ReddRadar
Agent skill
vqc-trainer
Variational quantum classifier training skill with gradient optimization
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/quantum-computing/skills/vqc-trainer
Metadata
Additional technical details for this skill
- phase
- 6
- domain
- science
- category
- quantum-ml
- specialization
- quantum-computing
SKILL.md
VQC Trainer
Purpose
Provides expert guidance on training variational quantum classifiers, including data encoding, circuit design, and gradient-based optimization.
Capabilities
- Data encoding circuit design
- Variational layer construction
- Gradient-based optimization (SPSA, Adam)
- Cross-validation for QML
- Hyperparameter tuning
- Overfitting detection
- Learning curve analysis
- Ensemble methods
Usage Guidelines
- Data Preparation: Preprocess classical data for quantum encoding
- Encoding Design: Select appropriate data encoding strategy
- Ansatz Design: Build variational circuit with trainable parameters
- Training Setup: Configure optimizer, learning rate, and batch size
- Evaluation: Assess model on test set with proper metrics
Tools/Libraries
- Qiskit Machine Learning
- PennyLane
- TensorFlow Quantum
- PyTorch
- scikit-learn
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
a5c-ai/babysitter
gsd-tools
Central utility skill for GSD operations. Provides config parsing, slug generation, timestamps, path operations, and orchestrates calls to other specialized skills. Acts as the unified entry point that the original gsd-tools.cjs provided via its lib/ modules (commands, config, core, init).
a5c-ai/babysitter
model-profile-resolution
Resolve model profile (quality/balanced/budget) at orchestration start and map agents to specific models. Enables cost/quality tradeoffs by selecting appropriate AI models for each agent role.
a5c-ai/babysitter
verification-suite
Plan structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.
a5c-ai/babysitter
state-management
STATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.
a5c-ai/babysitter
git-integration
Git commit patterns, formats, and conventions for GSD methodology. Provides atomic commits per task, structured commit messages, planning file commits, branch management, and milestone tag operations.
a5c-ai/babysitter
frontmatter-parsing
YAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.
Didn't find tool you were looking for?