---

name: lux description: "Use Lux/Lux API for Pandas-integrated visual exploratory data analysis, intent-driven recommendations, chart export, configuration, semantic data types, and optional SQL tables." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Lux repo skill

Use this skill when a task involves Lux/Lux API (lux-api), a Pandas dataframe with Lux recommendations, intent-driven visualization, Clause/Vis/VisList, Lux widget/display configuration, semantic data typing, or optional PostgreSQL-backed LuxSQLTable workflows.

First decisions

1. Install/import check: Lux installs as lux-api but imports as lux.
2. Import order: import lux before creating or loading Pandas dataframes that should become LuxDataFrame objects.
3. Workflow shape: decide whether the user is asking about dataframe recommendations, direct visualization objects, configuration/actions, semantic data types, or SQL-backed tables.
4. Environment shape: base Lux workflows are CPU/Pandas/visualization workflows. SQL is optional and requires a PostgreSQL service plus connector packages.
5. Staleness check: read references/repo-provenance.md before refreshing or trusting this skill against a different Lux checkout/version.

Minimal public install and import check:

pip install lux-api
python - <<'PY'
import lux
import pandas as pd
print(lux.__version__)
print(pd.DataFrame.__module__)
PY

For a stronger offline check after installation, run scripts/check_lux_environment.py and scripts/lux_recommendation_smoke.py.

Route map

User task	Read next
Import Lux with Pandas, set df.intent, inspect recommendation tabs, explain df.current_vis or df.exported, reset stale recommendations	sub-skills/pandas-intent-recommendations/SKILL.md
Construct a Clause, one Vis, or a VisList; enumerate wildcards; refresh a visualization source; export Altair/Matplotlib/Vega-Lite/Python code	sub-skills/visualization-export/SKILL.md
Configure lux.config, plotting backend/style, sampling, top-k/sort, default display, custom actions, or widget/debug diagnostics	sub-skills/configuration-actions/SKILL.md
Fix or explain semantic data types, temporal/geographic/id columns, named row/column indexes, grouped dataframes, small/empty dataframe warnings	sub-skills/special-data-types/SKILL.md
Connect Lux to PostgreSQL tables with LuxSQLTable, JoinedSQLTable, SQLExecutor, or SQL connection troubleshooting	sub-skills/sql-backend/SKILL.md

Shared references and scripts

• references/package-overview.md summarizes public objects, versioned surfaces, optional dependencies, and recommendation vocabulary.
• references/troubleshooting.md covers cross-cutting install/import/widget/cache/version/SQL issues.
• references/repo-provenance.md records the source snapshot and refresh baseline.
• references/repo-routing-metadata.json contains structured router metadata for managed repo-skill import tooling.
• scripts/check_lux_environment.py verifies package imports, versions, Pandas patching, and Lux diagnostics.
• scripts/lux_recommendation_smoke.py runs an integrated offline dataframe/intent/export smoke check.

Operating rules

• Do not tell users to run Lux repository tests, docs, examples, or upload scripts as part of normal package use. Use this skill's bundled references and scripts instead.
• Prefer in-memory or user-provided data over remote tutorial datasets for verification.
• If df.recommendation looks stale after changing config or data, call df.expire_recs(); if metadata or data types changed, also call df.expire_metadata() or recreate the dataframe.
• If an intent expands to multiple visualizations, use VisList, not Vis.
• Treat SQL support as optional/service-backed. Confirm connector, credentials, table existence, and privileges before constructing LuxSQLTable.
• Keep notebook/widget setup separate from terminal validation: terminal scripts should inspect recommendation objects and export code, not expect interactive widgets.