{"slug":"k-dense-ai-cirq","name":"cirq","description":"Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.","long_description":"---\nname: cirq\ndescription: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.\nlicense: Apache-2.0 license\nallowed-tools: Read Write Edit Bash\nmetadata:\n  version: \"1.0\"\n  skill-author: K-Dense Inc.\n---\n\n# Cirq - Quantum Computing with Python\n\nCirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators.\n\n## When to Use This Skill\n\nUse this skill when:\n- Building, simulating, or optimizing NISQ circuits in Python\n- Running jobs on Google Quantum AI processors (via `cirq-google`) or partner backends (IonQ, Azure Quantum, AQT, Pasqal)\n- Modeling noise, compiling to hardware gatesets, or designing characterization experiments\n- Using parameter sweeps, transformers, or the ReCirq experiment patterns\n\nFor IBM hardware use **qiskit**; for quantum ML with autodiff use **pennylane**; for physics simulations use **qutip**.\n\n## Installation\n\nRequires Python 3.11+. Current stable release: **1.6.1** (August 2025). Vendor packages share the same version number.\n\n```bash\nuv pip install \"cirq==1.6.1\"\n```\n\nFor hardware integration (pin matching versions for reproducibility):\n```bash\n# Google Quantum Engine (requires approved GCP project access)\nuv pip install \"cirq-google==1.6.1\"\n\n# IonQ\nuv pip install \"cirq-ionq==1.6.1\"\n\n# AQT (Alpine Quantum Technologies)\nuv pip install \"cirq-aqt==1.6.1\"\n\n# Pasqal\nuv pip install \"cirq-pasqal==1.6.1\"\n\n# Azure Quantum (IonQ, Honeywell/Quantinuum backends)\nuv pip install \"azure-quantum[cirq]\"\n```\n\nFor latest features during development, omit version pins; for production or hardware runs, pin all packages to the same Cirq release.\n\n## Quick Start\n\n### Basic Circuit\n\n```python\nimport cirq\nimport numpy as np\n\n# Create qubits\nq0, q1 = cirq.LineQubit.range(2)\n\n# Build circuit\ncircuit = cirq.Circuit(\n    cirq.H(q0),              # Hadamard on q0\n    cirq.CNOT(q0, q1),       # CNOT with q0 control, q1 target\n    cirq.measure(q0, q1, key='result')\n)\n\nprint(circuit)\n\n# Simulate\nsimulator = cirq.Simulator()\nresult = simulator.run(circuit, repetitions=1000)\n\n# Display results\nprint(result.histogram(key='result'))\n```\n\n### Parameterized Circuit\n\n```python\nimport sympy\n\n# Define symbolic parameter\ntheta = sympy.Symbol('theta')\n\n# Create parameterized circuit\ncircuit = cirq.Circuit(\n    cirq.ry(theta)(q0),\n    cirq.measure(q0, key='m')\n)\n\n# Sweep over parameter values\nsweep = cirq.Linspace('theta', start=0, stop=2*np.pi, length=20)\nresults = simulator.run_sweep(circuit, params=sweep, repetitions=1000)\n\n# Process results\nfor params, result in zip(sweep, results):\n    theta_val = params['theta']\n    counts = result.histogram(key='m')\n    print(f\"θ={theta_val:.2f}: {counts}\")\n```\n\n## Core Capabilities\n\n### Circuit Building\nFor comprehensive information about building quantum circuits, including qubits, gates, operations, custom gates, and circuit patterns, see:\n- **[references/building.md](references/building.md)** - Complete guide to circuit construction\n\nCommon topics:\n- Qubit types (GridQubit, LineQubit, NamedQubit)\n- Single and two-qubit gates\n- Parameterized gates and operations\n- Custom gate decomposition\n- Circuit organization with moments\n- Standard circuit patterns (Bell states, GHZ, QFT)\n- Import/export (OpenQASM, JSON)\n- Working with qudits and observables\n\n### Simulation\nFor detailed information about simulating quantum circuits, including exact simulation, noisy simulation, parameter sweeps, and the Quantum Virtual Machine, see:\n- **[references/simulation.md](references/simulation.md)** - Complete guide to quantum simulation\n\nCommon topics:\n- Exact simulation (state vector, density matrix)\n- Sampling and measurements\n- Parameter sweeps (single and multiple parameters)\n- Noisy simulation\n- State histograms and visualization\n- Quantum Virtual Machine (QVM)\n- Expectation values and observables\n- Performance optimization\n\n### Circuit Transformation\nFor information about optimizing, compiling, and manipulating quantum circuits, see:\n- **[references/transformation.md](references/transformation.md)** - Complete guide to circuit transformations\n\nCommon topics:\n- Transformer framework\n- Gate decomposition\n- Circuit optimization (merge gates, eject Z gates, drop negligible operations)\n- Circuit compilation for hardware\n- Qubit routing and SWAP insertion\n- Custom transformers\n- Transformation pipelines\n\n### Hardware Integration\nFor information about running circuits on real quantum hardware from various providers, see:\n- **[references/hardware.md](references/hardware.md)** - Complete guide to hardware integration\n\nSupported providers:\n- **Google Quantum AI** (`cirq-google`) — Sycamore, Weber, Willow processors via Quantum Engine (restricted access; requires approved GCP project)\n- **IonQ** (`cirq-ionq`) — trapped-ion QPUs and simulators\n- **Azure Quantum** (`azure-quantum[cirq]`) — IonQ and Honeywell/Quantinuum backends\n- **AQT** (`cirq-aqt`) — Alpine Quantum Technologies\n- **Pasqal** (`cirq-pasqal`) — neutral-atom devices\n\nTopics include device representation, qubit selection, authentication, job management, and circuit optimization for hardware. See [Access and authentication](https://quantumai.google/cirq/google/access) for Google Cloud setup.