test-review

Rules for reviewing DataHub smoke tests and integration tests against the project’s review process.

In plain words
What is it for?
They help gather test files, detect changed tests, apply the right standards, and create a review report.
Why use it?
They define which tests are included, which are excluded, and how to handle reviews with or without a pull request number.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/datahub-project/datahub/test-review
Clone the repo
git clone --depth 1 https://github.com/datahub-project/datahub

Made for: Cursor.

Per session 22 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 221 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00022 $0.00221
Opus 5 $0.00011 $0.00111
Sonnet 5 $0.00004 $0.00044
Haiku 4.5 $0.00002 $0.00022

Measured 3d ago against content hash fe36ee23278c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 3d 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.

.cursor/rules/test-review.mdc · 24 lines

What it actually says

DataHub Test Review

When asked to review tests, check test quality, validate smoke tests, or review integration tests, follow the skill instructions in .agent-skills/test-review/SKILL.md.

Quick reference

  1. Load standards from .agent-skills/test-review/standards/smoke-and-integration.md
  2. If a PR number is given, use incremental review mode with .agent-skills/test-review/scripts/detect-test-changes.sh
  3. Otherwise, gather test files and run a full review
  4. Use the sequential fallback workflow (read each file, check against standards, report findings)
  5. Generate a report using templates from .agent-skills/test-review/templates/

Scope

  • In scope: smoke-test/ (Python smoke tests + Cypress integration tests)
  • Out of scope: metadata-ingestion/tests/unit/, connector-specific integration tests
Changes

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.

  1. 3d ago First seen · 24 lines · 22 tokens per session scan A fe36ee23278c

Subscribe to this mod's changes

test-review is a cursor rule published in the GitHub repository datahub-project/datahub (12,629 stars, last pushed today), licensed Apache-2.0. It adds 22 tokens to every session and 221 once invoked, about $0.0001 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 2026-08-30.