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lemma-describe

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UpdatedJuly 15, 2026 at 00:47

Rigor for descriptive and diagnostic analytics (what happened and why): denominators, grain, and confounded slices, not model leakage.

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tkpratardan

tkpratardan/lemma

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Data ScientistsComputer and Mathematical Occupations·SOC 15-2051

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SKILL.md

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name	lemma-describe
description	Rigor for descriptive and diagnostic analytics (what happened and why): denominators, grain, and confounded slices, not model leakage.
homepage	https://github.com/tkpratardan/lemma
license	MIT

Describe and answer

When to use

Use this skill when a descriptive question needs a multi-step decomposition or competing explanations. The root contract covers bounded calculations.

Deliver

Return the requested number, list, table, or diagnostic with its observation unit or denominator, population, and time boundary. Put the complete result in chat and stop when it and its material caveats are supported.

Check

Confirm the relevant schema, units, grain, and definitions from the source.
Check duplicates, missing values, and denominator changes that could alter the result.
For comparisons, align populations and periods. For changes, distinguish volume from rate or mix.
Test one alternative interpretation when wording or semantics are ambiguous.

Use lemma-wrangle only when a reconciliation conflict prevents calculation. Do not fit a model or imply causality from a slice.

For complex decompositions, read references/deep-guide.md.

More from this repository

same repository

lemma-baseline

tkpratardan/lemma

Establish a dumb baseline and an honest validation harness before any real model, so every later number means something.

2026-07-154

lemma-causal

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Rigor for causal questions and A/B tests (the effect of acting on X): confounding, post-treatment bias, valid control groups.

2026-07-154

lemma-eda

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EDA kickoff for a fresh dataset: fixed opening scaffold (goal, imports, load, sanity), then chapters derived from the data; scan leakage, land a baseline.

2026-07-154

lemma-inference

tkpratardan/lemma

Rigor for statistical inference (is the difference real): hypothesis tests, power, multiple comparisons, effect size over p-value.

2026-07-154

lemma-leakage

tkpratardan/lemma

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

2026-07-154

lemma-model

tkpratardan/lemma

Final modeling once the baseline and feature set are locked: tune against validation, audit overfitting, touch the test set once, justify the complexity.

2026-07-154

name	lemma-describe
description	Rigor for descriptive and diagnostic analytics (what happened and why): denominators, grain, and confounded slices, not model leakage.
homepage	https://github.com/tkpratardan/lemma
license	MIT

Describe and answer

When to use

Use this skill when a descriptive question needs a multi-step decomposition or competing explanations. The root contract covers bounded calculations.

Deliver

Check

Confirm the relevant schema, units, grain, and definitions from the source.
Check duplicates, missing values, and denominator changes that could alter the result.
For comparisons, align populations and periods. For changes, distinguish volume from rate or mix.
Test one alternative interpretation when wording or semantics are ambiguous.

Use lemma-wrangle only when a reconciliation conflict prevents calculation. Do not fit a model or imply causality from a slice.

For complex decompositions, read references/deep-guide.md.