---

name: configuration-preprocessing description: "Inspect, choose, generate, and debug LimiX inference configs and preprocessing transforms." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

LimiX configuration and preprocessing router

Use this sub-skill when the task is to choose, validate, generate, or debug a LimiX inference configuration JSON or the preprocessing blocks that a config enables.

Do not use this sub-skill to run the model end to end. Full checkpoint inference needs a local LimiX checkpoint and may require CUDA/GPU; this sub-skill only covers configuration and preprocessing decisions.

Route by intent

• Need to call LimiXPredictor, prepare x_train/y_train/x_test, inspect outputs, or use missing-value imputation? Load ../predictor-inference/SKILL.md.
• Need to run the benchmark-style classification/regression CLI over dataset directories? Load ../benchmark-cli/SKILL.md.
• Need retrieval search, Optuna tuning, attention-map semantics, or retrieval-parameter trade-offs? Load ../retrieval-optimization/SKILL.md.
• Need to inspect whether a JSON config is valid, CPU-safe, retrieval-enabled, MVI-compatible, or likely to fail in preprocessing? Continue here.

Operating checklist

1. Pick the nearest catalog config from references/config-catalog.md by task, model size, retrieval use, and MVI need.
2. For CPU or low-memory work, prefer non-retrieval configs; LimiX rejects retrieval configs on CPU and retrieval inference can be GPU-memory heavy.
3. Validate user-supplied JSON with scripts/inspect_config.py before using it in a predictor or benchmark command.
4. If no config file exists, generate a safe no-retrieval baseline with scripts/generate_noretrieval_config.py, then inspect it.
5. When a preprocessing failure mentions constant/all-NaN features, category encoding, power transforms, one-hot size, KDI, Hyperopt, or malformed config keys, use references/troubleshooting.md.

Bundled references and scripts

• references/config-catalog.md: observed config matrix, config-list schema, helper-generated configs, and CPU/retrieval caveats.
• references/preprocessing-reference.md: transform order, class behavior, key options, data implications, and failure modes.
• references/troubleshooting.md: actionable fixes for malformed configs and preprocessing/runtime errors.
• scripts/inspect_config.py: standalone JSON validator and config summarizer.
• scripts/generate_noretrieval_config.py: standalone no-retrieval config generator.