Skip to main content

lucid-skill

AI-native data analysis skill. Connect Excel, CSV, MySQL, PostgreSQL — understand business semantics, query with SQL.

No API key required. No LLM inside — the AI agent is the brain; lucid-skill is the hands.


Features

  • Multi-source: Excel (.xlsx/.xls), CSV, MySQL, PostgreSQL — all unified into SQL
  • Semantic Layer: Define business meanings for tables and columns; persist as YAML, Git-friendly
  • JOIN Discovery: Automatically find join paths between tables (direct + indirect)
  • Domain Clustering: Auto-group tables into business domains
  • Embedding Search: Optional multilingual vector search for table discovery
  • Read-only Safety: Only SELECT allowed — mutating SQL is blocked at the engine level

Install

pip install lucid-skill

# Or with uv (recommended for OpenClaw)
uv tool install lucid-skill

# Optional: database drivers
pip install "lucid-skill[db]"       # MySQL + PostgreSQL

# Optional: embedding search
pip install "lucid-skill[embedding]" # sentence-transformers

Quick Start

# Connect a data source
lucid-skill connect csv /path/to/sales.csv

# Explore schema and semantics
lucid-skill init-semantic

# Search tables by business meaning
lucid-skill search "销售额 客户"

# Query with SQL
lucid-skill query "SELECT product, SUM(amount) FROM sales GROUP BY product ORDER BY 2 DESC LIMIT 10"

Architecture

Agent ──→ lucid-skill CLI ──→ Connectors (Excel/CSV/MySQL/PG)
                │                      │
                ├── Catalog (DuckDB)   └── DuckDB (in-memory query engine)
                └── Semantic Store (YAML)
  • No LLM inside — lucid-skill provides data access; the AI agent handles reasoning
  • DuckDB unified — catalog storage + query engine, single dependency, no compilation needed
  • Semantic persistence — YAML definitions survive restarts, shareable via Git

Supported Data Sources

Type Format Notes
Excel .xlsx, .xls Multiple sheets supported
CSV .csv Auto-detects encoding and delimiter
MySQL 5.7+ / 8.0+ Reads foreign keys and column comments (pip install lucid-skill[db])
PostgreSQL 12+ Reads foreign keys and column comments (pip install lucid-skill[db])

Environment Variables

Variable Default Description
LUCID_DATA_DIR ~/.lucid-skill/ Data directory (catalog, semantic store, models)
LUCID_EMBEDDING_ENABLED false Enable vector search (~460 MB model download on first use)

Security

  • Read-only: Only SELECT / WITH statements are allowed; all mutating SQL is blocked
  • No credentials stored: Database passwords are never written to disk
  • Local only: All data stays on your machine

MCP Server Mode

lucid-skill also works as an MCP Server for platforms that support it:

lucid-skill serve

Development

git clone https://github.com/WiseriaAI/lucid-skill
cd lucid-skill
pip install -e ".[dev]"
pytest

License

MIT

Metadata

Release files for lucid-skill 2.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for lucid-skill 2.0.0
File Size Uploaded
lucid_skill-2.0.0.tar.gz 47.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for lucid-skill 2.0.0
File Interpreter ABI Platform
lucid_skill-2.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 106.6 kB

Release files / lucid_skill-2.0.0.tar.gz

Download URL lucid_skill-2.0.0.tar.gz
Size 47.8 kB
Tags Source
SHA-256 checksum
How to use checksums
3d25846304be7857e3d178c6a245cc763fca4de472583d7e6cc87a965c6bd7ac
BLAKE2b-256 checksum
How to use checksums
4cf561b74ec0ecc4e709a2f2e71cd8d382ae769b3cdede13773daa4037146043
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.14.3

Release files / lucid_skill-2.0.0-py3-none-any.whl

Download URL lucid_skill-2.0.0-py3-none-any.whl
Size 58.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
7a3e0ea8aa2a756a3af10b50ce23f3d7c8356f5a283d6fbd2e9634c1ef6bd488
BLAKE2b-256 checksum
How to use checksums
7d1ae4ee0bba52ef8dc4a60898df0be909b197d9b505306efd6a2cc816f29aba
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.14.3

Release history Release notifications | RSS feed

This release

2.0.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page