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lemma-wrangle

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Mis à jour15 juillet 2026 à 00:47

Reconcile sources into a defensible analytical dataset when grain, keys, definitions, units, authority, extraction, joins, or provenance are uncertain.

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Source

tkpratardan

tkpratardan/lemma

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Métiers associésSOC

Basé sur la classification professionnelle SOC

Scientifiques des donnéesProfessions informatiques et mathématiques·SOC 15-2051

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3 fichiers

SKILL.md

readonly

name	lemma-wrangle
description	Reconcile sources into a defensible analytical dataset when grain, keys, definitions, units, authority, extraction, joins, or provenance are uncertain.

Wrangle and reconcile

Deliver

Produce the requested analytical dataset or result with its output grain, key/definition contract, join or extraction diagnostics, lineage, and unresolved conflicts.

Check

Inventory source ownership, dates, formats, units, row grain, and likely keys. scripts/source_inventory.py is available for complex inventories.
Profile key uniqueness and missingness before joining.
Preserve raw fields; create documented normalized fields.
Measure match rates, unmatched records, row multiplication, duplication, and metric conservation for joins.
Validate parsed or transformed values against representative source examples.

Do not enter this skill merely because several compatible files are used. Do not silently coerce units or keys, permit an unexplained many-to-many join, or drop unmatched records without accounting for them.

For authority matrices and extraction QA, read references/deep-guide.md.

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lemma-leakage

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Audit a dataset or pipeline for the five leakages that inflate a metric: target, preprocessing, temporal, group, and sampling.

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name	lemma-wrangle
description	Reconcile sources into a defensible analytical dataset when grain, keys, definitions, units, authority, extraction, joins, or provenance are uncertain.

Wrangle and reconcile

Deliver

Produce the requested analytical dataset or result with its output grain, key/definition contract, join or extraction diagnostics, lineage, and unresolved conflicts.

Check

Inventory source ownership, dates, formats, units, row grain, and likely keys. scripts/source_inventory.py is available for complex inventories.
Profile key uniqueness and missingness before joining.
Preserve raw fields; create documented normalized fields.
Measure match rates, unmatched records, row multiplication, duplication, and metric conservation for joins.
Validate parsed or transformed values against representative source examples.

For authority matrices and extraction QA, read references/deep-guide.md.