quantum-qiskit
quantum-qiskit is a Physics, mathematics & simulation skill for AI agents, published by aiming-lab in the AutoResearchClaw repository on GitHub. Skillspace rates quantum-qiskit D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Reference qiskit 2.x patterns for variational quantum machine learning. Covers data-encoding feature maps, variational quantum classifier (VQC) training, variational quantum eigensolver (VQE) for chemistry, matrix-product-state circuits, and noise model integration. Use when writing Python code that imports `qiskit`, `qiskit_aer`, `qiskit_algorithms`, `qiskit_machine_learning`, or `qiskit_nature`.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 13,814
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 1 other repositories, in 1 collections
- Scope
- Vendor-specific: built around one product. Reference for the public qiskit library ecosystem
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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