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fix(sl): stop baking drift-prone counts into overlay summaries (#270)
The auto-generated semantic-layer overlay description embedded measure/segment/column counts that were computed once and never recomputed, so the summary drifted and misreported its source after measures were later appended. Make the auto fallback count-free, since those counts are already rendered live from the body at `ktx sl list`/ `read` time; this removes the drift class without ever overwriting human-authored descriptions (the fill-only-when-empty guard is untouched). Adds a regression test that fails on main and passes after the fix, plus guards for description preservation and the no-measures fallback.
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2c18a62de4
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2 changed files with 77 additions and 16 deletions
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@ -50,13 +50,6 @@ function humanizeIdentifier(value: string): string {
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.toLowerCase();
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}
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function formatCount(count: number, singular: string, plural = `${singular}s`): string | null {
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if (count <= 0) {
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return null;
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}
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return `${count} ${count === 1 ? singular : plural}`;
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}
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function sourceFallback(source: Record<string, unknown>, sourceName: string): string {
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const table = cleanText(source.table);
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const sql = cleanText(source.sql);
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@ -66,15 +59,10 @@ function sourceFallback(source: Record<string, unknown>, sourceName: string): st
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if (sql) {
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return `Semantic-layer source for ${sourceName} backed by curated SQL.`;
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}
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const counts = [
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formatCount(Array.isArray(source.measures) ? source.measures.length : 0, 'measure'),
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formatCount(Array.isArray(source.segments) ? source.segments.length : 0, 'segment'),
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formatCount(Array.isArray(source.columns) ? source.columns.length : 0, 'computed column'),
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].filter((item): item is string => Boolean(item));
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return counts.length > 0
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? `Semantic-layer overlay for ${sourceName} defining ${counts.join(', ')}.`
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: `Semantic-layer overlay for ${sourceName}.`;
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// Measure/segment/column counts are rendered live from the body at list/read
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// time, so baking them into stored prose freezes a derived value that drifts
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// as the source later gains measures. Keep the auto fallback count-free.
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return `Semantic-layer overlay for ${sourceName}.`;
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}
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function columnFallback(column: Record<string, unknown>, sourceName: string): string {
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@ -0,0 +1,73 @@
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import { describe, expect, it } from 'vitest';
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import { normalizeSemanticLayerDescriptions } from '../../../src/context/sl/description-normalization.js';
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/**
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* Build an overlay-shaped source (no `table`/`sql`) so the overlay fallback
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* branch is exercised. Measure/segment counts are derived from array length, so
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* the element contents are irrelevant to the summary.
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*/
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function overlaySource(measureCount: number, segmentCount = 0): Record<string, unknown> {
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return {
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name: 'mart_customer_health',
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measures: Array.from({ length: measureCount }, (_, i) => ({ name: `m${i}`, expr: 'count(*)' })),
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segments: Array.from({ length: segmentCount }, (_, i) => ({ name: `s${i}`, expr: 'true' })),
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};
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}
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function ktxSummary(source: Record<string, unknown>): string | undefined {
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const descriptions = source.descriptions;
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if (descriptions && typeof descriptions === 'object' && !Array.isArray(descriptions)) {
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const ktx = (descriptions as Record<string, unknown>).ktx;
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return typeof ktx === 'string' ? ktx : undefined;
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}
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return undefined;
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}
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describe('normalizeSemanticLayerDescriptions', () => {
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it('stores a count-free overlay summary so the count cannot drift', () => {
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const normalized = normalizeSemanticLayerDescriptions(overlaySource(4, 3), { fillMissing: true });
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// The live count is rendered from the body at list/read time; it must not be
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// frozen into the stored prose, where it would silently go stale.
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expect(ktxSummary(normalized)).toBe('Semantic-layer overlay for mart_customer_health.');
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});
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it('does not keep a stale measure count after measures are appended', () => {
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// First ingest pass writes the auto summary for a 4-measure overlay.
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const first = normalizeSemanticLayerDescriptions(overlaySource(4, 3), { fillMissing: true });
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// A later ingest/reconcile pass appends 2 measures to the same source (now 6)
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// and re-normalizes — exactly what sl_edit_source does with fillMissing.
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(first.measures as unknown[]).push({ name: 'm4', expr: 'count(*)' }, { name: 'm5', expr: 'count(*)' });
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const second = normalizeSemanticLayerDescriptions(first, { fillMissing: true });
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expect(ktxSummary(second)).not.toMatch(/4 measures/);
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});
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it('never overwrites a human-authored user description across re-normalization', () => {
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const input: Record<string, unknown> = {
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...overlaySource(4),
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descriptions: { user: 'Health score per account, owned by RevOps.' },
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};
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const authored = normalizeSemanticLayerDescriptions(input, { fillMissing: true });
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expect(authored.descriptions).toEqual({ user: 'Health score per account, owned by RevOps.' });
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(authored.measures as unknown[]).push({ name: 'm4', expr: 'count(*)' });
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const again = normalizeSemanticLayerDescriptions(authored, { fillMissing: true });
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expect(again.descriptions).toEqual({ user: 'Health score per account, owned by RevOps.' });
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});
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it('never overwrites an authored ktx description even when it resembles the auto summary', () => {
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const input: Record<string, unknown> = {
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...overlaySource(2),
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descriptions: { ktx: 'Curated overlay notes for the health mart.' },
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};
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const authored = normalizeSemanticLayerDescriptions(input, { fillMissing: true });
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expect(ktxSummary(authored)).toBe('Curated overlay notes for the health mart.');
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});
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it('still produces a sensible fallback for a source with no measures', () => {
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const normalized = normalizeSemanticLayerDescriptions({ name: 'mart_empty' }, { fillMissing: true });
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expect(ktxSummary(normalized)).toBe('Semantic-layer overlay for mart_empty.');
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});
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});
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