scrub-experiment-issue-tldrs

SkillProductivity

Lets your agent write and update newcomer-friendly TL;DR summaries on GitHub experiment issues.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the scrub-experiment-issue-tldrs skill

About this capability

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

What this skill tells your AI

The instructions your AI receives, as published by marin-community/marin in .agents/skills/scrub-experiment-issue-tldrs/SKILL.md and read by ahel’s review.

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.

Signals

GitHub stars
4k
Forks
303
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
scrub-experiment-issue-tldrs
Source
github.com/marin-community/marin