qiskit
IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.
87
81%
Does it follow best practices?
Impact
99%
1.39xAverage score across 3 eval scenarios
Passed
No known issues
Evaluation results
100%
28%Quantum State Characterization Tools
V2 primitives and result access
uv installation
0%
100%
StatevectorSampler import
0%
100%
StatevectorEstimator import
0%
100%
Sampler result access
100%
100%
Estimator result access
100%
100%
No V1 quasi_dists usage
100%
100%
No measurements in Estimator circuits
100%
100%
SparsePauliOp observables
100%
100%
Sampler for bitstrings
100%
100%
Estimator for expectation values
100%
100%
100%
8%Circuit Optimization Benchmark Report
Transpilation analysis and optimization
uv installation
0%
100%
optimization_level=3 used
100%
100%
Fixed transpiler seed
100%
100%
Circuit depth measurement
100%
100%
Gate count measurement
100%
100%
Two-qubit gate count
100%
100%
All four optimization levels
100%
100%
JSON results saved
100%
100%
transpile() function used
100%
100%
Metrics printed
100%
100%
No deprecated V1 result access
100%
100%
98%
48%Variational Ground State Energy Finder
Qiskit Patterns VQE workflow
uv installation
0%
60%
StatevectorEstimator used
0%
100%
No Sampler for energy
100%
100%
SparsePauliOp Hamiltonian
0%
100%
No measurements in ansatz
70%
100%
V2 result access
0%
100%
COBYLA optimizer
100%
100%
Convergence tracking
100%
100%
JSON output saved
100%
100%
Four-stage structure
80%
100%
Parameterized circuit with assign_parameters
0%
100%
- Repository
- K-Dense-AI/claude-scientific-skills
- Commit
b58ad7e
- Evaluated
- Agent
- Claude Code
- Model
- Claude Sonnet 4.6
Table of Contents
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