metaxy
Feature versioning, lineage tracking, and metadata management for ML pipelines
Directs the agent to plan tasks first, enforce Python coding standards via the dignified-python skill, run only relevant filtered tests, and follow strict guardrails for commits, type safety, and error handling when working on this project.
All Skills in This Repository (7)
Pure Emerald Level Indicatorssybil
Execute documentation code samples during pytest runs.
syrupy
Validate Python test outputs against stored snapshots with pytest integration.
claude-improve-config
Analyze sessions to propose CLAUDE.md, hook, and skill improvements.
narwhals
Write dataframe-agnostic Python code that runs across multiple backends.
docs-page-frontmatter
Generate YAML front matter with title and description fields for documentation pages.
hypothesis
Generate test inputs and shrink failing examples for Python property tests.
metaxy
Guide Metaxy feature definitions, versioning, and metadata tooling in data pipelines.
Frequently Asked Questions
FAQPage SchemaHow to install Metaxy?โผ
Run `npx skills add anam-org/metaxy --all -g -y` in your terminal to install all skills in this suite globally.
What problem does Metaxy solve?โผ
It tracks feature versions and data lineage in multimodal ML pipelines, automatically detecting which downstream steps actually need recomputation when upstream data changes.
Which databases does Metaxy support?โผ
Metaxy works with DuckDB, ClickHouse, BigQuery, LanceDB, and Delta Lake as metadata stores, and integrates with Dagster, Ray, and SQLModel.
Does Metaxy work with Claude Code?โผ
Yes. It ships a dedicated skill and an MCP server so your agent can explore feature graphs and query metadata directly during a session.
How does Metaxy avoid unnecessary recomputation?โผ
It tracks field-level dependencies, so updates to data that a downstream feature does not depend on are pruned and never trigger wasteful recomputation.
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