Files
leo-claude-mktplace/plugins/data-platform/commands/profile.md
lmiranda 89f0354ccc feat: add data-platform plugin (v4.0.0)
Add new data-platform plugin for data engineering workflows with:

MCP Server (32 tools):
- pandas operations (14 tools): read_csv, read_parquet, read_json,
  to_csv, to_parquet, describe, head, tail, filter, select, groupby,
  join, list_data, drop_data
- PostgreSQL/PostGIS (10 tools): pg_connect, pg_query, pg_execute,
  pg_tables, pg_columns, pg_schemas, st_tables, st_geometry_type,
  st_srid, st_extent
- dbt integration (8 tools): dbt_parse, dbt_run, dbt_test, dbt_build,
  dbt_compile, dbt_ls, dbt_docs_generate, dbt_lineage

Plugin Features:
- Arrow IPC data_ref system for DataFrame persistence across tool calls
- Pre-execution validation for dbt with `dbt parse`
- SessionStart hook for PostgreSQL connectivity check (non-blocking)
- Hybrid configuration (system ~/.config/claude/postgres.env + project .env)
- Memory management with 100k row limit and chunking support

Commands: /initial-setup, /ingest, /profile, /schema, /explain, /lineage, /run
Agents: data-ingestion, data-analysis

Test suite: 71 tests covering config, data store, pandas, postgres, dbt tools

Addresses data workflow issues from personal-portfolio project:
- Lost data after multiple interactions (solved by Arrow IPC data_ref)
- dbt 1.9+ syntax deprecation (solved by pre-execution validation)
- Ungraceful PostgreSQL error handling (solved by SessionStart hook)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-25 14:24:03 -05:00

893 B

/profile - Data Profiling

Generate statistical profile and quality report for a DataFrame.

Usage

/profile <data_ref>

Workflow

  1. Get data reference:

    • If no data_ref provided, use list_data to show available options
    • Validate the data_ref exists
  2. Generate profile:

    • Use describe for statistical summary
    • Analyze null counts, unique values, data types
  3. Quality assessment:

    • Identify columns with high null percentage
    • Flag potential data quality issues
    • Suggest cleaning operations if needed
  4. Report:

    • Summary statistics per column
    • Data type distribution
    • Memory usage
    • Quality score

Examples

/profile sales_data
/profile df_a1b2c3d4

Available Tools

Use these MCP tools:

  • describe - Get statistical summary
  • head - Preview first rows
  • list_data - List available DataFrames