From semantic-models
Optimizes DAX query performance in semantic models using a tiered framework covering DAX patterns, query structure, model design, and Direct Lake.
How this skill is triggered — by the user, by Claude, or both
Slash command
/semantic-models:daxThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Skills and references for writing, debugging, and optimizing DAX in semantic models.
Skills and references for writing, debugging, and optimizing DAX in semantic models.
For systematic DAX query performance optimization, read the workflow reference first:
references/dax-performance-optimization.md — Tiered framework (4 tiers), phased workflow, decision guide, and error handling.
Detailed reference files (progressive disclosure — consult as directed by the workflow):
references/engine-internals.md — FE/SE architecture, xmSQL, compression/segments, SE fusion, trace diagnosticsreferences/dax-patterns.md — Tier 1 DAX patterns (DAX001–DAX021) + Tier 2 query structure (QRY001–QRY004)references/model-optimization.md — Tier 3 model patterns (MDL001–MDL009) + Tier 4 Direct Lake (DL001–DL002)Trace capture and performance profiling:
te query (see the te-cli skill) first; as an alternative, the connect-pbid skill covers FE/SE timing (performance-profiling.md) and intermediate result inspection (evaluateandlog-debugging.md).te query (-s <workspace> -d <model>) against the workspace XMLA endpoint; see the te-cli skill (tabular-editor plugin).semantic-model — Model design, build, and auditing including DAX anti-patterns and best practicesconnect-pbid (pbi-desktop plugin) — Trace capture, performance profiling, EVALUATEANDLOG debugginglineage-analysis — Impact analysis before model changes3plugins reuse this skill
First indexed Jul 17, 2026
npx claudepluginhub jonathan-pap/power-bi-agentic-development --plugin semantic-modelsOptimizes DAX query performance in semantic models using a tiered framework covering DAX patterns, query structure, model design, and Direct Lake.
Diagnoses and optimizes Power BI performance issues like slow reports, DAX queries, and large models using Performance Analyzer, DAX Studio, and VertiPaq Analyzer.
Reviews Microsoft Fabric analytics engineering artifacts: Fabric Data Warehouse T-SQL design, dimensional modeling, semantic model storage mode selection, DAX measure correctness, and data preparation quality.