CtrlK
BlogDocsLog inGet started
Tessl Logo

cirq

Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators.

46

Quality

50%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/cirq/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

61%Scale 1-5

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

This is a well-structured skill that provides good executable examples and clear progressive disclosure to reference files. Its main weaknesses are moderate verbosity (especially in the best practices and common topics lists that largely state things Claude would already know) and the lack of explicit validation/verification steps in the workflow templates, particularly for hardware execution which is an expensive operation.

Suggestions

Add explicit validation checkpoints to the hardware execution template (e.g., validate circuit against device constraints, verify qubit connectivity before submission)

Trim the 'Common topics' bullet lists under each reference section—these are redundant with the reference files and add ~40 lines of low-value content

Reduce the best practices section to only non-obvious, Cirq-specific advice rather than general software engineering wisdom Claude already knows

DimensionReasoningScore

Conciseness

The skill is moderately efficient but includes some unnecessary verbosity. The 'Common topics' bullet lists under each reference section are somewhat redundant given they point to reference files. The best practices section, while useful, contains advice Claude likely already knows (e.g., 'keep circuits modular and reusable', 'document thoroughly with metadata'). The hardware execution template with multiple provider branches is lengthy.

3 / 5

Actionability

The skill provides executable code examples for core use cases: basic circuits, parameterized circuits, variational algorithms, noise studies, and hardware execution. The code is copy-paste ready with proper imports. Minor gaps exist—the variational algorithm cost function is somewhat contrived, and the hardware template has incomplete Azure setup ('# Setup workspace...').

4 / 5

Workflow Clarity

The skill provides templates and patterns but lacks explicit validation checkpoints. For hardware execution—a potentially expensive/destructive operation—there's no validation step (e.g., validate circuit against device constraints before submitting). The best practices mention 'always test on simulators first' and 'validate circuits against device constraints' but these aren't integrated into the workflow templates as explicit steps.

3 / 5

Progressive Disclosure

The skill has good structure with a clear overview, quick start, and well-signaled references to six separate reference files (building.md, simulation.md, transformation.md, hardware.md, noise.md, experiments.md). Each reference section clearly describes what it covers. Minor issue: no bundle files were provided to verify these references exist, and the 'Common topics' bullet lists under each section add bulk that could be trimmed since the reference files presumably cover these.

4 / 5

Total

14

/

20

Passed

Description

39%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.

The description reads more like a tagline or product summary than a skill description optimized for selection. It identifies the domain (Cirq/quantum circuits) but lacks concrete actions, natural trigger terms, and critically has no 'Use when...' clause to guide skill selection. The specificity to Google's Cirq framework provides some distinctiveness but the description needs significant improvement to function well in a multi-skill selection context.

Suggestions

Add a 'Use when...' clause with trigger terms like 'Use when the user asks about Cirq, quantum circuits, quantum gates, qubits, quantum simulation, or Google Quantum AI.'

List specific concrete actions such as 'create quantum circuits with qubits and gates, simulate circuit execution, visualize measurement results, optimize gate sequences, and interface with Google quantum hardware.'

Include natural synonyms and related terms users might say, such as 'quantum computing,' 'quantum programming,' 'quantum algorithms,' 'Hadamard gate,' 'CNOT,' or 'quantum noise simulation.'

DimensionReasoningScore

Specificity

Names the domain (quantum circuits, Cirq framework) but the actions listed are very high-level and generic: 'designing, simulating, and running quantum circuits.' No concrete actions like 'create qubits,' 'apply gates,' 'measure results,' or 'optimize circuits' are mentioned.

2 / 5

Completeness

Provides a vague 'what' (designing, simulating, running quantum circuits) but has no 'when' clause at all. There is no explicit guidance on when Claude should select this skill, which caps this dimension per the rubric guidelines.

2 / 5

Trigger Term Quality

Includes relevant keywords like 'Cirq,' 'quantum circuits,' 'quantum computers,' and 'simulators,' but misses natural user phrases like 'quantum computing,' 'qubits,' 'quantum gates,' 'Google quantum,' or 'quantum simulation.' The term 'Google Quantum AI' is helpful but niche.

3 / 5

Distinctiveness Conflict Risk

Cirq is a specific framework, and the quantum computing domain is fairly niche, making it mostly distinct. However, it could overlap with other quantum computing skills (e.g., Qiskit, PennyLane) since the description doesn't clearly differentiate Cirq-specific capabilities.

4 / 5

Total

11

/

20

Passed

Validation

81%

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

Validation9 / 11 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

9

/

11

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.