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name: parameter_transform_adapter description: Apply scalar Stan-style constrained and unconstrained transforms with support checks and log-Jacobian values for bounded real parameters.

Parameter Transform Adapter

Use this skill when a Stan parameter contract must be converted between constrained model coordinates and unconstrained inference coordinates. Do not use it to evaluate likelihoods or gradients.

Inputs

• Parameter contract containing name, lower, and upper.
• Numeric value in constrained or unconstrained coordinates.

Outputs

• JSON-compatible result with mapped value, validity, diagnostic message, and log absolute Jacobian.

Workflow

1. Load or define the scalar parameter contract.
2. Use scripts/parameter_transforms.py for constrain, unconstrain, and roundtrip operations.
3. Reject constrained values outside support instead of silently clipping.
4. Pass only valid transformed values to score-model evaluators.

Validation

Run python tests/test_parameter_transforms.py from this skill directory.

Limitations

This skill supports univariate finite-interval real parameters, which is sufficient for the Bernoulli recovery proxy. Extend it before applying to vectors, simplexes, ordered vectors, or covariance matrices.