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modules/reporting-engine/fixtures/semantic_layer/retail_monthly.semantic.json
33.6 KB · Oct 3, 2026 · 06:30 UTC
{
"schema_version": "0.3",
"semantic_layer_id": "retail_monthly.reporting_semantics",
"semantic_version": 1,
"dataset_contract": {
"dataset_contract_id": "retail_monthly",
"contract_version": 1,
"identity": {
"method": "caller_assigned",
"value": "fixture.retail_monthly"
},
"origin_snapshot": {
"profile_schema_version": "0.4",
"snapshot_fingerprint": "18e4481730ada16b90f9adef037b3b2776547801b40a2ed6489416f4700fd3d3"
},
"unknown_column_policy": "allow_as_unclassified_extension"
},
"scope": {
"title": "Synthetic monthly retail reporting semantics",
"business_area": "Synthetic retail performance",
"purpose": "Define reviewed canonical business-metric mappings, metric, dimension, period, and analysis-validity semantics for the packaged Reporting Engine fixture.",
"coverage_level": "strong",
"included_subjects": [
"sales and units performance",
"margin-rate analysis",
"average selling price",
"monthly current-versus-prior comparison",
"brand, category, region, and SKU analysis"
],
"excluded_subjects": [
"cohort lifecycle",
"funnel conversion",
"root-cause hierarchy",
"set membership",
"structured financial statements"
]
},
"sources": [
{
"source_id": "source.dataset_profile",
"source_type": "dataset_profile",
"locator": "generated profile for fixtures/semantic_layer/retail_monthly.csv",
"authority": "mechanical",
"supports": [
"physical columns",
"types and cardinality",
"mechanical metric, dimension, and period candidates"
],
"caveats": [
"The profile does not establish business meaning or analysis validity."
],
"last_checked": "2026-07-18"
},
{
"source_id": "source.fixture_notes",
"source_type": "data_dictionary",
"locator": "fixtures/semantic_layer/retail_monthly_source_notes.md",
"authority": "canonical",
"supports": [
"row grain",
"metric definitions and aggregation",
"canonical business metric mappings and role absence",
"dimension meaning",
"period scope",
"reviewed analysis rules"
],
"caveats": [
"The source describes a synthetic test fixture, not a real business."
],
"last_checked": "2026-07-28"
}
],
"evidence": [
{
"evidence_id": "evidence.dataset_profile",
"source_id": "source.dataset_profile",
"locator": "dataset profile root",
"claim": "The referenced physical fields and mechanical role candidates exist in the profiled dataset.",
"confidence": "high",
"status": "supported",
"notes": [
"Mechanical evidence does not approve a business interpretation."
]
},
{
"evidence_id": "evidence.grain_and_period",
"source_id": "source.fixture_notes",
"locator": "Grain And Scope",
"claim": "Each row is one SKU-brand observation for one calendar month; current YTD and aligned prior-year YTD are valid reusable period rules.",
"confidence": "high",
"status": "supported",
"notes": []
},
{
"evidence_id": "evidence.sales",
"source_id": "source.fixture_notes",
"locator": "Metrics / Sales",
"claim": "Sales is additive net invoiced sales in US dollars.",
"confidence": "high",
"status": "supported",
"notes": []
},
{
"evidence_id": "evidence.units",
"source_id": "source.fixture_notes",
"locator": "Metrics / Units",
"claim": "Units is additive sold unit volume.",
"confidence": "high",
"status": "supported",
"notes": []
},
{
"evidence_id": "evidence.margin_rate",
"source_id": "source.fixture_notes",
"locator": "Metrics / MarginRate",
"claim": "MarginRate is non-additive and must be aggregated as a sales-weighted mean.",
"confidence": "high",
"status": "supported",
"notes": []
},
{
"evidence_id": "evidence.average_selling_price",
"source_id": "source.fixture_notes",
"locator": "Metrics / Average selling price",
"claim": "Average selling price is sum(Sales) divided by sum(Units) for the selected scope.",
"confidence": "high",
"status": "supported",
"notes": []
},
{
"evidence_id": "evidence.dimensions",
"source_id": "source.fixture_notes",
"locator": "Dimensions",
"claim": "Brand, Category, Region, and SKU have the documented reporting and entity roles.",
"confidence": "high",
"status": "supported",
"notes": [
"Brand and SKU are redundant as simultaneous decomposition dimensions in this fixture."
