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name: lexiflow_direct_search description: Run a bounded randomized direct-search loop that samples paired directions, updates by targeted lexicographic comparisons, and tracks the best historical point.

LexiFlow Direct Search

Use this skill when implementing or auditing the LexiFlow paper mechanism for bounded recovery or reusable optimization tooling. Do not use it as a generic scalarized multi-objective optimizer; it assumes priority-ordered minimization objectives, optional goals, and non-negative tolerances.

Inputs

• Continuous bounded search space
• Callable objective function returning priority-ordered minimization objectives
• Goals, tolerances, seed, budget, and step-size settings

Outputs

• Best configuration and objectives
• Evaluation history
• Update/rejection trace with target vectors

Workflow

1. Confirm objective values are ordered by priority and are minimization values.
2. Preserve the paper mechanism described in the module document rather than replacing it with weighted scalarization.
3. Run the companion script or import its pure functions for deterministic behavior.
4. Save command outputs, trace files, and metrics when the skill is used in a recovery experiment.

Validation

Run python scripts/lexiflow_direct_search.py --self-test when available, then run the bundled test command through the Distiller skill-tree validator.

Limitations

This generated skill is source-repository independent and derived from the paper text. Full HPO benchmark reproduction still requires real model training stacks and datasets; the included scripts are intended for deterministic mechanism validation and bounded proxy recovery.