# cirq

A skill for Google Quantum AI's Cirq framework: build and simulate quantum circuits, model noise, run on hardware. Useful when your Python project touches quantum computing.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1900 installs · ★ 54652
- Author: K-Dense-AI
- License: LicenseRef-Apache-2.0-license · policy=link-only · description only; the file stays with the author
- Source: https://github.com/K-Dense-AI/scientific-agent-skills/tree/HEAD/skills/cirq/SKILL.md
- Updated: 2026-10-19
- HTML: https://affpapa.org/en/nevibecode/skills/cirq

## What it does

The skill hands your agent reference material on Cirq: circuit building, simulation, transformations, hardware integration and noise modeling. It ships `references/building.md`, `references/simulation.md`, `references/transformation.md`, `references/hardware.md` and `references/noise.md`, plus code examples. The agent reads them with `Read`, edits files with `Write` and `Edit`, and runs code through `Bash`.

Examples target Cirq 1.7.0 on Python 3.11+. Locally, `uv pip install "cirq-core==1.7.0"` is enough; OpenQASM import also needs `ply`. Keep every `cirq-*` package in one environment on the same release, because `cirq-google`, `cirq-ionq`, `cirq-aqt` and `cirq-pasqal` ship in step with the core. Azure is the exception: it runs its own Cirq 1.6.1 stack, and forcing 1.7.0 into it breaks the setup.

Cloud execution needs provider credentials, network access and assigned targets. Google Quantum Engine requires an approved GCP project, and bundled virtual processor names prove nothing about live access. The skill covers Google, IonQ, Azure Quantum, AQT and Pasqal. For IBM hardware you want qiskit, for quantum ML with autodiff pennylane, for physics simulations qutip.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill cirq -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/cirq/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/cirq/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill cirq -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/cirq/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill cirq -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/cirq/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install K-Dense-AI/scientific-agent-skills cirq
```

2. **Manually: put the files in place**
- File: `.github/skills/cirq/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill cirq -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/K-Dense-AI/scientific-agent-skills --path skills/cirq
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/cirq/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill cirq -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/K-Dense-AI/scientific-agent-skills/tree/HEAD/skills/cirq/SKILL.md

## When to use it
- build a parameterized circuit and sweep it over a range of values
- model noise and see how it shifts the measurement results
- compile a circuit down to a specific processor's gateset
- submit a job to Google Quantum AI or a partner backend
- work through transformers and qubit routing

## Example prompts
- Build a Bell state circuit on two qubits and run 1000 shots on `cirq.Simulator`.
- Sweep the `theta` parameter from 0 to 2π and show me the histograms.
- Add a depolarizing noise model and compare against the ideal simulation.

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From the same set: [k-dense-ai/scientific-agent-skills](https://affpapa.org/en/nevibecode/by/k-dense-ai/scientific-agent-skills.md) — 159 cards

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