]
},
{
"evidence_id": "evidence.analysis_rules",
"source_id": "source.fixture_notes",
"locator": "Reviewed Analysis Rules",
"claim": "The listed time, ranking, mix, relationship, distribution, and PVM analyses are supported; funnel, statement, cohort, set, and root-cause analyses are not established.",
"confidence": "high",
"status": "supported",
"notes": []
},
{
"evidence_id": "evidence.business_metric_roles",
"source_id": "source.fixture_notes",
"locator": "Canonical Business Metric Roles",
"claim": "Sales is the canonical Sales metric; the dataset contains no separate Discount or COGS measure.",
"confidence": "high",
"status": "supported",
"notes": [
"MarginRate does not establish a separately reported COGS amount."
]
}
],
"business_metric_mappings": {
"sales": {
"state": "mapped",
"metric_id": "metric.sales",
"candidate_metric_ids": [],
"confidence": "high",
"rationale": "The canonical fixture notes identify net invoiced Sales as this dataset contract's Sales role.",
"evidence_ids": [
"evidence.business_metric_roles",
"evidence.sales"
],
"caveats": [
"The mapped role is net invoiced sales, not a gross-sales measure."
]
},
"discount": {
"state": "absent",
"metric_id": null,
"candidate_metric_ids": [],
"confidence": "high",
"rationale": "The canonical fixture notes establish that the dataset contains no separate Discount amount or rate.",
"evidence_ids": [
"evidence.business_metric_roles"
],
"caveats": [
"Do not reconstruct Discount from already-net Sales."
]
},
"cogs": {
"state": "absent",
"metric_id": null,
"candidate_metric_ids": [],
"confidence": "high",
"rationale": "The canonical fixture notes establish that the dataset contains no COGS or cost-of-sales measure.",
"evidence_ids": [
"evidence.business_metric_roles"
],
"caveats": [
"MarginRate alone does not establish a separately reported COGS amount."
]
}
},
"metrics": [
{
"metric_id": "metric.sales",
"label": "Sales",
"binding": {
"binding_type": "column",
"column": "Sales",
"expression": null,
"input_metric_ids": []
},
"definition": "Net invoiced sales value at the monthly SKU-brand row grain.",
"metric_class": "additive_value",
"aggregation": {
"default": "sum",
"allowed": [
"sum"
],
"forbidden": [
"unweighted_mean"
],
"weight_metric_id": null
},
"unit": {
"kind": "currency",
"currency": "USD",
"symbol": "$"
},
"directionality": "descriptive_increase",
"valid_period_grains": [
"month",
"quarter",
"year",
"ytd"
],
"compatible_dimension_ids": [
"dimension.brand",
"dimension.category",
"dimension.region",
"dimension.sku"
],
"forbidden_dimension_ids": [],
"status": "defined",
"confidence": "high",
"rationale": "The canonical fixture notes define Sales as additive USD value.",
"evidence_ids": [
"evidence.sales"
],
"caveats": [
"An increase is descriptive; the fixture does not assert that it is always favorable."
