Agent skill

Quantum Computing Guide

by wentorai in wentorai/research-plugins

Explore quantum computing research with Qiskit and Cirq frameworks

MITAuto-check passedResearch & Science

Install Quantum Computing Guide

skills CLI
$ npx skills add wentorai/research-plugins --skill quantum-computing-guide -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wentorai/research-plugins quantum-computing-guide --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/domains/physics/quantum-computing-guide .claude/skills/quantum-computing-guide && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
quantum-computing-guide
GitHub stars
298
Used in
1 other repo
Token cost
~1.6k tokens
SKILL.md length
153 words
Files
1
Skills in repo
428
Repo updated
First seen
Licence
MIT

At a glance

Explore quantum computing research with Qiskit and Cirq frameworks

  • Tasks that involve Quantum computing
  • SKILL.md covers Quantum Computing Fundamentals, Building Quantum Circuits with…, Fundamental Quantum Algorithms and Noise and Error Mitigation, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Quantum Computing Guide is an agent skill from wentorai/research-plugins. Explore quantum computing research with Qiskit and Cirq frameworks

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Quantum computing. It works with Qiskit. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Quantum computing

Example prompts

  • “/quantum-computing-guide”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Quantum Computing Guide loads about 1.6k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 153 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 153 words, ~1,614 tokens.

Download SKILL.mdSave it as .claude/skills/quantum-computing-guide/SKILL.md (or your agent's skills folder).
name
quantum-computing-guide
description
Explore quantum computing research with Qiskit and Cirq frameworks

Quantum Computing Guide

A skill for conducting quantum computing research using Qiskit (IBM) and Cirq (Google) frameworks. Covers quantum circuit construction, fundamental algorithms, noise simulation, and practical considerations for running experiments on quantum hardware.

Quantum Computing Fundamentals

Key Concepts
Qubit: The basic unit of quantum information
  - Superposition: A qubit can be in a state |0>, |1>, or any
    linear combination alpha|0> + beta|1> where |alpha|^2 + |beta|^2 = 1
  - Measurement: Collapses to |0> with probability |alpha|^2
    or |1> with probability |beta|^2

Entanglement: Two qubits can be correlated in ways impossible classically
  - Bell state: (|00> + |11>) / sqrt(2)
  - Measuring one qubit instantly determines the other

Quantum gates: Unitary operations that transform qubit states
  - Single-qubit: H (Hadamard), X (NOT), Z, S, T, Rx, Ry, Rz
  - Two-qubit: CNOT, CZ, SWAP
  - Multi-qubit: Toffoli (CCNOT), Fredkin (CSWAP)

Building Quantum Circuits with Qiskit

Basic Circuit Construction
python
from qiskit import QuantumCircuit
from qiskit_aer import AerSimulator


def create_bell_state() -> QuantumCircuit:
    """
    Create a Bell state (maximally entangled pair).
    """
    qc = QuantumCircuit(2, 2)

    # Apply Hadamard to qubit 0 (creates superposition)
    qc.h(0)

    # Apply CNOT with qubit 0 as control, qubit 1 as target
    qc.cx(0, 1)

    # Measure both qubits
    qc.measure([0, 1], [0, 1])

    return qc


def run_circuit(qc: QuantumCircuit, shots: int = 1024) -> dict:
    """
    Run a quantum circuit on a simulator.

    Args:
        qc: Quantum circuit to execute
        shots: Number of measurement repetitions
    """
    simulator = AerSimulator()
    result = simulator.run(qc, shots=shots).result()
    counts = result.get_counts()

    return {
        "counts": counts,
        "probabilities": {
            state: count / shots for state, count in counts.items()
        }
    }
Quantum Teleportation Circuit
python
def quantum_teleportation() -> QuantumCircuit:
    """
    Implement quantum teleportation protocol.
    Transfers the state of qubit 0 to qubit 2 using entanglement.
    """
    qc = QuantumCircuit(3, 3)

    # Prepare an arbitrary state on qubit 0
    qc.rx(1.2, 0)
    qc.rz(0.7, 0)

    qc.barrier()

    # Create entangled pair (qubits 1 and 2)
    qc.h(1)
    qc.cx(1, 2)

    qc.barrier()

    # Bell measurement on qubits 0 and 1
    qc.cx(0, 1)
    qc.h(0)
    qc.measure([0, 1], [0, 1])

    qc.barrier()

    # Conditional corrections on qubit 2
    qc.cx(1, 2)
    qc.cz(0, 2)

    qc.measure(2, 2)

    return qc

Fundamental Quantum Algorithms

Algorithm Overview
AlgorithmSpeedupProblem
Grover'sQuadratic (sqrt(N))Unstructured search
Shor'sExponentialInteger factorization
VQEHeuristicGround state energy
QAOAHeuristicCombinatorial optimization
Quantum Phase EstimationExponentialEigenvalue estimation
HHLExponential (conditions apply)Linear systems
Variational Quantum Eigensolver (VQE)
python
from qiskit.circuit.library import TwoLocal


def build_vqe_circuit(n_qubits: int, depth: int = 2) -> dict:
    """
    Build a parameterized ansatz circuit for VQE.

