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qiskit

Build, simulate, transpile, and execute quantum circuits with Qiskit and IBM Quantum Runtime. Use for Qiskit 2.x circuits and operators, V2 Sampler or Estimator primitives, target-aware transpilation, local or noisy simulation, IBM QPU execution, Runtime sessions or batches, error mitigation, and Qiskit ecosystem packages.

77

Quality

96%

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SKILL.md
Quality
Evals
Security

Quality

Content

92%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.

A well-structured, executable skill body with clear workflows, strong progressive disclosure, and copy-paste-ready examples. The only weakness is minor: inline time-sensitive version pins and a verification date that slightly undercut conciseness.

Suggestions

Move the pinned versions and verification date into references/sources.md (already referenced for pin changes) and keep only a brief 'verified against current 2.x releases; see sources.md' note inline to improve conciseness.

Consider adding an explicit validate-then-retry feedback loop note for the IBM QPU submission step (e.g., check job status / error codes and resubmit) to match the workflow-clarity feedback-loop expectation for batch/QPU operations.

DimensionReasoningScore

Conciseness

Lean and action-oriented with no padding or basic-concept explanations, but the inline verification date and pinned version numbers ('verified on 2026-07-23 against qiskit==2.5.0...') are time-sensitive and not isolated in a deprecated/old-patterns section, per the conciseness guideline.

4 / 5

Actionability

Multiple copy-paste-ready executable examples (local Sampler/Estimator, IBM QPU sampling/estimation, Batch) plus concrete install and script commands cover the common cases fully.

5 / 5

Workflow Clarity

A clear 5-step Core Workflow (Map, Optimize, Apply layout, Execute, Analyze) with an explicit 8-item Final Checklist that provides validation checkpoints and pre-QPU verification, avoiding the destructive/batch cap.

5 / 5

Progressive Disclosure

Clear overview with a well-signaled Reference Map table linking 11 one-level-deep reference files plus 3 bundled scripts, all of which exist in the bundle; content is appropriately split between inline flows and references.

5 / 5

Total

19

/

20

Passed

Description

100%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, third-person description that clearly states capabilities and provides an explicit 'Use for' trigger covering the Qiskit 2.x surface area. It is comprehensive, concrete, and unlikely to fire for the wrong skill.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('Build, simulate, transpile, and execute quantum circuits') spanning the full Qiskit domain with comprehensive coverage of distinct operations.

5 / 5

Completeness

Explicitly answers both 'what' (Build, simulate, transpile, and execute...) and 'when' ('Use for Qiskit 2.x circuits and operators...') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Comprehensive natural term coverage for the domain ('quantum circuits', 'simulate', 'transpile', 'IBM QPU execution', 'error mitigation', 'V2 Sampler or Estimator primitives') including synonyms and API names a Qiskit user would actually say.

5 / 5

Distinctiveness Conflict Risk

Narrow, well-defined niche (Qiskit 2.x, IBM Quantum Runtime, V2 primitives) with distinct triggers and minimal overlap risk with other skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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