],
"origin_profile_observation": {
"source_role": "metric",
"metric_class": "additive_value",
"aggregation": "sum",
"confidence": "high",
"inference_reasons": [
"name suggests additive value"
]
}
},
{
"metric_id": "metric.units",
"label": "Units",
"binding": {
"binding_type": "column",
"column": "Units",
"expression": null,
"input_metric_ids": []
},
"definition": "Sold unit volume at the monthly SKU-brand row grain.",
"metric_class": "additive_volume",
"aggregation": {
"default": "sum",
"allowed": [
"sum"
],
"forbidden": [
"unweighted_mean"
],
"weight_metric_id": null
},
"unit": {
"kind": "count",
"currency": null,
"symbol": null
},
"directionality": "descriptive_increase",
"valid_period_grains": [
"month",
"quarter",
"year",
"ytd"
],
"compatible_dimension_ids": [
"dimension.brand",
"dimension.category",
"dimension.region",
"dimension.sku"
],
"forbidden_dimension_ids": [],
"status": "defined",
"confidence": "high",
"rationale": "The canonical fixture notes define Units as additive sold volume.",
"evidence_ids": [
"evidence.units"
],
"caveats": [],
"origin_profile_observation": {
"source_role": "metric",
"metric_class": "additive_volume",
"aggregation": "sum",
"confidence": "high",
"inference_reasons": [
"name suggests additive volume"
]
}
},
{
"metric_id": "metric.sales_per_units",
"label": "Sales_per_Units",
"binding": {
"binding_type": "derived",
"column": null,
"expression": "sum(Sales) / sum(Units)",
"input_metric_ids": [
"metric.sales",
"metric.units"
]
},
"definition": "Average selling price for the selected scope, calculated as the ratio of aggregate sales to aggregate units.",
"metric_class": "rate",
"aggregation": {
"default": "ratio_of_sums",
"allowed": [
"ratio_of_sums"
],
"forbidden": [
"sum",
"unweighted_mean_of_row_ratios"
],
"weight_metric_id": "metric.units"
},
"unit": {
"kind": "currency_per_unit",
"currency": "USD",
"symbol": "$/unit"
},
"directionality": "descriptive_increase",
"valid_period_grains": [
"month",
"quarter",
"year",
"ytd"
],
"compatible_dimension_ids": [
"dimension.brand",
"dimension.category",
"dimension.region",
"dimension.sku"
],
"forbidden_dimension_ids": [],
"status": "defined",
"confidence": "high",
"rationale": "The source notes define average selling price as a ratio of sums, correcting the profiler's generic derived-rate candidate into a reviewed metric.",
"evidence_ids": [
"evidence.average_selling_price"
],
"caveats": [
"Requires non-zero aggregate units in the selected scope."
],
"origin_profile_observation": {
"source_role": "derived_metric",
"metric_class": "derived_rate",
"aggregation": "derived_from_value_and_volume",
"confidence": "medium",
"inference_reasons": [
"additive value metric divided by additive volume metric"
]
}
},
{
"metric_id": "metric.marginrate",
"label": "MarginRate",
"binding": {
"binding_type": "column",
"column": "MarginRate",
"expression": null,
"input_metric_ids": []
},
"definition": "Gross margin divided by sales at the monthly SKU-brand row grain.",
"metric_class": "rate",
"aggregation": {
"default": "weighted_mean",
"allowed": [
"weighted_mean"
],
"forbidden": [
"sum",
"unweighted_mean"
],
"weight_metric_id": "metric.sales"
},
"unit": {
"kind": "percentage",
"currency": null,
"symbol": "%"
},
"directionality": "descriptive_increase",
"valid_period_grains": [
"month",
"quarter",
"year",
"ytd"
],
"compatible_dimension_ids": [
"dimension.brand",
"dimension.category",
"dimension.region",
"dimension.sku"
],
"forbidden_dimension_ids": [],
"status": "defined",
"confidence": "high",
"rationale": "The canonical source defines MarginRate and its sales-weighted aggregation rule.",
"evidence_ids": [
"evidence.margin_rate"
],
"caveats": [
"Do not sum rates or use an unweighted mean across unequal sales values."
],
"origin_profile_observation": {
"source_role": "metric",
"metric_class": "rate",
"aggregation": "semantic_layer_defined",
"confidence": "high",
"inference_reasons": [
"name suggests price, rate, or ratio"
]
}
}
],
"dimensions": [
{
"dimension_id": "dimension.brand",
"label": "Brand",
"column": "Brand",
"definition": "Commercial brand used for reporting and aggregation.",
"semantic_type": "entity",
"valid_uses": [
"group",
"filter",
"panel",
"point"
],
"hierarchy_parent_id": "dimension.category",
"status": "defined",
"confidence": "high",
"rationale": "The source notes define Brand as a reporting dimension grouped by Category.",
"evidence_ids": [
"evidence.dimensions"
],
"caveats": [
"Brand and SKU are one-to-one in this fixture and must not be treated as independent decomposition axes."
