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Map a MetricFlow semantic_model or metric into ktx semantic layer sources. Covers the MetricFlow to ktx primitive table, `extends:` inheritance flattening, metric-type handling (simple / derived / ratio / cumulative / conversion), `model: ref('x')` resolution, and four worked examples. Load when the turn contains `.yml`/`.yaml` files with top-level `semantic_models:` or `metrics:`.
Passed 15 of 21 test cases with the skill, and 9 of 21 without it.
and 5 more in the full report
6 fixed10 passed either way7 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
Show how source provenance is tracked at the top of a generated semantic layer file derived from raw-sources/conn-1/models/orders.yml lines 1 through 15.
| Checked | Without skill | With skill |
|---|---|---|
| The provenance string uses HTML comment syntax containing the file path and line range. | Missed | Passed |
The instructions your model reads when the skill loads.
A MetricFlow semantic_model maps to an SL source; MetricFlow measures map to ktx measures; MetricFlow entities map to ktx joins; MetricFlow metrics (top-level) map to ktx measures OR to cross-model derived measures. Files in one WorkUnit are ALWAYS part of the same logical entity (a connected component, possibly spanning extends: + cross-model metric refs). Flatten inheritance and cross-file references at write time.
| MetricFlow | ktx form | Notes |
|---|---|---|
semantic_model: X { model: ref('t') } with measures + dimensions | Overlay named X with measures, computed-only columns, column_overrides, joins | The model: ref resolves to a manifest table. |
semantic_model: X { model: source('s','t') } | Overlay named X over table t. | Same shape; source() still resolves to a physical table. |
semantic_model: X { model: <literal> } with no manifest entry | Standalone with explicit sql:, grain:, columns: | Happens when the dbt manifest isn't available. |
semantic_model: Y { extends: X } | Merge Y's measures/dimensions/entities into X's overlay, or write a single overlay named for the most-derived child (Y) containing both X's and Y's primitives | Do not emit a second overlay for X - flatten. |
measures: [{ name, agg, expr }] | measures: [{ name, expr: "<agg>(<expr>)" }] | Aggregation inlined. agg: count_distinct → count(distinct ...). |
entities: [{ name, type: primary }] | grain: [<entity_name-or-expr>] on the overlay/standalone | Primary/unique entities drive grain. |
entities: [{ name, type: foreign }] | joins: entry joining to the primary-entity's semantic_model | Only when a matching primary is discoverable. |
metrics: [{ type: simple, type_params: { measure: X } }] | If the base measure is labeled/described by the metric: in-place edit to the existing measure. Otherwise leave as-is. | Same-name metrics can absorb metadata. |
metrics: [{ type: simple, filter: <jinja> }] | New measure on the same source, with the filter translated to SQL and attached via filter: | Translate Jinja {{ Dimension('x__y') }} to the column name y. |
metrics: [{ type: derived, type_params: { expr, metrics } }] | Derived measure on whichever source owns the referenced measures, with expr: referencing measure names | If the metric spans models, still write it once on the source owning the "primary" measure (the one the agent judges most central). Mention the cross-model chain in the description. |
metrics: [{ type: ratio, type_params: { numerator, denominator } }] | Same as derived; expr: "numerator / NULLIF(denominator, 0)" if no explicit expr | Safe-division by default. |
metrics: [{ type: cumulative, type_params: { window, grain_to_date } }] | Standalone source with a window-function SQL; reference the resulting column as a normal measure | ktx SL has no first-class cumulative primitive (spec Non-goals). |
metrics: [{ type: conversion }] | Flag for human - do NOT write. Emit a wiki note describing the intended semantics. | No ktx equivalent in v1. |
| Metric not mappable | Wiki page <metric_name>-definition.md with the full YAML body quoted | Capture the intent even if we can't emit SL. |
Type map: MetricFlow time to ktx time; categorical to string; number to number; boolean to boolean. Follow expr over name when both differ - expr is the physical column.
Verify each MetricFlow model source table with entity_details before producing the corresponding sl_write_source.
Before writing a wiki page or SL source on any topic:
discover_data({query: "<topic>"}) - see what wikis, SL sources, and raw
tables already exist. Prefer updating existing pages over creating new ones.Before emitting any schema.table or schema.table.column into a wiki body,
SL source, tables: frontmatter, sl_refs, or emit_unmapped_fallback:
entity_details({connectionId, targets: [{display: "<identifier>"}]}) -
confirm the identifier resolves; inspect native types, FK/PK, andtest cases passed, vs 9 / 21 without
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