\n\n### Noise Modeling\nFor information about modeling noise, noisy simulation, characterization, and error mitigation, see:\n- **[references/noise.md](references/noise.md)** - Complete guide to noise modeling\n\nCommon topics:\n- Noise channels (depolarizing, amplitude damping, phase damping)\n- Noise models (constant, gate-specific, qubit-specific, thermal)\n- Adding noise to circuits\n- Readout noise\n- Noise characterization (randomized benchmarking, XEB)\n- Noise visualization (heatmaps)\n- Error mitigation techniques\n\n### Quantum Experiments\nFor information about designing experiments, parameter sweeps, data collection, and using the ReCirq framework, see:\n- **[references/experiments.md](references/experiments.md)** - Complete guide to quantum experiments\n\nCommon topics:\n- Experiment design patterns\n- Parameter sweeps and data collection\n- ReCirq framework structure\n- Common algorithms (VQE, QAOA, QPE)\n- Data analysis and visualization\n- Statistical analysis and fidelity estimation\n- Parallel data collection\n\n## Common Patterns\n\n### Variational Algorithm Template\n\n```python\nimport scipy.optimize\n\ndef variational_algorithm(ansatz, cost_function, initial_params):\n    \"\"\"Template for variational quantum algorithms.\"\"\"\n\n    def objective(params):\n        circuit = ansatz(params)\n        simulator = cirq.Simulator()\n        result = simulator.simulate(circuit)\n        return cost_function(result)\n\n    # Optimize\n    result = scipy.optimize.minimize(\n        objective,\n        initial_params,\n        method='COBYLA'\n    )\n\n    return result\n\n# Define ansatz\ndef my_ansatz(params):\n    q = cirq.LineQubit(0)\n    return cirq.Circuit(\n        cirq.ry(params[0])(q),\n        cirq.rz(params[1])(q)\n    )\n\n# Define cost function\ndef my_cost(result):\n    state = result.final_state_vector\n    # Calculate cost based on state\n    return np.real(state[0])\n\n# Run optimization\nresult = variational_algorithm(my_ansatz, my_cost, [0.0, 0.0])\n```\n\n### Hardware Execution Template\n\n```python\nimport os\n\ndef run_on_hardware(circuit, provider='google', processor_id=None, repetitions=1000):\n    \"\"\"Template for running on quantum hardware.\"\"\"\n\n    if provider == 'google':\n        import cirq_google as cg\n\n        project_id = os.environ['GOOGLE_CLOUD_PROJECT']\n        engine = cg.Engine(project_id=project_id)\n\n        # List available processors: engine.list_processors()\n        processor_id = processor_id or 'weber'  # use your assigned processor_id\n        sampler = engine.get_sampler(processor_id=processor_id)\n        return sampler.run(circuit, repetitions=repetitions)\n\n    elif provider == 'ionq':\n        import cirq_ionq as ionq\n\n        # Requires IONQ_API_KEY in environment\n        service = ionq.Service()\n        return service.run(circuit, repetitions=repetitions, target='qpu')\n\n    elif provider == 'azure':\n        from azure.quantum.cirq import AzureQuantumService\n\n        service = AzureQuantumService(\n            resource_id=os.environ['AZURE_QUANTUM_RESOURCE_ID'],\n            location=os.environ['AZURE_QUANTUM_LOCATION'],\n        )\n        return service.run(circuit, repetitions=repetitions, target='ionq.qpu')\n\n    else:\n        raise ValueError(f\"Unknown provider: {provider}\")\n```\n\n### Noise Study Template\n\n```python\ndef noise_comparison_study(circuit, noise_levels):\n    \"\"\"Compare circuit performance at different noise levels.\"\"\"\n\n    results = {}\n\n    for noise_level in noise_levels:\n        # Create noisy circuit\n        noisy_circuit = circuit.with_noise(cirq.depolarize(p=noise_level))\n\n        # Simulate\n        simulator = cirq.DensityMatrixSimulator()\n        result = simulator.run(noisy_circuit, repetitions=1000)\n\n        # Analyze\n        results[noise_level] = {\n            'histogram': result.histogram(key='result'),\n            'dominant_state': max(\n                result.histogram(key='result').items(),\n                key=lambda x: x[1]\n            )\n        }\n\n    return results\n\n# Run study\nnoise_levels = [0.0, 0.001, 0.01, 0.05, 0.1]\nresults = noise_comparison_study(circuit, noise_levels)\n```\n\n## Best Practices\n\n1. **Circuit Design**\n   - Use appropriate qubit types for your topology\n   - Keep circuits modular and