Calibration Analyzer
SkillDev toolsHardware calibration data analysis skill for optimal qubit selection
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Calibration Analyzer skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/quantum-computing/skills/calibration-analyzer/SKILL.md and read by ahel’s review.
Purpose
Provides expert guidance on analyzing quantum hardware calibration data to select optimal qubits and gate configurations for circuit execution.
Capabilities
- T1/T2 coherence analysis
- Gate error rate parsing
- Readout error analysis
- Crosstalk characterization
- Qubit quality ranking
- Temporal calibration tracking
- Error budget calculation
- Calibration drift detection
Usage Guidelines
- Data Retrieval: Fetch latest calibration data from backend
- Metric Extraction: Parse T1, T2, gate fidelities, and readout errors
- Quality Ranking: Score qubits based on weighted metrics
- Selection: Choose optimal qubits for circuit execution
- Monitoring: Track calibration changes over time
Tools/Libraries
- Qiskit IBMQ Provider
- Cirq-Google
- Amazon Braket SDK
- Pandas
- Matplotlib
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
calibration-analyzer- Source
- github.com/a5c-ai/babysitter