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mapping_explanation_diagnostics

mapping_explanation_diagnostics

Diagnose visual-prompt label-mapping instability, precision, and concept-overlap explanations.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentación de la Skill

GitHub

name: mapping_explanation_diagnostics description: Diagnose visual-prompt label-mapping instability, precision, and concept-overlap explanations.

Mapping Explanation Diagnostics

Use this skill after fixed FLM or ILM-VP has produced one or more target-to-source mappings. It explains whether mappings changed, stabilized, and share target/source visual attributes.

Inputs

  • Initial and final mappings or a mapping history.
  • Optional descriptor dictionaries for target and source labels.
  • Optional metrics for fixed and iterative runs.

Outputs

  • Changed-class count.
  • Adjacent mapping stability.
  • Per-pair shared attributes and explanation text.
  • Accuracy/loss improvement summary.

Workflow

  1. Normalize mapping history.
  2. Compare initial and final mappings.
  3. Compute adjacent stability across epochs.
  4. Join target/source descriptors and list shared concepts.
  5. Report diagnostics separately from metric claims.

Validation

Run python tests/test_mapping_diagnostics.py or validate_skill_tree.py --run-tests.

Limitations

Descriptor overlap is an explanation aid, not proof of correctness. It should be combined with recovery metrics and mechanism checks.

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