reusable\n   - Label measurements with descriptive keys\n   - Validate circuits against device constraints before execution\n\n2. **Simulation**\n   - Use state vector simulation for pure states (more efficient)\n   - Use density matrix simulation only when needed (mixed states, noise)\n   - Leverage parameter sweeps instead of individual runs\n   - Monitor memory usage for large systems (2^n grows quickly)\n\n3. **Hardware Execution**\n   - Always test on simulators first\n   - Select best qubits using calibration data\n   - Optimize circuits for target hardware gateset\n   - Implement error mitigation for production runs\n   - Store expensive hardware results immediately\n\n4. **Circuit Optimization**\n   - Start with high-level built-in transformers\n   - Chain multiple optimizations in sequence\n   - Track depth and gate count reduction\n   - Validate correctness after transformation\n\n5. **Noise Modeling**\n   - Use realistic noise models from calibration data\n   - Include all error sources (gate, decoherence, readout)\n   - Characterize before mitigating\n   - Keep circuits shallow to minimize noise accumulation\n\n6. **Experiments**\n   - Structure experiments with clear separation (data generation, collection, analysis)\n   - Use ReCirq patterns for reproducibility\n   - Save intermediate results frequently\n   - Parallelize independent tasks\n   - Document thoroughly with metadata\n\n## Additional Resources\n\n- **Official Documentation**: https://quantumai.google/cirq\n- **API Reference**: https://quantumai.google/reference/python/cirq\n- **Tutorials**: https://quantumai.google/cirq/tutorials\n- **Examples**: https://github.com/quantumlib/Cirq/tree/main/examples\n- **Version policy**: https://quantumai.google/cirq/dev/versions\n- **ReCirq**: https://github.com/quantumlib/ReCirq\n\n## Common Issues\n\n**Circuit too deep for hardware:**\n- Use circuit optimization transformers to reduce depth\n- See `transformation.md` for optimization techniques\n\n**Memory issues with simulation:**\n- Switch from density matrix to state vector simulator\n- Reduce number of qubits or use stabilizer simulator for Clifford circuits\n\n**Device validation errors:**\n- Check qubit connectivity with device.metadata.nx_graph\n- Decompose gates to device-native gateset\n- See `hardware.md` for device-specific compilation\n\n**No","tagline":"Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML ","category":"design-creative","tags":["agent-skill"],"author":"K-Dense-AI","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"recursive skill source sync","sourceDetail":"K-Dense-AI/scientific-agent-skills","creatorName":"K-Dense-AI","creatorUrl":"https://github.com/K-Dense-AI","sourceUrl":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/k-dense-ai-cirq#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. 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issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"6d since push"},{"status":"pass","label":"License clarity","detail":"Apache-2.0 license"},{"status":"pass","label":"README/SKILL.md completeness","detail":"Metadata includes enough usage and workflow context"},{"status":"warn","label":"Dependency/runtime risk","detail":"command execution surface, external package install surface"},{"status":"pass","label":"Install availability","detail":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"warn","label":"Permission surface","detail":"shell or command execution, filesystem or document access"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq"},{"status":"info","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"pass","label":"OpenAgentSkill usage","detail":"10 views, 0 install copies"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Large GitHub adoption signal","Install command has no obvious high-risk pattern","Outcome loop is ready but needs first real agent run"],"warnings":["SKILL.md does not include an explicit limitations or safe operating boundaries section.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access","No real agent outcome reports yet","Human review required before unattended installation"],"evidence":{"stars":"38K GitHub stars","repoActivity":"38K stars, 3.6K forks","lastPushed":"6d since push","license":"Apache-2.0 license","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq","install":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","installSafety":"standard package or runtime install path","permissionSurface":"shell or command execution, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet","agentProvenScore":0,"outcomeConfidence":"0%","installPolicy":"sandbox_only"},"installReadiness":{"ready":true,"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","policy":"sandbox_only","label":"Sandbox only","notes":["Install path is available","Repository evidence is available","License is declared","No Agent Proven outcome evidence yet","6d since push","Trust Score v5 requires review or sandbox-only use before install."]