code-review
Use to review code changes with a two-stage process - first checking spec/requirements…
Use during PR creation for a UI feature or feature task. Run the PR build in Docker with sample data, record the feature, and upload the verified video into the GitHub PR description. Standalone fixes, refactors, styling and localization changes do not require this workflow.
$ npx -y skills add open-metadata/OpenMetadata --skill ui-pr-recording --agent claude-codeHow it fires
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Use during PR creation for a UI feature or feature task. Run the PR build in Docker with sample data, record the feature, and upload the verified video into the GitHub PR description. Standalone fixes, refactors, styling and localization changes do not require this workflow.
name: ui-pr-recording description: Use during PR creation for a UI feature or feature task. Run the PR build in Docker with sample data, record the feature, and upload the verified video into the GitHub PR description. Standalone fixes, refactors, styling and localization changes do not require this workflow.
Produce evidence of the feature running against a real local OpenMetadata stack as part of [pr-checklist](../pr-checklist/SKILL.md) when creating its PR. The requirement is recorded in ADR:2026-10-10-ui-prs-require-docker-screen-recordings.
Inspect the task/linked issue and the diff against the PR's base. This requirement applies when creating a PR that implements or extends a UI feature, including a task or subtask of that feature with UI impact. Standalone bug fixes, refactors, styling, localization, docs, tests and backend-only work may use `Not applicable — <reason>` in the recording section. Classify by the task and its behavior, not just changed paths or labels. A styling task that delivers part of a UI feature still qualifies.
Run this step during PR creation, not automatically during implementation or a standalone review. A user can still explicitly request a recording for any change. For a qualifying PR, prepare a description containing a playable GitHub-hosted video, the recorded commit, Docker startup/health evidence, sample-data setup, and the steps and outcomes shown. Screenshots supplement the video; a local path, test trace, terminal recording, mock-only UI or TODO does not satisfy the requirement. Required automated tests remain separate checks.
When invoked from `pr-checklist` Step 5, complete sections 1–3 only and return the verified local video path and evidence for the PR body. Section 4 runs at `pr-checklist` Step 7, after Step 6 has prepared the complete body for review; capture must not create or edit a PR.
Use [test-locally](../test-locally/SKILL.md) for prerequisites and the existing build workflow. Build the committed PR code, including the UI, and record `git rev-parse HEAD`. Do not use a released image or skip the build unless the existing artifact is verified to contain that code.
Inspect `docker ps` and the Compose configuration first. The local runner stops both default dev stacks even with `-r false`; its default `-r true` deletes database files. If another task owns those services, use an isolated Compose stack with distinct container names, host ports, network and volumes. A different project name alone is insufficient: the base Compose file pins names, ports, a subnet and a database bind mount. Do not stop another task's stack or delete its data.
For an available default dev stack, from the repo root:
source env/bin/activate make generate ./docker/run_local_docker.sh -m ui -d mysql -s false -i true -r false docker compose -f docker/development/docker-compose.yml ps curl --fail --silent --show-error http://localhost:8585/api/v1/system/version
Verify the server revision matches the recorded build and the server, database and search services are healthy. Use the configured URLs/Compose files for an isolated stack. Keep Docker running through recording and verification, and report its final state; do not tear it down implicitly.
The runner loads the repository's sample data through ingestion. Wait for the data the demo needs and verify it in the UI/API; a successful startup alone does not prove ingestion succeeded. Alternatively, ingest the repository sample data into the isolated stack and create a small synthetic fixture through the API for the changed flow. Record setup commands/fixture names and any sample-loader failures. Failures affecting the demo must be fixed before recording.
Use the available browser recording tool or the UI project's installed Playwright. Confirm the tool produces an actual video; screenshot-only tools cannot satisfy this task. For Playwright, set both `viewport` and `recordVideo.size` explicitly to the same dimensions; start with 1920×1080 for a desktop flow. Without an explicit video size, [Playwright scales the video to fit 800×800](https://playwright.dev/docs/videos). Retain `page.video()`, then await context closure before reading/saving the video. If reusing login state, include IndexedDB in `storageState` when authentication uses it. Keep authentication files and tokens out of artifacts.
Check a short sample before recording the whole flow. Choose a viewport suited to the feature and keep small labels legible at the size reviewers will watch; extra pixels alone do not fix tiny text. For a sharper capture or clearer cursor movement, consider a native recorder when available:
| Recorder | Useful when | | --- | --- | | [OBS Studio](https://obsproject.com/kb/recording-encoder-presets-guide) | Recording the browser window at its native resolution; its **Indistinguishable** preset favors quality over file size. | | [Screen Studio](https://screen.studio/) (macOS) | Adding focused zooms and cursor/click emphasis; it supports MP4 exports up to 4K at 60 fps. |
These are optional capture choices, not required dependencies or purchases. Keep actions and outcomes visible when zooming. Capture at the desired resolution/frame rate instead of upscaling or interpolating an existing clip; re-encoding cannot recover detail lost during capture.
Show navigation to the feature, the action and its visible result against the Docker server. For a preference, show both states and switching back. Include persistence, permission or error behavior when the change affects it. Use UI/API assertions to verify the outcomes instead of treating a completed click sequence as success. Use real server responses, not route mocks.
Keep the clip focused and text readable; captions are useful when the state change is not obvious. Record with synthetic sample data and omit credentials, tokens and unrelated browser c
The Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.
Repo: open-metadata/OpenMetadata
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