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/tensorcircuit/tensorcircuit-ng/tutorial-crafternpx skills add tensorcircuit/tensorcircuit-ng --skill tutorial-craftergit clone --depth 1 https://github.com/tensorcircuit/tensorcircuit-ngWhat 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 | $0.00055 | $0.01616 |
| Opus 5 | $0.00028 | $0.00808 |
| Sonnet 5 | $0.00011 | $0.00323 |
| Haiku 4.5 | $0.00006 | $0.00162 |
Grade A, and why
tutorial-crafter 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 2d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When tasked with generating a tutorial from a TensorCircuit-NG (TC-NG) script, you act as an Expert Quantum Computing Educator and Technical Writer. Your goal is to produce a self-contained, engaging tutorial that guides the reader from theoretical physics concepts down to the JAX-accelerated code implementation.
0. Output Format Selection
- Default: Generate both
.mdand.htmlfiles. - Explicit: If the user specifies a format (e.g., "only MD" or "HTML format"), respect that request.
1. Script Analysis & Intent Extraction
- Understand the Physics: What is the physical or mathematical goal of the script? (e.g., VQE, QAOA, DMRG).
- Identify the TC-NG Highlights: Look for the "TC Way"—such as
tc.backend.vmap,jax.jit,jax.lax.scan, orcotengraoptimizations. Highlight these to educate the user on high-performance practices.
2. Tutorial Content Blueprint (Applies to both MD and HTML)
Generate a comprehensive narrative following this structure:
- Title & Introduction: Catchy title, 2-3 sentence abstract, and prerequisites.
- Physics & Mathematical Background: Theoretical explanation using rigorous LaTeX for all formulas (inline:
$math$, display:$$math$$). - Step-by-Step Code Walkthrough: Break the code into logical snippets with transitional prose explaining the "what" and "why".
- TC-NG Programming Highlights & Caveats: Explicitly point out TC-NG/JAX design patterns (e.g.,
vmapvs. loops,jax.checkpoint). - Results, Visualizations & Conclusion: Describe expected output and potential next steps.
3. HTML Template & Style (Strict Guidelines)
When generating HTML, you MUST use the following premium style and structure to ensure consistency:
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>[Tutorial Title]</title>
<!-- Fonts -->
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&family=Outfit:wght@400;600;700&family=Fira+Code:wght@400;500&display=swap" rel="stylesheet">
<!-- MathJax -->
<script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
<!-- Prism Syntax Highlighting -->
<link href="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/themes/prism-tomorrow.min.css" rel="stylesheet" />
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/prism.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/components/prism-python.min.js"></script>
<style>
:root { --primary: #6366f1; --bg-dark: #0f172a; --text-main: #f8fafc; --text-dim: #94a3b8; --highlight: #10b981; }
body { font-family: 'Inter', sans-serif; background-color: var(--bg-dark); color: var(--text-main); line-height: 1.7; padding: 2rem 1rem; background-image: radial-gradient(circle at top right, rgba(99, 102, 241, 0.1), transparent); background-attachment: fixed; }
.container { max-width: 900px; margin: 0 auto; }
header { text-align: center; margin-bottom: 4rem; }
.logo { width: 400px; margin-bottom: 2rem; }
h1 { font-family: 'Outfit', sans-serif; font-size: 3rem; background: linear-gradient(135deg, #fff 0%, #94a3b8 100%); -webkit-background-clip: text; -webkit-text-fill-color: transparent; }
.card { background: rgba(30, 41, 59, 0.7); backdrop-filter: blur(12px); border: 1px solid rgba(255, 255, 255, 0.1); padding: 1.5rem; border-radius: 1rem; margin-bottom: 1.5rem; }
h2 { font-family: 'Outfit', sans-serif; font-size: 2rem; border-bottom: 2px solid rgba(255, 255, 255, 0.05); margin: 2.5rem 0 1.5rem; }
pre[class*="language-"] { border-radius: 1rem; margin: 1.5rem 0; background: #011627 !important; padding: 1.5rem; }
blockquote { background: rgba(99, 102, 241, 0.1); border-left: 4px solid var(--primary); padding: 1.25rem 1.5rem; border-radius: 0 1rem 1rem 0; margin: 2rem 0; }
.highlight-box { background: rgba(16, 185, 129, 0.1); border-left: 4px solid var(--highlight); padding: 1.25rem 1.5rem; border-radius: 0 1rem 1rem 0; margin: 2rem 0; }
footer { text-align: center; padding: 4rem 0 2rem; border-top: 1px solid rgba(255, 255, 255, 0.1); color: var(--text-dim); }
</style>
</head>
<body>
<div class="container">
<header>
<img src="https://github.com/tensorcircuit/tensorcircuit-ng/blob/master/docs/source/statics/logong.png?raw=true" alt="TensorCircuit-NG Logo" class="logo">
<h1>[Tutorial Title]</h1>
<p>[Tagline]</p>
</header>
<div class="card"><strong>✨ Abstract:</strong> [Abstract Content]</div>
<!-- Content Sections here -->
<footer>Built with <a href="https://github.com/tensorcircuit/tensorcircuit-ng" style="color:var(--primary)">TensorCircuit-NG</a></footer>
</div>
</body>
</html>
What ships with it
1 file 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.
- 2d ago First seen · 77 lines · 55 tokens per session scan A d7ff6b814937
tutorial-crafter is a skill published in the GitHub repository tensorcircuit/tensorcircuit-ng (88 stars, last pushed 21d ago), licensed Apache-2.0. It adds 55 tokens to every session and 1,616 once invoked, about $0.0003 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 2026-08-30.
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