},"agentCompatibility":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"riskSummary":{"level":"medium","label":"Review before production","notes":["SKILL.md does not include an explicit limitations or safe operating boundaries section.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"sandbox_only","reason":"Compare alternatives before installing."},"outcome_loop":{"version":"openagentskill-agent-outcome-v4","required_after_install":true,"endpoint":"/api/agent/outcome","method":"POST","event_id_source":"feedback.event_id, install_receipt.resolve_event_id, or decision_packet.outcome_feedback.event_id","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"required_fields":["event_id","skill_slug","task"],"quality_fields":["task_success","output_quality","error_type","human_review_required","used_in_production","workspace","evidence_url","time_to_useful_ms","source_version"],"ranking_inputs_updated":["Trust Score v5 outcome confidence","Agent Proven Score","Resolve ranking task-fit evidence","Skill detail machine-readable metadata","Outcome leaderboard"]},"agent_contract":{"suited_tasks":["design-creative","agent-skill"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"install_command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","trust_score":67,"trust_version":"trust-score-v5","risk_level":"medium","do_not_use_when":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Live brokerage, exchange, wallet, or payment credentials outside an explicitly approved sandbox"],"before_install":["Read the audit page and machine-readable metadata.","Confirm the install command, license, and permission surface fit the workspace.","Get explicit human approval or choose an alternative before installing."],"after_run":["Report the outcome to /api/agent/outcome using the resolve event id.","Include output_quality, workspace, human_review_required, and evidence_url when available.","Re-resolve before broad production rollout."]},"bestFor":["design-creative","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Live brokerage, exchange, wallet, or payment credentials outside an explicitly approved sandbox"],"knownRisks":["SKILL.md does not include an explicit limitations or safe operating boundaries section.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"],"backward_compatible":{"trust_score_v4":{"version":"trust-score-v4","score":75,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout."}}},"trust_score_v4":{"version":"trust-score-v4","score":75,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout.","recommendedAction":"Test in a sandbox workflow and compare its install path with close alternatives.","dimensions":[{"id":"github_adoption","label":"GitHub adoption","score":100,"weight":0.13,"status":"pass","detail":"38K GitHub stars"},{"id":"repo_activity","label":"Stars/forks activity","score":97,"weight":0.08,"status":"pass","detail":"38K stars, 3.6K forks; issue activity unavailable in current metadata"},{"id":"maintenance","label":"Recent maintenance","score":100,"weight":0.14,"status":"pass","detail":"6d since push"},{"id":"license","label":"License clarity","score":86,"weight":0.09,"status":"pass","detail":"Apache-2.0 license"},{"id":"documentation","label":"README/SKILL.md completeness","score":86,"weight":0.14,"status":"pass","detail":"Metadata includes enough usage and workflow context"},{"id":"dependency_risk","label":"Dependency/runtime risk","score":54,"weight":0.12,"status":"warn","detail":"command execution surface, external package install surface"},{"id":"installability","label":"Install availability","score":92,"weight":0.1,"status":"pass","detail":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq"},{"id":"install_safety","label":"Install command safety","score":92,"weight":0.1,"status":"pass","detail":"standard package or runtime install path"},{"id":"permission_surface","label":"Permission surface","score":48,"weight":0.07,"status":"warn","detail":"shell or command execution, filesystem or document access"},{"id":"repository","label":"Repository evidence","score":86,"weight":0.04,"status":"pass","detail":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq"},{"id":"review_status","label":"Review status","score":66,"weight":0.05,"status":"info","detail":"AI review data available"},{"id":"agent_outcomes","label":"Agent Proven outcomes","score":54,"weight":0.13,"status":"info","detail":"No agent outcome data yet"}],"checks":[{"status":"pass","label":"GitHub adoption","detail":"38K GitHub stars"},{"status":"pass","label":"Stars/forks activity","detail":"38K stars, 3.6K forks; issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"6d since push"},{"status":"pass","label":"License clarity","detail":"Apache-2.0 license"},{"status":"pass","label":"README/SKILL.md completeness","detail":"Metadata