition and technical detail |
| Expert | Deep domain knowledge | Focus on nuances, edge cases, implementation |
What ships with it
8 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.
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.
- 1mo ago First seen · 101 lines · 28 tokens per session scan A 43d9d0c2b4bc
layered-first-principles-teaching is a skill published in the GitHub repository Dqz00116/skill-lib (22 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 809 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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