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>
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25
plugins/data-platform/.claude-plugin/plugin.json
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25
plugins/data-platform/.claude-plugin/plugin.json
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{
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"name": "data-platform",
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"version": "1.0.0",
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"description": "Data engineering tools with pandas, PostgreSQL/PostGIS, and dbt integration",
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"author": {
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"name": "Leo Miranda",
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"email": "leobmiranda@gmail.com"
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},
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"homepage": "https://gitea.hotserv.cloud/personal-projects/leo-claude-mktplace/src/branch/main/plugins/data-platform/README.md",
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"repository": "https://gitea.hotserv.cloud/personal-projects/leo-claude-mktplace.git",
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"license": "MIT",
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"keywords": [
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"pandas",
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"postgresql",
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"postgis",
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"dbt",
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"data-engineering",
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"etl",
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"dataframe"
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],
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"hooks": "hooks/hooks.json",
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"commands": ["./commands/"],
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"agents": ["./agents/"],
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"mcpServers": ["./.mcp.json"]
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}
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