],
"origin_profile_observation": {
"source_role": "dimension",
"confidence": "high",
"distinct_count": 4,
"cardinality_class": "low"
}
},
{
"dimension_id": "dimension.category",
"label": "Category",
"column": "Category",
"definition": "Product category grouping brands into Color and Care.",
"semantic_type": "categorical",
"valid_uses": [
"group",
"filter",
"panel",
"composition"
],
"hierarchy_parent_id": null,
"status": "defined",
"confidence": "high",
"rationale": "The canonical source defines Category as a brand grouping.",
"evidence_ids": [
"evidence.dimensions"
],
"caveats": [],
"origin_profile_observation": {
"source_role": "dimension",
"confidence": "high",
"distinct_count": 2,
"cardinality_class": "low"
}
},
{
"dimension_id": "dimension.region",
"label": "Region",
"column": "Region",
"definition": "Reporting geography for North and South.",
"semantic_type": "geography",
"valid_uses": [
"group",
"filter",
"panel",
"composition"
],
"hierarchy_parent_id": null,
"status": "defined",
"confidence": "high",
"rationale": "The canonical source defines Region as a reporting geography that cross-classifies Category.",
"evidence_ids": [
"evidence.dimensions"
],
"caveats": [],
"origin_profile_observation": {
"source_role": "dimension",
"confidence": "high",
"distinct_count": 2,
"cardinality_class": "low"
}
},
{
"dimension_id": "dimension.sku",
"label": "SKU",
"column": "SKU",
"definition": "Stock-keeping-unit identifier for the observation entity.",
"semantic_type": "identifier",
"valid_uses": [
"filter",
"detail",
"point"
],
"hierarchy_parent_id": "dimension.brand",
"status": "defined",
"confidence": "high",
"rationale": "The canonical source defines SKU as the row entity under Brand.",
"evidence_ids": [
"evidence.dimensions"
],
"caveats": [
"One SKU per brand makes SKU redundant with Brand in this fixture."
],
"origin_profile_observation": {
"source_role": "identifier",
"confidence": "high",
"distinct_count": 4,
"cardinality_class": "low"
}
}
],
"periods": [
{
"period_id": "period.date",
"label": "Calendar month",
"column": "Date",
"definition": "The calendar month represented by the row; stored as the first day of that month.",
"grain": "month",
"calendar": "gregorian",
"timezone": null,
"status": "defined",
"confidence": "high",
"rationale": "The source notes define Date as a calendar-month key rather than a transaction timestamp.",
"evidence_ids": [
"evidence.grain_and_period"
],
"caveats": [
"Display month labels, not the literal first-day storage convention."
],
"origin_profile_observation": {
"confidence": "high",
"grain": "month"
}
}
],
"period_rules": [
{
"period_rule_id": "period_rule.all_available",
"label": "All available calendar months",
"period_id": "period.date",
"rule_type": "all_available",
"scope_type": "all_available",
"parameters": {
"window_length": null,
"fiscal_year_start_month": 1,
"comparison_offset_years": 1,
"requires_runtime_bounds": false
},
"status": "defined",
"confidence": "high",
"rationale": "Ordered monthly trajectory and composition analyses may use the complete available snapshot range.",
"evidence_ids": [
"evidence.grain_and_period"
],
"caveats": [
"The concrete start and end are resolved from each snapshot."
]
},
{
"period_rule_id": "period_rule.current_ytd",
"label": "Current calendar year to latest available month",
"period_id": "period.date",
"rule_type": "current_ytd",
"scope_type": "single",
"parameters": {
"window_length": null,
"fiscal_year_start_month": 1,
"comparison_offset_years": 1,
"requires_runtime_bounds": false
},
"status": "defined",
"confidence": "high",
"rationale": "Current-period ranking, relationship, distribution, and composition analyses use calendar YTD through the latest available month.",
"evidence_ids": [
"evidence.grain_and_period"
],
"caveats": [
"The snapshot supplies the current year and latest available month."
