DataHub is an open-source metadata platform that catalogs data assets so people can find, understand, govern, and monitor data across an organization’s data ecosystem. Data teams use it for data discovery, governance, observability, and answering questions about cataloged data with an analytics agent.
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 datahub-project/datahub --skill test-reviewgit clone --depth 1 https://github.com/datahub-project/datahubWrote 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/datahub-project/datahub/test-review)<a href="https://agentmods.dev/skills/datahub-project/datahub/test-review"><img src="https://agentmods.dev/badge/skills/datahub-project/datahub/test-review/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/datahub-project/datahub/test-review"><img src="https://agentmods.dev/badge/skills/datahub-project/datahub/test-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Excessive Agency · line 209 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00000 | $0.02280 |
| Opus 5.5 | $0.00000 | $0.00912 |
| Sonnet 5.5 | $0.00000 | $0.00456 |
| Haiku 4.5 | $0.00000 | $0.00228 |
Grade A, and why
test-review 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 1mo 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 — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DataHub Test Review
You are an expert DataHub test reviewer. Your role is to evaluate pytest smoke tests against established testing standards, identify issues, and provide actionable feedback.
Authoring how-to: smoke-test/AGENTS.md. Review rubric:
standards/smoke.md.
Multi-Agent Compatibility
This skill is designed to work across multiple coding agents (Claude Code, Cursor, Codex, Copilot, Gemini CLI, Windsurf, and others).
What works everywhere:
- All review checklists, standards references, and procedures in this document
- Bash for running scripts (
detect-test-changes.sh,ghCLI,git diff) - Reading files, searching code, and generating review reports
Claude Code-specific features (other agents can safely ignore these):
- The
/test-reviewslash command (.claude/commands/test-review.md) loads this skill automatically - The
test-quality-analyzeragent (.claude/agents/test-quality-analyzer.md) can be dispatched for parallel analysis -- fallback instructions are provided inline for agents that cannot dispatch sub-agents TaskCreate/TaskUpdatefor progress tracking -- if unavailable, simply proceed through the steps sequentially
Standards file paths: All standards are in the standards/ directory alongside this file. All paths below are relative to .agent-skills/test-review/.
Quick Start
Full review? -> Load standards, gather test files, then launch test-quality-analyzer agent (or perform checks directly)
PR review? -> Detect changed test files, then analyze only those files
Scope
In Scope
smoke-test/-- Python pytest smoke tests (API-level tests against a running DataHub instance)smoke-test/tests/-- shared test utilities, fixtures, and helpers
Out of Scope
smoke-test/tests/cypress/-- Cypress UI testse2e-test/ui/playwright/-- Playwright UI testsmetadata-ingestion/tests/integration/-- ingestion connector tests (covered bydatahub-connector-pr-review)metadata-ingestion/tests/unit/-- unit testsmetadata-ingestion/src/datahub/testing/-- ingestion testing utilities
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed · -14 lines e1ae409bf131
- 1mo ago First seen · 302 lines · 0 tokens per session scan A a211e30ecca4
test-review is a skill published in the GitHub repository datahub-project/datahub (12,851 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 2,280 tokens. 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 2026-08-30.
Other skills, from other repositories
openmetadata-pr-review
Reviews OpenMetadata and Collate pull requests as a maintainer deciding whether to merge. Use WHENEVER the user asks to review a pull request — any phrasing ("review this PR", "PR review", "can you review.
java-affected-tests
Use before opening or updating an OpenMetadata PR that changes Java, a JSON schema, an index mapping, a SQL migration, seed data or a pom — PR CI no longer runs the Java integration tests (they run only in the merge queue) and the JavaUIIT/search-it suites run only nightly, so this selects the unit tests and…
connector-review
Review an OpenMetadata connector against golden standards. Runs multi-agent analysis covering architecture, code quality, type safety, testing, and performance. When a PR number is given, automatically posts the quality summary to the PR description and a detailed review as a PR comment.
pr-checklist
Use when opening or finalizing a GitHub PR for OpenMetadata. Walks through the repo PR template — linked issue, high-level design (for big PRs), unit/integration/Playwright tests + coverage, UI screen recording, and manual test steps — then drafts a fully-filled PR body and (optionally) creates the PR.
test-enforcement
Use after implementing any feature or fix to ensure comprehensive test coverage. Enforces 90% line coverage in openmetadata-service, integration tests for all API endpoints in openmetadata-integration-tests, and Playwright E2E tests for UI changes.
connector-audit
Deep reliability audit for OpenMetadata connectors — runs 7 investigation prompts (metadata, errors, auth, lineage, scale, synthesis, implementation) against connector standards.