Semantic Model

Semantic models: design, build, refresh, review

Guidance for designing, building, refreshing, and reviewing Power BI / Analysis Services tabular models from the terminal. It consolidates model review with modeling best practices, and routes every change to the narrowest capable tool. Depth lives in references/; this file is the operating loop and the routing.

When to use

• Designing or building a model: star schema, relationships, measures, calculation groups, roles, parameters, storage modes, incremental refresh
• Optimizing a model: size / VertiPaq, DAX correctness, Direct Lake, refresh cost
• Reviewing or auditing a model against quality, performance, and best-practice standards
• Preparing a model for Copilot / AI consumption

When NOT to use

• Editing report visuals, pages, or formatting: use the pbir-cli skill (reports plugin)
• Isolated DAX query performance tuning: use the dax skill
• TMDL file syntax mechanics: use the tmdl skill (this skill routes to it for the file-edit fallback)
• The te command surface itself: the te-cli skill (tabular-editor plugin) is the command reference; this skill is the modeling judgment layered on top

Tool cascade (the core operating rule)

Reach for the narrowest capable tool, in order. Most edits never leave step 1.

1. te CLI first. One verb per operation, staged in memory until --save, with a save-time DAX + referential-integrity gate. Covers add/set/rm/mv for measures, columns, relationships (Sales[K]->Dim[K] shorthand on te add), roles + RLS filters, calculation groups / items, incremental-refresh policy, te format, te bpa, te vertipaq, te query. Each Bash call is a fresh shell, so pass -m <model> (and -s/-d for remote) on every command, or set TE_SESSION. Read the real object's settable surface first with te get <obj> and te set <obj> -q <prop> (no value). The te-cli skill is the full command reference.
2. TOM, or a model MCP, when te cannot reach a property. Some properties are absent from te set -q (for example alternateOf, securityFilteringBehavior, crossFilteringBehavior, KPI sub-objects, linguistic-schema content, calendar objects). Drive these through a te script C# pass (in-process TOM), or the connect-pbid skill (PowerShell + TOM/ADOMD against a live local Desktop instance, and the only route to traces: EVALUATEANDLOG, aggregation-hit events, storage DMVs). The Power BI Modeling MCP server is also available if you prefer an MCP. The local Desktop proxy cannot reach Direct Lake; use a remote XMLA endpoint there.
3. fab + direct TMDL last, with the tmdl skill. Service- and file-shape operations with no model-edit verb: assigning Entra principals to roles (workspace-side, not in .tmdl), report-to-model binding, Copilot-folder features (AI instructions, AI data schema, verified answers), Lakehouse / Delta reshaping behind Direct Lake, and bulk structural surgery that is cleaner as one TMDL diff than N te calls. For read-only Fabric retrieval of AI instructions / schema, use scripts/get_semantic_model_ai_metadata.py. Author the TMDL with the tmdl skill, then run te validate.

Ordering gate: add relationships before any measure that uses RELATED() or a cross-table CALCULATE(), or the save gate fails with DAX0002 (no relationship in context).

Lifecycle

Design

Model dimensionally: a star of fact plus conformed dimensions beats snowflakes and fact-to-fact joins. Decide storage mode and refresh strategy before building; both are near one-way doors once published. See references/dimensional-modeling.md, references/storage-modes.md, references/composite-models.md, and references/direct-lake.md.

Build

Make each change through the cascade above. Author measures with full metadata (DisplayFolder, FormatString, Description) in one pass. Validate after every mutation (te validate) and gate on BPA (te bpa run --fail-on error). Renaming or moving any object can silently break downstream reports and models; run the lineage check first, then propagate with pbir-cli / fabric-cli (see references/refactoring-renaming.md). Deep guidance per area: references/relationships.md, references/time-intelligence.md, references/calculation-groups.md, references/parameters.md, references/security.md, references/dax-authoring.md.

Refresh

Configure incremental refresh from the terminal (te incremental-refresh); for Direct Lake, the refresh is the framing. See references/incremental-refresh.md, and the refresh-semantic-model skill for monitoring and troubleshooting.

Review

Audit against the categories below and produce prioritized findings with file locations. Gather context first with scripts/get_model_info.py (storage mode, size, connected reports, endorsement, data sources, refresh schedule). Full checklist in references/review-checklist.md; performance method in references/performance.md.

