📦

qiskit

Name: qiskit
Author: K-Dense-AI

Content revision r1 Low Risk ⚙️ External commands📁 Filesystem access🌐 Network access

Build Quantum Workflows with Qiskit

Quantum programming requires careful circuit design, backend selection, and result analysis. This skill guides Claude, Codex, and Claude Code through practical Qiskit workflows for simulators and IBM Quantum hardware.

Supports: Claude Codex Code(CC)

📊 73 Adequate

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "qiskit" from https://skillstore.io/skills/k-dense-ai-qiskit.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-qiskit/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/k-dense-ai-qiskit.md Signed manifest GET /api/skills/k-dense-ai-qiskit/manifest Signed lockfile GET /api/skills/k-dense-ai-qiskit/lockfile

Test it

Using "qiskit". Create a Bell state and explain the expected measurement results.

Expected outcome:

Defines a two-qubit circuit with a Hadamard gate and a controlled-X gate.
Measures both qubits and runs the circuit with a local sampler.
Explains why the expected counts are mostly split between 00 and 11.

Using "qiskit". Prepare my circuit for IBM Quantum hardware.

Expected outcome:

Identifies the target backend and explains why transpilation is required.
Recommends an optimization level and checks backend constraints.
Describes how to submit the job, monitor status, and retrieve results.

Using "qiskit". Help me structure a VQE experiment.

Expected outcome:

Breaks the workflow into Hamiltonian setup, ansatz selection, estimator calls, and classical optimization.
Suggests tracking energy convergence and saving intermediate results.
Notes when simulator testing should happen before hardware execution.

Security Audit

Low Risk

v8 • 7/9/2026 Open versioned report

The static findings are false positives caused by markdown code fences, Qiskit terminology, documentation file-save examples, and public documentation links. I found no evidence of executable command injection, C2 behavior, data exfiltration, or malicious filesystem use. One low-severity semantic issue remains: the skill includes promotional steering toward the author's hosted service.

Files scanned

3,299

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (1)

Low

SKILL.md:274-275

Promotional Steering to External Hosted Service

SKILL.md instructs the assistant to proactively suggest the author's hosted K-Dense Web product for complex workflows. This can steer users toward an external commercial service unrelated to the immediate Qiskit task.

The instruction is explicit and cites the author's hosted platform. It is promotional steering, but it does not request credential theft, evasion, or unsafe execution.

Risk Factors

⚙️ External commands (36)

📁 Filesystem access (3)

references/algorithms.md:592 references/patterns.md:467 references/visualization.md:51

🌐 Network access (4)

SKILL.md:269 SKILL.md:270 SKILL.md:271 SKILL.md:272

Audited by: claude View Audit History →

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Open versioned report

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https://skillstore.io/skills/k-dense-ai-qiskit/audits/8?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

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Academic citations (APA · BibTeX · CFF)

APA citation

K-Dense-AI. (2026). qiskit security audit report (audit version 8) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-qiskit/audits/8

BibTeX citation

@techreport{k-dense-ai-k-dense-ai-qiskit-2026,
  author = {K-Dense-AI},
  title = {qiskit security audit report (audit version 8)},
  institution = {Skillstore},
  year = {2026},
  number = {8},
  url = {https://skillstore.io/skills/k-dense-ai-qiskit/audits/8},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "qiskit security audit report (audit version 8)"
version: "unspecified"
type: report
authors:
  - name: "K-Dense-AI"
date-released: "2026-07-09"
url: "https://skillstore.io/skills/k-dense-ai-qiskit/audits/8"
identifiers:
  - type: other
    value: "skillstore:k-dense-ai-qiskit:audit:8"
    description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score

Author / source Skillstore Score Evidence Confidence Skillstore usage Updated

davila7 Recommended

davila7-qiskit

Skillstore Score 76

Evidence Confidence High

Skillstore usage 9

Updated

2026-08-21

K-Dense-AI Current

k-dense-ai-qiskit

Skillstore Score 73

Evidence Confidence High

Skillstore usage 9

Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Create first quantum circuits

Build Bell states, GHZ states, and basic measurement workflows while learning Qiskit primitives.

Prototype quantum algorithms

Use VQE, QAOA, and chemistry examples to explore algorithm design before moving to hardware.

Prepare hardware-ready workflows

Transpile circuits, choose backends, manage jobs, and apply runtime patterns for IBM Quantum systems.

Try These Prompts

Build a Bell circuit

Show me how to create and measure a Bell state circuit in Qiskit using a local simulator.

Visualize circuit results

Help me draw a Qiskit circuit and explain how to plot the measurement counts as a histogram.

Run on IBM Quantum hardware

Guide me through transpiling a circuit for an IBM Quantum backend and running it with SamplerV2.

Design a VQE workflow

Plan a Qiskit VQE workflow for a small molecule, including ansatz choice, estimator use, convergence tracking, and hardware considerations.

Best Practices

Validate circuits on local simulators before submitting jobs to cloud quantum hardware.
Transpile for the selected backend and review two-qubit gate count before execution.
Save job identifiers, backend names, shot counts, and optimization settings with experiment results.

Avoid

Submitting untested circuits directly to hardware before simulator validation.
Using Sampler when the task needs expectation values, or Estimator when the task needs bitstring counts.
Comparing quantum results without recording backend noise, calibration state, shots, and transpilation settings.