qlik-toolkit

Script syntax reference, QVD optimization, incremental load patterns (insert-only, insert/update, insert/update/delete, dual-timestamp for SCD2), JOIN/KEEP prefixes, ApplyMap patterns, CROSSTABLE, master calendar generation, variable definitions, error handling, logging patterns, null handling patterns, diagnostic and validation patterns, subroutine integration, and platform gotchas (SET vs LET, dollar-sign expansion timing, SET variable comma limitation). Load when writing, reviewing, or debugging Qlik load scripts, QVD operations, STORE/LOAD syntax, preceding LOAD, NullAsValue, script organization, JOIN, KEEP, ApplyMap, CROSSTABLE, AutoNumber, composite keys, or data quality defensive coding.

Catalog of failure classes that appear in Qlik Sense development artifacts, with severity model and finding-format contract. Covers script syntax errors, data model integrity issues (synthetic keys, circular references, grain misalignment), naming convention violations, expression correctness gaps, security misconfigurations (Section Access, PII), cross-artifact inconsistency, blocked dependency tracking, and post-load data quality. Load when reviewing a Qlik artifact (data model spec, load script, expression catalog, visualization spec, or full app), running a QA pass before sign-off, classifying defect severity, formatting findings for remediation, or deciding which checks apply to a given review scope.

Set analysis syntax and patterns ({1}, {$}, element-set arithmetic, P()/E(), $(=...) modifiers), aggregation functions, TOTAL qualifier usage, Aggr() patterns, conditional expressions, null handling in expressions, dollar-sign expansion timing, expression performance optimization, calculation conditions, and common Qlik Sense expression anti-patterns. Load when writing, reviewing, or debugging Qlik expressions — master measures, master dimensions, calculated dimensions, KPI formulas, set-analysis snippets, year-over-year and rolling-window calculations, or any expression that misbehaves under selection.

Star schema design, key resolution (natural/composite/hash/AutoNumber), synthetic key prevention, circular reference resolution, QVD layer architecture, multi-app patterns (single app, generator/consumer, extract-transform-model-UI, binary load), source architecture consumption (dimensional warehouse, OLTP, Data Vault 2.0, pre-joined views, flat files), grain alignment across multiple facts, bridge tables, link tables, ApplyMap vs dimension, HidePrefix/HideSuffix. Load when designing or reviewing a Qlik Sense data model, deciding between single-app and multi-app, choosing a key strategy, or diagnosing synthetic keys and circular references.

This skill should be used when naming, renaming, prefixing, aliasing, or mapping any Qlik Sense field, table, variable, or expression. Covers entity-prefix dot notation for non-key fields, key field conventions (% prefix, _key suffix, HidePrefix, HideSuffix), table naming (dimension, fact, temp, mapping, bridge), variable naming (v prefix, field-reference vs expression variables, variable-to-expression name mirroring), expression naming (master measures, master dimensions, calculated dimensions), script and QVD file naming, the cross-layer field naming strategy from source through extract/transform/model to UI, the Mapping RENAME field-rename layer, variable-to-field-name alignment, and the most common Qlik naming anti-patterns (silent synthetic keys, inconsistent key names, double-prefix from QUALIFY).

Qlik project directory layout convention for Claude-Code workflows: data-sources, scripts, qvds, documentation, tests directories with per-directory rationale and starter README templates. Cross-platform PowerShell + Bash scaffolding scripts that are idempotent (re-running preserves existing files). Load when starting a new Qlik Sense project, setting up a workspace for Claude to help with, or evaluating an existing project's directory layout against a baseline convention.

Post-load data quality validation patterns for Qlik Sense. Provides query templates for null-rate analysis, referential integrity checks, value distribution analysis, row-count validation, orphaned-record detection, sparse-field identification, and duplicate-key detection — usable against a live tenant via MCP or any post-load data interface. Also provides patterns for embedding validation checks directly into load scripts so failures surface during reload rather than in production. Load when running data quality checks against a loaded app, writing diagnostic or validation scripts, or designing fail-fast assertions inside a load script.

Brownfield Qlik platform discovery: subroutine identification and limitation patterns from existing .qvs scripts, naming-convention variations (entity-prefix dot vs underscore vs camelCase; dim_/fact_ vs hub_/sat_/lnk_ vs Map_), connection conventions, QVD storage conventions (centralized layered vs per-app vs date-stamped), architecture pattern detection (single-app, generator/consumer, four-layer, binary load), incremental load detection, and convention-conflict resolution when platform conventions differ from framework defaults. Load when working in a brownfield Qlik environment, reverse-engineering an existing platform's conventions, or integrating new development with shared subroutine libraries.

Chart type selection with decision criteria based on data relationships, sheet layout patterns on the Qlik Sense responsive grid, responsive design behavior, color and formatting standards including accessibility-safe palettes, filter pane and listbox design strategies, navigation flow, accessibility best practices, and reference-app reverse-engineering patterns. Load when designing or reviewing Qlik Sense sheets, choosing chart types, building KPIs, configuring filter panes, replicating a reference app's look-and-feel, or evaluating a layout's responsive behavior.

Data source profiling for Qlik development. When MCP or direct database access is available, provides query templates and procedures to assess source schemas, field types, cardinality, null rates, sample values, and data quality indicators. When live access is unavailable, generates a structured Source Profile Template for manual completion. Includes source architecture classification — annotating tables with architectural role, key structure, mutability, incremental load pattern, and consumption implications (dimensional warehouse, OLTP, Data Vault 2.0, flat files). Load when profiling source schemas before data-model design, assessing source data quality, classifying source architecture, or filling in a Source Profile Template by hand.

Performance optimization for Qlik Sense: memory optimization (field types, dual values, symbolic keys, data volume estimation), script load optimization (QVD optimized load rules, preceding LOAD, redundant disk reads), expression calculation optimization (Aggr nesting, set analysis complexity, pre-calculated flags), calculation conditions, data reduction techniques (load-time vs runtime), and profiling/diagnostic approaches. Load when optimizing reload time, reducing app memory footprint, speeding up a slow chart, choosing between load-time vs expression-time computation, evaluating Aggr() cardinality, or diagnosing why an app feels slow.

Capability registry for the Qlik Cloud MCP server: maps MCP tools to development tasks, 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 against a live tenant. The MCP tool definitions themselves document parameters and response structure; this skill covers framework integration, sequencing, and pitfalls discovered through live testing. Load when interacting with a live Qlik Cloud tenant via MCP, validating an expression against real data, analyzing a reference app, or running post-load data quality checks.