includes enough usage and workflow context"},{"status":"warn","label":"Dependency/runtime risk","detail":"command execution surface, external package install surface"},{"status":"pass","label":"Install availability","detail":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"warn","label":"Permission surface","detail":"shell or command execution, filesystem or document access"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq"},{"status":"info","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"pass","label":"OpenAgentSkill usage","detail":"10 views, 0 install copies"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Large GitHub adoption signal","Install command has no obvious high-risk pattern"],"warnings":["SKILL.md does not include an explicit limitations or safe operating boundaries section.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"],"evidence":{"stars":"38K GitHub stars","repoActivity":"38K stars, 3.6K forks","lastPushed":"6d since push","license":"Apache-2.0 license","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq","install":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","installSafety":"standard package or runtime install path","permissionSurface":"shell or command execution, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"installReadiness":{"ready":true,"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","policy":"sandbox_only","label":"Sandbox only","notes":["Install path is available","Repository evidence is available","License is declared","No Agent Proven outcome evidence yet","6d since push"]},"agentCompatibility":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"riskSummary":{"level":"medium","label":"Review before production","notes":["SKILL.md does not include an explicit limitations or safe operating boundaries section.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"sandbox_only","reason":"Human review or sandbox validation is required before automatic installation."},"bestFor":["design-creative","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Live brokerage, exchange, wallet, or payment credentials outside an explicitly approved sandbox"],"knownRisks":["SKILL.md does not include an explicit limitations or safe operating boundaries section.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"outcome_stats":null,"safety":{"score":57,"level":"avoid_auto_install","label":"Avoid automatic install","safety_tier":{"tier":"blocked","label":"Blocked for auto-install","badge":"BLOCKED","summary":"This skill should not be selected by an agent without explicit human security review.","recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","auto_install_policy":"block","reasons":["Audit risk exceeds the requested agent policy","Audit classified this skill as risky","Audit risk risky exceeds max_risk=medium"]},"auto_install_allowed":false,"human_review_required":true,"blocked":true,"audit_risk":"risky","permission_hints":[{"id":"shell","label":"Shell or command execution","reason":"Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.","severity":"high"},{"id":"network","label":"Network access","reason":"Skill likely fetches remote pages, APIs, repositories, or external services.","severity":"medium"},{"id":"filesystem","label":"Filesystem access","reason":"Skill may read or write project files, documents, generated artifacts, or local workspace state.","severity":"medium"}],"policy_warnings":["Audit risk risky exceeds max_risk=medium","High-risk permission hints: Shell or command execution","Dependency or permission surface needs review"],"constraints_applied":{"max_risk":"medium","needs_install_command":true,"min_stars":0}},"safety_gate":{"tier":"blocked","label":"Blocked for auto-install","badge":"BLOCKED","auto_install_policy":"block","auto_install_allowed":false,"blocked":true,"human_review_required":true,"recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","reasons":["Audit risk exceeds the requested agent policy","Audit classified this skill as risky","Audit risk risky exceeds max_risk=medium"]},"eval":{"version":"openagentskill-skill-eval-v1","status":"failed","score":78,"risk_level":"high","decision":{"recommendation":"do_not_auto_install","reason":"Audit score: Risky","auto_install_allowed":false,"policy":"block","human_review_required":true},"blockers":["Audit score: Risky","Agent safety gate: This skill should not be selected by an agent without explicit human security review.","Permission surface: shell or command execution, filesystem or document access"],"warnings":["Trust score: Good trust signals with a few areas worth checking before rollout.","Audit risk risky exceeds max_risk=medium","High-risk permission hints: Shell or command execution","Dependency or permission surface needs review","Permission surface may require sandboxing","Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required","SKILL.md does not include an explicit limitations or safe operating boundaries section.","Hardware integration notes reference cloud credentials but do not warn agents to avoid exposing or committing secrets.