Performance optimization for Qlik Sense: three-metric framework (Base RAM, Peak RAM, Reload Time), key encoding hierarchy, QVD optimized load rules, expression performance (If vs set analysis, Aggr caution, master items for caching), memory choreography, and data reduction techniques. Load when optimizing or reviewing performance-sensitive artifacts.
Complete QA checklist used by the qa-reviewer agent for validating Qlik development artifacts. Covers data model integrity, naming convention compliance, script quality, expression correctness, security gaps, cross-artifact consistency, blocked dependency audit, and data quality validation. Also available for manual invocation outside the pipeline via /qlik-review-checklist.
Section access patterns, row-level security, data reduction, OMIT field usage, hybrid security models, and Cloud vs. client-managed security differences. Use when designing or reviewing security configurations.
Initialize a new Qlik project with standard directory structure, input subdirectories, artifact phases, and dependency tracking template.
Post-load data quality validation patterns for Qlik development. Provides query templates for null rate analysis, referential integrity checks, value distribution analysis, row count validation, orphaned record detection, sparse field identification, and duplicate detection. Usable by the qa-reviewer when MCP or post-load data access is available. Also provides patterns for embedding validation checks directly into load scripts. Load when performing data quality validation or writing diagnostic scripts.
Captures existing platform patterns for brownfield Qlik projects. Provides structured templates for documenting existing app inventory, shared subroutine catalogs, naming convention maps, data connection standards, QVD storage conventions, and organizational coding standards. Used by requirements-analyst during Phase 0 context ingestion and by script-developer during Phase 4 for platform compatibility. Load when ingesting platform context or writing scripts that must integrate with existing platform conventions.
Capability registry for the Qlik Cloud MCP server. Maps MCP tools to pipeline phases, provides MCP detection patterns, documents behavioral gotchas not covered by tool definitions, and defines multi-step workflows for expression validation, reference app analysis, visualization scaffolding, and data quality checks. Load whenever an agent needs to interact with a live Qlik Cloud tenant. The tool definitions themselves document parameters, response structures, and basic usage -- this skill covers framework integration, sequencing, and pitfalls discovered through live testing.
Star schema patterns, key resolution strategies, synthetic key prevention, QVD layer design, multi-app architecture patterns, source architecture consumption strategies, and associative engine behavior for Qlik Sense data modeling. Load when designing or reviewing data models.