Review categories (by severity)

• Critical: bidirectional ambiguity, circular dependencies, missing data types, orphaned tables, fail-open RLS, limited relationships that silently drop rows
• Memory & size: high-cardinality dictionaries, auto attribute hierarchies (isAvailableInMDX on hidden / high-cardinality columns), unsplit DateTime, auto date/time tables, wrong data types, calc columns that should be measures, unused objects
• Data reduction: unfiltered fact history (no incremental refresh), unnecessary columns, detail grain not needed for reporting, logic better pushed upstream
• DAX correctness: filtering tables not columns in CALCULATE, unguarded division, context-blind calc columns, variable time-shift bugs (references/dax-authoring.md; for query tuning use the dax skill)
• Measure hygiene: implicit measures, report-scoped measures that belong in the model, ambiguous duplicates
• Documentation & AI: missing descriptions (Copilot truncates after 200 characters), missing display folders, missing synonyms, inconsistent naming (use standardize-naming-conventions)
• Design: star-schema violations, mis-marked date table, many-to-many without a bridge, dead inactive relationships
• Direct Lake: non-unique one-side keys (queries fail at runtime), DirectQuery fallback, calculated-column support by Direct Lake flavor, Delta guardrail breaches

Related skills

• tmdl: TMDL file authoring (the cascade's step-3 fallback)
• dax: DAX query performance optimization
• connect-pbid: TOM / ADOMD via PowerShell against a live Desktop instance; traces; the TOM / MCP tier
• te-cli: the te command reference
• c-sharp-scripting: TOM C# scripts and macros (te script) for properties te cannot reach
• standardize-naming-conventions: naming audit and remediation
• refresh-semantic-model: refresh monitoring and troubleshooting
• lineage-analysis: artifact lineage (downstream reports and models that consume this model, across workspaces); distinct from intra-model object dependencies
• bpa-rules (tabular-editor): authoring BPA rules; fabric-cli: service / workspace operations

Reference map

references/dimensional-modeling.md:    star schema, SCD2, junk / degenerate dimensions, header-detail, bridges
references/relationships.md:           cardinality, limited relationships, ambiguity, active / inactive, USERELATIONSHIP
references/time-intelligence.md:       classic vs calendar TI, mark-as-date traps, week-based / 4-4-5
references/calculation-groups.md:      precedence, sideways recursion, selection expressions, the variant trap
references/parameters.md:              field parameters, what-if parameters, dynamic titles
references/security.md:                RLS validation + defensive filters, bidirectional + RLS, OLS restrictions
references/query-semantic-model.md:    querying a model with DAX, INFO functions, output formats, probing
references/storage-modes.md:           Import / DirectQuery / Dual / Hybrid decision matrix
references/composite-models.md:        source groups, regular vs limited, Direct-Lake-plus-Import
references/aggregations.md:            user-defined aggregations, grain, te-script AlternateOf
references/direct-lake.md:             OneLake vs SQL, framing, DirectQuery fallback, guardrails
references/incremental-refresh.md:     IR policy, detect data changes, hybrid / real-time, refresh strategy
references/vertipaq-optimization.md:   VPA metrics, value vs hash encoding, splitting high-cardinality keys
references/dax-authoring.md:           variable semantics, DIVIDE, measure vs calc column (gaps vs the dax skill)
references/ai-copilot-readiness.md:    the Copilot grounding contract, synonyms / linguistic schema, descriptions, Q&A retirement
references/metadata-and-organization.md: descriptions, display folders, naming, measure tables, perspectives
references/hierarchies-cultures.md:    user hierarchies, parent-child, KPIs, perspectives, cultures / translations
references/documentation-and-bpa.md:    data dictionary, BPA documentation gate, metadata diffs, intra-model impact analysis (artifact lineage = the lineage-analysis skill)
references/refactoring-renaming.md:    safe rename workflow (lineage check first, then propagate via pbir-cli / fabric-cli)
references/review-checklist.md:        full audit checklist with remediation
references/performance.md:             performance testing, unused-column detection, memory analysis
scripts/get_model_info.py:             model metadata overview (mode, size, reports, endorsement, sources, refresh)
scripts/manage-ai-metadata.csx:        read/write AI instructions and AI schema through TOM culture linguistic metadata
scripts/get_semantic_model_ai_metadata.py: Fabric CLI service-definition readback for AI instructions and AI schema

What this skill deliberately leaves out

• GUI-tool walkthroughs and the old review skill's "use whatever tool is available" framing: superseded by the te-cli-first cascade
• Hand-authored Q&A phrasings: Q&A is being retired and Copilot does not read phrasings; invest in synonyms and descriptions
• Perspectives or display folders presented as security: both are queryable by anyone with model access; use RLS / OLS
• The PBIT format: out of scope

Source: data-goblin/power-bi-agentic-development → plugins/semantic-models/skills/semantic-model/SKILL.md