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"checks":[{"id":"task_fit","label":"Task fit","status":"pass","score":84,"required_for_auto_install":true,"detail":"Task wording matches this skill metadata.","evidence":["Evaluate cirq before installing it in an agent workflow","design-creative","GitHub automation workflows; Claude Code teams; teams that value GitHub adoption signals"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add K-Dense-AI/scientific-agent-skills --skill cirq"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add K-Dense-AI/scientific-agent-skills --skill cirq"]},{"id":"trust_score","label":"Trust score","status":"warn","score":75,"required_for_auto_install":true,"detail":"Good trust signals with a few areas worth checking before rollout.","evidence":["Strong shortlist","38K GitHub stars","Apache-2.0 license"]},{"id":"audit_score","label":"Audit score","status":"fail","score":85,"required_for_auto_install":true,"detail":"Risky","evidence":["Dependency or permission surface needs review"]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"fail","score":57,"required_for_auto_install":true,"detail":"This skill should not be selected by an agent without explicit human security review.","evidence":["Do not auto-install. Inspect the source, dependencies, and permission surface first.","Audit risk exceeds the requested agent policy"]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"pass","score":86,"required_for_auto_install":false,"detail":"Metadata includes enough usage and workflow context","evidence":["Strong README/SKILL.md context"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"Apache-2.0 license","evidence":["Apache-2.0 license"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"6d since push","evidence":["6d since push"]},{"id":"permission_surface","label":"Permission surface","status":"fail","score":48,"required_for_auto_install":true,"detail":"shell or command execution, filesystem or document access","evidence":["Shell or command execution: high","Network access: medium","Filesystem access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/k-dense-ai-cirq/evals","api":"/api/agent/evals?slug=k-dense-ai-cirq","text":"/api/agent/evals?slug=k-dense-ai-cirq&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"k-dense-ai-cirq","name":"cirq","description":"Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.","category":"design-creative","url":"https://www.openagentskill.com/skills/k-dense-ai-cirq","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq","github_repo":"K-Dense-AI/scientific-agent-skills"},"suited_tasks":["GitHub automation workflows","Claude Code teams","teams that value GitHub adoption signals","Inspect repository metadata","Compare code changes","Write concise engineering summaries","Chunk documents","Create embeddings"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add k-dense-ai-cirq"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"cirq\" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cirq\",\"task\":\"Install cirq\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"cirq\" as a Claude Code skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cirq\",\"task\":\"Install cirq\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"cirq\" from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cirq\",\"task\":\"Install cirq\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/k-dense-ai-cirq/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-cirq"},"trust":{"score":75,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"sandbox_only","evidence":{"stars":"38K GitHub stars","repoActivity":"38K stars, 3.6K forks","lastPushed":"6d since push","license":"Apache-2.0 license","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq","install":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","installSafety":"standard package or runtime install path","permissionSurface":"shell or command execution, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","agent-skill"],"known_risks":["SKILL.md does not include an explicit limitations or safe operating boundaries section.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":85,"risk_level":"risky","risk_label":"Risky","warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required","SKILL.md does not include an explicit limitations or safe operating boundaries section.","Hardware integration notes reference cloud credentials but do not warn agents to avoid exposing or committing secrets.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface"]},"safety_gate":{"tier":"blocked","label":"Blocked for auto-install","auto_install_policy":"block","auto_install_allowed":false,"human_review_required":true,"blocked":true,"recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first."