]
},
{
"period_rule_id": "period_rule.current_ytd_vs_prior_ytd",
"label": "Current calendar YTD versus aligned prior-year YTD",
"period_id": "period.date",
"rule_type": "current_ytd_vs_prior_ytd",
"scope_type": "comparison_pair",
"parameters": {
"window_length": null,
"fiscal_year_start_month": 1,
"comparison_offset_years": 1,
"requires_runtime_bounds": false
},
"status": "defined",
"confidence": "high",
"rationale": "Current and prior periods must cover aligned calendar months and are resolved from the latest available snapshot month.",
"evidence_ids": [
"evidence.grain_and_period"
],
"caveats": [
"The comparison is unavailable when the snapshot lacks aligned prior-year history."
]
}
],
"analysis_policies": [
{
"analysis_id": "analysis.monthly_sales_trajectory",
"label": "Monthly sales trajectory",
"question_family": "How did total sales move across the available calendar months?",
"analysis_task_ids": [
"time_and_period_movement"
],
"selection_emphases": [
"single_metric_trend_shape"
],
"validity": "valid",
"business_purpose": "Inspect the ordered monthly path of total sales.",
"role_bindings": {
"period_axis": {
"binding_type": "concept",
"concept_id": "period.date"
},
"primary_metric": {
"binding_type": "concept",
"concept_id": "metric.sales"
}
},
"period_rule_id": "period_rule.all_available",
"conditions": [
"Aggregate Sales by calendar month before rendering."
],
"rationale": "Sales is additive and Date is a reviewed ordered monthly axis.",
"evidence_ids": [
"evidence.sales",
"evidence.grain_and_period",
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": [
"Only four months are present, so seasonality cannot be inferred."
]
},
{
"analysis_id": "analysis.sales_current_vs_prior_by_month",
"label": "Current versus prior sales by month",
"question_family": "Where were the monthly sales gaps between the reviewed current and prior-year windows?",
"analysis_task_ids": [
"time_and_period_movement"
],
"selection_emphases": [
"compact_side_by_side_period_comparison"
],
"validity": "valid",
"business_purpose": "Compare January and February sales with the same months in the prior year.",
"role_bindings": {
"period_axis": {
"binding_type": "concept",
"concept_id": "period.date"
},
"comparison_metric": {
"binding_type": "concept",
"concept_id": "metric.sales"
}
},
"period_rule_id": "period_rule.current_ytd_vs_prior_ytd",
"conditions": [
"Align months by calendar month number within the two reviewed windows."
],
"rationale": "The metric is additive and the source defines equal current and prior-year month windows.",
"evidence_ids": [
"evidence.sales",
"evidence.grain_and_period",
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": []
},
{
"analysis_id": "analysis.current_brand_sales_ranking",
"label": "Current brand sales ranking",
"question_family": "Which brands generated the most sales in the reviewed current period?",
"analysis_task_ids": [
"ranking_and_comparison"
],
"selection_emphases": [
"ranked_single_metric_comparison"
],
"validity": "valid",
"business_purpose": "Rank brands by current calendar-YTD sales through the snapshot's latest month.",
"role_bindings": {
"primary_metric": {
"binding_type": "concept",
"concept_id": "metric.sales"
},
"category": {
"binding_type": "concept",
"concept_id": "dimension.brand"
}
},
"period_rule_id": "period_rule.current_ytd",
"conditions": [
"Sum Sales by Brand within the current scope."
