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scrub-experiment-issue-tldrs

Review GitHub experiment issues and update concise summaries that explain the setup, investigation, and current conclusion. Add useful supporting links and maintain labels so newcomers can understand both ongoing and completed work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Run the experiment-issue TL;DR scrub only from its scheduler or an explicit request for that scrub.

연동 도구GitHub
설치 방법 보기

이럴 때 유용합니다

  • Add summaries to experiment issues
  • Update stale conclusions or unresolved blockers
  • Make closed experiment issues easier to understand
  • Maintain supporting links and summary labels

포함된 파일(1)

  • SKILL.md3.1 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

scrub-experiment-issue-tldrs

Use this skill on scheduled scrub turns that maintain experiment issue summaries in marin-community/marin.

The Python selector script only picks which issues to inspect and provides thread context. All summary judgment, writing, and GitHub issue editing lives in this workflow.

Focus

  • Keep experiment issues understandable to a technically strong newcomer who does not know the local project history.
  • Prefer issues whose current body lacks a managed TL;DR block or whose existing summary is weak, stale, vague, or unlabeled.
  • Treat closed issues as fully eligible. They often have the clearest conclusions and are good summary targets.

Managed Block Format

For each candidate issue, update or add exactly one managed issue-body block bounded by <!-- experiment-tldr:start --> and <!-- experiment-tldr:end -->.

Write the block as normal Markdown in this shape:

<!-- experiment-tldr:start -->
## Summary

One short newcomer-friendly summary paragraph.

### Helpful links
- <smallest useful set of links>
<!-- experiment-tldr:end -->

Writing Guidance

  • Explain the setup, the investigation, and why it mattered.
  • State the current conclusion, recommendation, or unresolved blocker in concrete language.
  • Improve existing managed summaries whenever they are inaccurate, stale, vague, or miss the real conclusion.
  • Improve unmanaged summaries too when the issue still lacks the tldr label and the current body is not adequate.
  • Treat 250 words as a soft cap for the summary section, not a target.

Helpful Links Guidance

  • Keep the list short.
  • Prefer decisive comments, W&B reports, follow-up PRs, linked issues, and similar artifacts that let a reader verify the summary quickly.
  • Omit redundant or low-value links.

Label And Edit Guidance

  • The selector script output is the source of truth for candidate order and provided thread context.
  • Use gh issue view --json <fields>, gh pr view --json <fields>, explicit narrow flags such as --comments, and gh api to inspect related issues, PRs, or comments when the provided context is not enough.
  • Skip issues whose body already matches the desired managed block content.
  • The tldr label means the issue now has an adequate newcomer-friendly summary plus enough supporting links to dig deeper.
  • Add the tldr label when the issue now meets that bar. Remove it when the issue no longer meets that bar.
  • After updating an issue body, add a short @dlwh comment describing what changed.

Output

  • Keep the run focused on useful issue-body improvements rather than broad repository changes.
  • If there are zero candidates, report that and exit without mutating GitHub.
  • If you mutate any issue bodies or labels, report the affected issue numbers and what changed.
  • End the run with exactly one footer line of valid one-line JSON: HARNESS_SCRUB_LOOP {"needs_followup_at":null}. Set needs_followup_at to null when the run is complete, or a future RFC 3339 timestamp when another follow-up turn is needed.

리뷰

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Compare Zephyr performance before and after a PR
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Register Hugging Face datasets for Marin by inspecting their structure without downloading the full dataset. Identify text fields, configurations, and data splits, then add a dataset module and validate the mapping with a sample.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Registering a Hugging Face dataset for Marin
  • Inspecting text fields without a full dataset download
  • Checking configurations and data splits
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add-grant

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Turn a specified GCP access request into a reviewable Pulumi change and pull request. Select the narrowest suitable role and encrypt personal email identities, covering resource permissions and Cloud Run viewer access through IAP, an access gateway.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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  • Add a viewer to a Cloud Run service protected by IAP
  • Prepare service account impersonation permissions
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Add or update Pallas/Mosaic kernels, specialized computation routines for JAX. The skill covers reference implementations, output and gradient checks, public wrappers, fallback behavior, performance benchmarks, and hardware-specific tuning when requested.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Adding a Pallas kernel for a JAX computation
  • Checking outputs and gradients against a reference
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Preserve old experiment scripts with a dated Git tag, a named snapshot of the code, and add comments linking related GitHub issues to the archived files and cleanup pull request.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Preserving a snapshot of old experiment scripts
  • Linking experiment issues to archived files
  • Updating archive notices after a tag changes
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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Launch a specified Zephyr pipeline and check startup
  • Monitor stage progress and worker health over time
  • Investigate stalled stages or repeated worker failures
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