},"quality":{"score":92,"label":"Excellent"},"supply":{"track":"Design and creative production","scenario":"Design and creative","maintenance":"6d since push","risk":"Risky"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","SKILL.md does not include an explicit limitations or safe operating boundaries section.","Audit risk risky exceeds max_risk=medium","High-risk permission hints: Shell or command execution","Dependency or permission surface needs review","Permission surface may require sandboxing","Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required"],"agent_contract":{"task_input":"Use cirq in an agent workflow","recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","install_policy":"block","minimum_review_before_use":["Trust: 75/100 Strong shortlist","Audit: 85/100 Risky","Safety: 57/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"k-dense-ai-cirq (cirq)","install_command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","risk_summary":"Risky; Blocked for auto-install; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"k-dense-ai-cirq","task":"Use cirq in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/k-dense-ai-cirq","api":"https://www.openagentskill.com/api/agent/skills/k-dense-ai-cirq","audit":"https://www.openagentskill.com/skills/k-dense-ai-cirq/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=k-dense-ai-cirq&task=Use%20cirq%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20cirq%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20cirq%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/k-dense-ai-cirq/install","manifest":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-cirq"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"k-dense-ai-cirq","name":"cirq","description":"Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.","category":"design-creative","url":"https://www.openagentskill.com/skills/k-dense-ai-cirq","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq","github_repo":"K-Dense-AI/scientific-agent-skills"},"suited_tasks":["GitHub automation workflows","Claude Code teams","teams that value GitHub adoption signals","Inspect repository metadata","Compare code changes","Write concise engineering summaries","Chunk documents","Create embeddings"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add k-dense-ai-cirq"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"cirq\" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cirq\",\"task\":\"Install cirq\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"cirq\" as a Claude Code skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cirq\",\"task\":\"Install cirq\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"cirq\" from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cirq\",\"task\":\"Install cirq\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/k-dense-ai-cirq/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-cirq"},"trust":{"score":75,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"sandbox_only","evidence":{"stars":"38K GitHub stars","repoActivity":"38K stars, 3.6K forks","lastPushed":"6d since push","license":"Apache-2.0 license","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq","install":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","installSafety":"standard package or runtime install path","permissionSurface":"shell or command execution, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","agent-skill"],"known_risks":["SKILL.md does not include an explicit limitations or safe operating boundaries section.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":85,"risk_level":"risky","risk_label":"Risky","warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required","SKILL.md does not include an explicit limitations or safe operating boundaries section.","Hardware integration notes reference cloud credentials but do not warn agents to avoid exposing or committing secrets.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface"]},"safety_gate":{"tier":"blocked","label":"Blocked for auto-install","auto_install_policy":"block","auto_install_allowed":false,"human_review_required":true,"blocked":true,"recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first."