    Args:
        n_qubits: Number of qubits
        depth: Circuit depth (repetitions)
    """
    ansatz = TwoLocal(
        n_qubits,
        rotation_blocks=["ry", "rz"],
        entanglement_blocks="cx",
        entanglement="linear",
        reps=depth
    )

    return {
        "circuit": ansatz,
        "n_parameters": ansatz.num_parameters,
        "description": (
            "VQE uses a classical optimizer to minimize "
            "<psi(theta)|H|psi(theta)> where psi(theta) is the "
            "parameterized quantum state and H is the Hamiltonian."
        )
    }

Noise and Error Mitigation

Simulating Realistic Noise
python
from qiskit_aer.noise import NoiseModel, depolarizing_error


def create_noisy_simulator(error_rate: float = 0.01) -> dict:
    """
    Create a noise model for realistic quantum simulation.

    Args:
        error_rate: Depolarizing error probability per gate
    """
    noise_model = NoiseModel()

    # Single-qubit gate error
    error_1q = depolarizing_error(error_rate, 1)
    noise_model.add_all_qubit_quantum_error(error_1q, ["h", "rx", "ry", "rz"])

    # Two-qubit gate error (typically higher)
    error_2q = depolarizing_error(error_rate * 10, 2)
    noise_model.add_all_qubit_quantum_error(error_2q, ["cx"])

    return {
        "noise_model": noise_model,
        "single_qubit_error": error_rate,
        "two_qubit_error": error_rate * 10,
        "mitigation_strategies": [
            "Zero-Noise Extrapolation (ZNE)",
            "Probabilistic Error Cancellation (PEC)",
            "Measurement error mitigation",
            "Dynamical decoupling",
            "Quantum error correction (surface codes)"
        ]
    }

Running on Real Hardware

Practical Considerations
1. Qubit connectivity:
   Real devices have limited qubit connections (not all-to-all)
   SWAP gates are needed to route operations -> increases circuit depth

2. Gate fidelity:
   Single-qubit gates: ~99.9% fidelity
   Two-qubit gates: ~99-99.5% fidelity
   Limits useful circuit depth to ~100-1000 gates

3. Coherence times:
   T1 (energy relaxation): 100-500 microseconds
   T2 (dephasing): 50-200 microseconds
   Circuit must complete before decoherence

4. Queue times:
   Real quantum computers have job queues (minutes to hours)
   Use simulators for development; reserve hardware for final runs

Publishing Quantum Computing Research

Report the exact device used (name, calibration date), number of qubits and connectivity, gate set and fidelities, transpilation settings, number of shots, error mitigation techniques applied, and comparison with classical simulation where tractable. Provide Qiskit or Cirq code in a public repository for reproducibility.

© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/domains/physics/quantum-computing-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Quantum Computing Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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QutipzLanqing/codex-claude-academic-skills4.6k9 repos~2.3kAutomated safety check: PassBSD-3-Clause
Qiskitdavila7/claude-code-templates32k10 repos~2.2kAutomated safety check: PassMIT
QiskitK-Dense-AI/scientific-agent-skills48k1 repos~3.3kAutomated safety check: PassApache-2.0
PennylaneK-Dense-AI/scientific-agent-skills48k1 repos~1.8kAutomated safety check: NotesApache-2.0

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Works with

Questions about Quantum Computing Guide

What does Quantum Computing Guide do?

Explore quantum computing research with Qiskit and Cirq frameworks. Quantum Computing Guide is an agent skill from wentorai/research-plugins.

When should I use Quantum Computing Guide?

Quantum Computing Guide fits situations like: tasks that involve Quantum computing.

How do I install Quantum Computing Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill quantum-computing-guide -a claude-code`. Or copy the skill folder (skills/domains/physics/quantum-computing-guide in wentorai/research-plugins) into .claude/skills/quantum-computing-guide in your project. Claude Code loads it when a task matches its description.

How do I install Quantum Computing Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill quantum-computing-guide -a codex`. Or copy the skill folder (skills/domains/physics/quantum-computing-guide in wentorai/research-plugins) into .agents/skills/quantum-computing-guide in your project. Codex loads it when a task matches its description.

Can I use Quantum Computing Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wentorai/research-plugins --skill quantum-computing-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/quantum-computing-guide, .gemini/skills/quantum-computing-guide, .github/skills/quantum-computing-guide and .opencode/skills/quantum-computing-guide in your project.

What does Quantum Computing Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: Quantum Computing Guide is instructions for the agent only. Our summary lists: Python 3.

Does Quantum Computing Guide access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Quantum Computing Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Quantum Computing Guide use?

Quantum Computing Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Quantum Computing Guide use?

About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Quantum Computing Guide?

Skills that share tags, products or a category with Quantum Computing Guide: Qiskit 2.x Quantum ML Reference (aiming-lab/AutoResearchClaw, 15k stars), Qutip (zLanqing/codex-claude-academic-skills, 4.6k stars), Qiskit (davila7/claude-code-templates, 32k stars) and Qiskit (K-Dense-AI/scientific-agent-skills, 48k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Quantum Computing Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 428 skills in this directory. The repository was last updated on June 19, 2026.

Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.