How do I install the Semantic Model skill?

Run npx skillmds@latest add insightfulanalytics/semantic-model in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Semantic Model skill do?

This skill should be used whenever the user mentions a "semantic model", "data model", or "dataset", or asks to "build", "model", "design", "optimize", "review", or "audit" one, or to "add a measure", "add a relationship", "create a role" / "set up RLS", "add a calculation group", "set up incremental refresh", "fix a star schema", "reduce model size", "prepare a model for Copilot / AI", or "check model quality". Covers the full lifecycle (design, build, refresh, review) and drives every operation through the `te` CLI first, then TOM (connect-pbid) or a model MCP, then TMDL authoring (the tmdl skill). Not for report visuals (use pbir-cli) or isolated DAX query tuning (use the dax skill). It is listed under AI & ML on SkillMD.

Is Semantic Model safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Semantic Model?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Semantic Model free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Semantic Model?

InsightfulAnalytics (@insightfulanalytics) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Semantic Model by insightfulanalytics

Name: Semantic Model
Rating: 4.2 (5 reviews)
Author: InsightfulAnalytics

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)
Writing or rewriting the DAX of a measure: use the dax-standard skill
Isolated DAX query performance tuning: use the dax-optimisation 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.

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.
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.
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. 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-optimisation skill)
Calculation groups: row measures that carry their own scenario filter (the swap silently returns the same number in every column), format strings on a lower-precedence group that never fire, explicit ordinal: lines a save will strip (references/calculation-groups.md)
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, calc columns on Direct Lake, Delta guardrail breaches

Related skills

tmdl: TMDL file authoring (the cascade's step-3 fallback)
dax-optimisation: 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
date-table: drop a ready-made DimDate (calendar / ISO week / fiscal, plus a Dates Selected title measure) into a PBIP model
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:      when a second measure axis forces one, precedence (whose format string wins, where item order comes from), one shared format string through a UDF, scenario-agnostic row measures, 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

Semantic Model

File contents