},"quality":{"score":92,"label":"Excellent"},"supply":{"track":"Design and creative production","scenario":"Design and creative","maintenance":"6d since push","risk":"Risky"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","SKILL.md does not include an explicit limitations or safe operating boundaries section.","Audit risk risky exceeds max_risk=medium","High-risk permission hints: Shell or command execution","Dependency or permission surface needs review","Permission surface may require sandboxing","Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required"],"agent_contract":{"task_input":"Use cirq in an agent workflow","recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","install_policy":"block","minimum_review_before_use":["Trust: 75/100 Strong shortlist","Audit: 85/100 Risky","Safety: 57/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"k-dense-ai-cirq (cirq)","install_command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","risk_summary":"Risky; Blocked for auto-install; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"k-dense-ai-cirq","task":"Use cirq in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/k-dense-ai-cirq","api":"https://www.openagentskill.com/api/agent/skills/k-dense-ai-cirq","audit":"https://www.openagentskill.com/skills/k-dense-ai-cirq/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=k-dense-ai-cirq&task=Use%20cirq%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20cirq%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20cirq%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/k-dense-ai-cirq/install","manifest":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-cirq"}},"supply_profile":{"track":{"slug":"design","label":"Design and creative production","shortLabel":"Design","description":"Design assets, images, video, audio, multimodal media, presentation, and creative production skills."},"scenario":{"label":"Design and creative","description":"I need my agent to produce design assets, UI directions, presentations, or creative media workflows.","useCases":[{"slug":"github-automation","title":"GitHub automation"},{"slug":"rag-knowledge","title":"RAG and knowledge"},{"slug":"browser-automation","title":"Browser automation"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":38487,"starsLabel":"38K","forks":3607,"license":"Apache-2.0 license","qualityScore":92,"trustScore":75,"auditScore":85},"maintenance":{"status":"fresh","label":"6d since push","daysSincePush":6,"lastPushedAt":"2026-08-30T13:19:27+00:00"},"risk":{"level":"risky","label":"Risky","requiresReview":true,"notes":["Dependency or permission surface needs review","Permission surface may require sandboxing","Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required","SKILL.md does not include an explicit limitations or safe operating boundaries section.","Hardware integration notes reference cloud credentials but do not warn agents to avoid exposing or committing secrets."]},"coverageTags":["Design","Design and creative","design-creative","agent-skill"]},"audit":{"audit_score":85,"risk_level":"risky","risk_label":"Risky","quality_score":92,"trust_score":75,"maintenance_score":100,"security_score":75,"install_score":92,"warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required","SKILL.md does not include an explicit limitations or safe operating boundaries section.","Hardware integration notes reference cloud credentials but do not warn agents to avoid exposing or committing secrets.","This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"quality_signals":{"model":"v2","star_score":32.1,"usage_score":0,"review_score":5.25,"metadata_score":3,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"github-automation","title":"GitHub automation","url":"https://www.openagentskill.com/use-cases/github-automation"},{"slug":"rag-knowledge","title":"RAG and knowledge","url":"https://www.openagentskill.com/use-cases/rag-knowledge"},{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"},{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"}],"stacks":[{"slug":"rag-knowledge-base","title":"RAG knowledge base","url":"https://www.openagentskill.com/collections/rag-knowledge-base"},{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"},{"slug":"frontend-product-ui","title":"Frontend and UI","url":"https://www.openagentskill.com/collections/frontend-product-ui"}],"install":"npx skills add K-Dense-AI/scientific-agent-skills --skill cirq","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add k-dense-ai-cirq","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"cirq\" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cirq\",\"task\":\"Install cirq\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"cirq\" as a Claude Code skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cirq\",\"task\":\"Install cirq\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"cirq\" from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cirq\",\"task\":\"Install cirq\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq","github_repo":"K-Dense-AI/scientific-agent-skills","version":"1.0.0","license":"Apache-2.0 license","urls":{"web":"https://www.openagentskill.com/skills/k-dense-ai-cirq","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cirq","api":"/api/agent/skills/k-dense-ai-cirq","install_api":"/api/skills/k-dense-ai-cirq/install"},"meta":{"created_at":"2026-08-30T13:24:12.502813+00:00","updated_at":"2026-09-01T11:59:28.941454+00:00","agent_friendly":true}}