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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.

64

Quality

81%

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SKILL.md
Quality
Evals
Security

Quality

Content

78%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Well-structured content with excellent progressive disclosure — all eight referenced files exist and are one level deep — and mostly executable examples. Weaknesses are modest: duplicated content (Pattern 1 vs. First Circuit, marketing stats, dual navigation) and a VQE pattern with undefined variables.

Suggestions

Delete Pattern 1 (it duplicates the First Circuit Quick Start verbatim) and drop the unverifiable marketing stats ('83x faster', '13M+ downloads').

Make the VQE pattern self-contained by defining or stubbing ansatz, hamiltonian, and initial_params, or explicitly label it as a skeleton requiring the patterns.md reference.

Collapse either the per-section 'Topics covered' lists or the Workflow Decision Guide into a single navigation scheme to save tokens.

DimensionReasoningScore

Conciseness

Largely efficient and assumes Claude's competence — no explanations of basic quantum concepts — but contains trimmable material: marketing stats ('83x faster transpilation than competitors', '13M+ downloads'), Pattern 1 duplicating the First Circuit example verbatim, and a Workflow Decision Guide that repeats the section pointers already given. Not 3 because the padding is minor and structural rather than conceptual over-explanation; not 5 because the redundancy is systematic.

4 / 5

Actionability

Install commands and the Bell-state Quick Start are fully executable, and Pattern 2 (hardware execution with transpilation) is copy-paste ready. Below 5 because Pattern 3 (VQE) references undefined variables (ansatz, hamiltonian, backend, initial_params), making it a fragment rather than runnable code.

4 / 5

Workflow Clarity

The four-step Qiskit Patterns workflow (Map, Optimize, Execute, Post-process), the numbered Development Workflow, and pre-flight checkpoints ('Test with noisy simulators before hardware', 'Check backend status before submitting') give a clear sequence. Below 5 because there are no explicit validate→fix→retry feedback loops around job submission or variational convergence.

4 / 5

Progressive Disclosure

The body is a true overview (quick start, brief capability summaries, best practices) pointing to eight verified one-level-deep reference files, each clearly signaled with 'See references/x.md', topic lists, and a decision guide for navigation. Matches the clear-overview anchor.

5 / 5

Total

17

/

20

Passed

Description

78%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description with explicit trigger guidance and excellent competitor disambiguation that minimizes conflict risk. Its main weakness is the thin 'what' side — it identifies the domain but never states the concrete actions the framework performs.

Suggestions

Replace the vague 'Best for ... enterprise quantum computing' clause with concrete actions, e.g. 'Build quantum circuits, transpile for hardware, execute with primitives, and visualize results.'

Add common natural trigger phrasings such as 'quantum circuits', 'quantum simulator', or 'run on quantum hardware' to the 'Use when' clause.

DimensionReasoningScore

Specificity

Names several specific capability areas — 'targeting IBM Quantum hardware', 'Qiskit Runtime for production workloads', 'quantum error mitigation' — though they are framed as use-contexts rather than concrete actions, and 'enterprise quantum computing' is vague filler. Below 5 because the action list is not comprehensive; above 3 because it goes well beyond naming 1-2 actions.

4 / 5

Completeness

Explicitly answers 'when' with a 'Use when...' clause covering three triggers plus 'Best for' scenarios, but the 'what' is thin — 'IBM quantum computing framework' identifies the domain without stating what it does (build circuits, transpile, execute, analyze). Not 5 because the what-side lacks concrete capability statements.

4 / 5

Trigger Term Quality

Good natural keyword coverage: 'IBM Quantum', 'Qiskit Runtime', 'quantum error mitigation', 'hardware execution', plus explicit competitor names (cirq, pennylane, qutip) that serve as routing triggers. Not 5 because common user phrasings like 'quantum circuit', 'quantum simulator', or 'run on quantum hardware' are missing.

4 / 5

Distinctiveness Conflict Risk

Clear niche (IBM Quantum ecosystem) with explicit disambiguation ('For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip'), making wrong-skill triggering very unlikely.

5 / 5

Total

17

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository

synthetic-sciences/openscience

Path

backend/cli/skills/quantum/qiskit/SKILL.md

Reviewed

Table of Contents

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