agentmods.dev

quantum-machine-learning

A collection of guides for variational quantum algorithms used in optimization, physics, machine learning, and generative modeling. These algorithms adjust circuit parameters to search for a useful result.

In plain words
What is it for?
Use it for QAOA optimization, VQE energy estimation, Fermi-Hubbard calculations, supervised quantum classification, generative modeling, and continuous-variable neural networks.
Why use it?
It groups workflows for several quantum tasks so you can choose an approach without designing the full method yourself.

Skill for Claude CodeCodex

18 19d ago A scan 86 tokens no licence
View the source file unitarylab/quantum-practices
Install

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.

agentmods
npx agentmods add skills/unitarylab/quantum-practices/quantum-machine-learning
Any agent
npx skills add unitarylab/quantum-practices --skill quantum-machine-learning
Clone the repo
git clone --depth 1 https://github.com/unitarylab/quantum-practices

Made for: Claude Code, Codex.

Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 537 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00086 $0.00537
Opus 5 $0.00043 $0.00269
Sonnet 5 $0.00017 $0.00107
Haiku 4.5 $0.00009 $0.00054

Measured 3d ago against content hash 05ee629c5aaa, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

quantum-machine-learning 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.

The scan reads SKILL.md. This mod also ships 12 executable files (cvqnn/scripts/algorithm.py, cvqnn/scripts/cvqnn_implementation.py, fermi-hubbard-vqe/scripts/algorithm.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

algorithms/quantum-machine-learning/SKILL.md · 41 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

18 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.

Changes

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.

  1. 3d ago First seen · 41 lines · 86 tokens per session scan A 05ee629c5aaa

Subscribe to this mod's changes

quantum-machine-learning is a skill published in the GitHub repository unitarylab/quantum-practices (18 stars, last pushed 19d ago), with no licence file. It adds 86 tokens to every session and 537 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 2026-08-30.

Data and AIScientificagent-skillsdeepseek-harnessdsh-plugindsh-pluginsquantum-algorithmsquantum-computing
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