Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vaquarkhan/data-engineering-agent-skills --skill openmetadata-datahub-and-openlineagegit clone --depth 1 https://github.com/vaquarkhan/data-engineering-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/openmetadata-datahub-and-openlineage)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/openmetadata-datahub-and-openlineage"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/openmetadata-datahub-and-openlineage/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/openmetadata-datahub-and-openlineage"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/openmetadata-datahub-and-openlineage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.01119 |
| Opus 5 | $0.00025 | $0.00560 |
| Sonnet 5 | $0.00010 | $0.00224 |
| Haiku 4.5 | $0.00005 | $0.00112 |
Grade A, and why
openmetadata-datahub-and-openlineage scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenMetadata DataHub And OpenLineage
Overview
Use this skill when metadata and lineage must be operationalized through open tooling such as OpenMetadata, DataHub, or OpenLineage. It helps agents align producers with catalog expectations, ensure lineage accuracy, and make discovery trustworthy rather than decorative.
When to Use
- integrating metadata platforms into delivery workflows
- improving dataset discovery and trust signals
- capturing and validating lineage across pipelines
- publishing governed datasets into open catalog ecosystems
- connecting
OpenLineageevents from Spark, Airflow, or dbt to a catalog - defining metadata governance policies for multi-team environments
Do not use this when the team has no shared catalog requirement or when lineage is handled entirely within a closed platform (e.g., Unity Catalog, Purview) with no open integration needs.
Workflow
-
Define metadata ownership and minimum required fields. Include:
- who owns each dataset's metadata (producing team, platform team, or steward)
- minimum required fields: owner, description, classification, freshness, grain
- which fields are auto-populated from lineage vs manually maintained
- how metadata quality is measured and enforced
- what "complete" means for a dataset to appear as discoverable
-
Connect lineage capture to actual execution surfaces.
OpenLineageintegration with orchestrators (Airflow, Dagster)OpenLineageintegration with processing engines (Spark, dbt, Flink)- validate that lineage events fire correctly on job start, complete, and failure
- test that column-level lineage propagates through transformation layers
- monitor for gaps: jobs that run but produce no lineage events
-
Make discovery trustworthy through quality signals.
- surface trust indicators: last validated, freshness, quality score, owner responsiveness
- distinguish production-governed datasets from experimental or deprecated ones
- tag datasets with classification levels (public, internal, restricted, sensitive)
- ensure search relevance: descriptions, tags, and usage signals improve discoverability
- retire stale assets — dead datasets in the catalog erode trust
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 97 lines · 50 tokens per session scan A 85a33e5cc9ff
openmetadata-datahub-and-openlineage is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 2mo ago), licensed MIT. It adds 50 tokens to every session and 1,119 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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