],
"rationale": "Brand is a reviewed grouping dimension and Sales is additive.",
"evidence_ids": [
"evidence.sales",
"evidence.dimensions",
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": []
},
{
"analysis_id": "analysis.category_sales_mix_over_time",
"label": "Category sales mix over time",
"question_family": "How did total sales and category composition change across months?",
"analysis_task_ids": [
"composition_and_mix",
"time_and_period_movement"
],
"selection_emphases": [
"composition_change_over_periods"
],
"validity": "valid",
"business_purpose": "Show monthly total sales together with Color and Care contribution.",
"role_bindings": {
"period_axis": {
"binding_type": "concept",
"concept_id": "period.date"
},
"primary_metric": {
"binding_type": "concept",
"concept_id": "metric.sales"
},
"component_dimension": {
"binding_type": "concept",
"concept_id": "dimension.category"
}
},
"period_rule_id": "period_rule.all_available",
"conditions": [
"Sum Sales by calendar month and Category."
],
"rationale": "Sales is additive and Category is a reviewed composition dimension.",
"evidence_ids": [
"evidence.sales",
"evidence.dimensions",
"evidence.grain_and_period",
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": []
},
{
"analysis_id": "analysis.brand_sales_margin_relationship",
"label": "Brand sales and margin relationship",
"question_family": "Which current-period brands combine higher sales with higher or lower margin rate?",
"analysis_task_ids": [
"metric_relationship"
],
"selection_emphases": [
"relationship_between_two_metrics"
],
"validity": "valid",
"business_purpose": "Compare current-period brand scale with sales-weighted margin rate.",
"role_bindings": {
"x_metric": {
"binding_type": "concept",
"concept_id": "metric.sales"
},
"y_metric": {
"binding_type": "concept",
"concept_id": "metric.marginrate"
},
"point_dimension": {
"binding_type": "concept",
"concept_id": "dimension.brand"
}
},
"period_rule_id": "period_rule.current_ytd",
"conditions": [
"Create one point per Brand.",
"Sum Sales by Brand and calculate MarginRate as a Sales-weighted mean."
],
"rationale": "The source explicitly supports a Brand-level sales-versus-margin relationship after reviewed aggregation.",
"evidence_ids": [
"evidence.sales",
"evidence.margin_rate",
"evidence.dimensions",
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": [
"The four-point fixture is illustrative and cannot establish statistical association."
]
},
{
"analysis_id": "analysis.brand_sales_margin_units_bubble",
"label": "Brand sales, margin, and units bubble view",
"question_family": "How do current brands compare on sales, margin rate, and unit scale?",
"analysis_task_ids": [
"metric_relationship"
],
"selection_emphases": [
"two_metric_relationship_plus_size"
],
"validity": "valid",
"business_purpose": "Add current unit scale to the Brand sales-versus-margin relationship.",
"role_bindings": {
"x_metric": {
"binding_type": "concept",
"concept_id": "metric.sales"
},
"y_metric": {
"binding_type": "concept",
"concept_id": "metric.marginrate"
},
"size_metric": {
"binding_type": "concept",
"concept_id": "metric.units"
},
"point_dimension": {
"binding_type": "concept",
"concept_id": "dimension.brand"
}
},
"period_rule_id": "period_rule.current_ytd",
"conditions": [
"Create one point per Brand.",
"Aggregate Sales and Units by sum and MarginRate by Sales-weighted mean."
],
"rationale": "Sales, Units, MarginRate, and Brand have compatible reviewed semantics for a scoped entity-level relationship.",
"evidence_ids": [
"evidence.sales",
"evidence.units",
"evidence.margin_rate",
"evidence.dimensions",
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": [
"Bubble area is descriptive magnitude, not a fourth causal claim."
]
},
{
"analysis_id": "analysis.margin_rate_distribution",
"label": "Margin-rate distribution",
"question_family": "What is the distribution shape of row-level margin rates across the available brand-month observations?",
"analysis_task_ids": [
"distribution"
],
"selection_emphases": [
"frequency_shape"
],
"validity": "valid",
"business_purpose": "Inspect spread and concentration of observed row-level margin rates.",
"role_bindings": {
"distribution_metric": {
"binding_type": "concept",
"concept_id": "metric.marginrate"
}
},
"period_rule_id": "period_rule.all_available",
"conditions": [
"Use the sixteen row-level brand-month observations without aggregating MarginRate first."
],
"rationale": "MarginRate is a numeric observation at the documented row grain and the question explicitly concerns that observation distribution.",
"evidence_ids": [
"evidence.margin_rate",
"evidence.grain_and_period",
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": [
"The sample is small; a smoothed density interpretation is not approved."
]
},
{
"analysis_id": "analysis.sales_price_volume_mix",
"label": "Sales price-volume-mix decomposition",
"question_family": "How did the sales change between the reviewed current and prior-year windows decompose into price, volume, and mix effects?",
"analysis_task_ids": [
"variance_and_bridge"
],
"selection_emphases": [
"pvm_decomposition_comparison"
],
"validity": "valid",
"business_purpose": "Decompose the comparable-window sales movement using additive value and volume semantics.",
"role_bindings": {
"period_filter": {
"binding_type": "concept",
"concept_id": "period.date"
},
"value_metric": {
"binding_type": "concept",
"concept_id": "metric.sales"
},
"volume_metric": {
"binding_type": "concept",
"concept_id": "metric.units"
}
},
"period_rule_id": "period_rule.current_ytd_vs_prior_ytd",
"conditions": [
"Use identical Brand-SKU population and equal calendar-month windows.",
"Derive price as the ratio of aggregate Sales to aggregate Units at the required decomposition grain."
],
"rationale": "The source defines compatible additive value, additive volume, derived price, and comparable period windows.",
"evidence_ids": [
"evidence.sales",
"evidence.units",
"evidence.average_selling_price",
"evidence.grain_and_period",
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": [
"The fixture supports a mechanical example; business interpretation of mix effects remains context-dependent."
]
},
{
"analysis_id": "analysis.category_region_sales_composition",
"label": "Category and region sales composition",
"question_family": "How is current sales distributed jointly across Region and Category?",
"analysis_task_ids": [
"composition_and_mix"
],
"selection_emphases": [
"two_dimension_share_and_size"
],
"validity": "valid",
"business_purpose": "Show current sales size and composition across two cross-classifying dimensions.",
"role_bindings": {
"primary_metric": {
"binding_type": "concept",
"concept_id": "metric.sales"
},
"width_category": {
"binding_type": "concept",
"concept_id": "dimension.region"
},
"stack_category": {
"binding_type": "concept",
"concept_id": "dimension.category"
}
},
"period_rule_id": "period_rule.current_ytd",
"conditions": [
"Sum Sales by Region and Category within the current scope."
],
"rationale": "Region and Category cross-classify in the fixture and Sales is additive.",
"evidence_ids": [
"evidence.sales",
"evidence.dimensions",
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": [
"Do not substitute Brand and SKU as the two dimensions because they are redundant in this fixture."
]
},
{
"analysis_id": "analysis.structured_statement",
"label": "Structured statement reporting",
"question_family": "Show a structured financial statement with line items and scenarios.",
"analysis_task_ids": [
"evidence_and_reporting_tables"
],
"selection_emphases": [
"structured_statement_values"
],
"validity": "invalid",
"business_purpose": "Record that the dataset cannot support a statement table despite containing numeric values.",
"role_bindings": {},
"period_rule_id": null,
"conditions": [],
"rationale": "The source explicitly states that no statement structure, statement line, or scenario semantics are present.",
"evidence_ids": [
"evidence.analysis_rules"
],
"confidence": "high",
"caveats": [
"A different prepared package with reviewed statement roles would require a separate semantic layer or revision."
]
}
],
"open_questions": [],
"review": {
"status": "human_reviewed",
"reviewed_by": "Reporting Engine fixture author",
"reviewed_at": "2026-07-28",
"notes": [
"Review applies only to the synthetic fixture and its canonical source notes.",
"Contract validation proves wiring, not the truth of semantic judgments in another dataset."
]
},
"boundaries": {
"semantic_judgment_owner": "model_or_human_review",
"deterministic_validation_scope": "Schema, identifiers, evidence references, business-metric mapping references, profile bindings, manifest intent references, and required role coverage only.",
"chart_selection_included": false,
"rendering_included": false
}
}
SHA-256: 50f4f3082a216e790ca85593023961d4a790195c814927806b4bfdeacbfac1fb