| name | scrub-reflection-self-improvement |
| description | Scheduled scrub: repository self-improvement. |
| schedule_cron | 0 10 2 * * * |
| schedule_tz | America/New_York |
scrub-reflection-self-improvement
Use this skill on scheduled scrub turns to identify and land high-leverage improvements in marin-community/marin.
Focus
- Look for improvements from recent issues, PR feedback, and recurring operational friction.
- Prefer one concrete implementation per run when feasible.
- If implementation is blocked, produce a concrete plan and capture follow-up work in GitHub.
Candidate Signals
- Repeated confusion in docs, recipes, or contributor workflows.
- Recurring failures or avoidable manual steps in experiments, scripts, and infra operations.
- Capability gaps that reduce the value of agent-assisted contributions.
Triage Checklist
Run a lightweight, repeatable scan before choosing work:
- Review recent open issues and open PRs for repeated friction clusters.
- Explicitly check for already-open scrub-generated issues/PRs touching the same area; prefer advancing or deferring to that existing artifact instead of creating a parallel one.
- Review the latest commits on
main for changes that imply follow-on docs/workflow updates.
- Search
AGENTS.md, .agents/skills/, and docs for stale workflow guidance related to those clusters.
- De-duplicate against existing issues/PRs before creating new artifacts.
When possible, prefer improvements that remove recurring operator time (for example,
turning ad-hoc scrub judgment into explicit repeatable guidance).
Decision Heuristics
- Pick the highest-leverage change with the lowest coordination overhead.
- Treat open scrub-generated issues/PRs as first-class prior art during triage; if one already covers the candidate improvement, avoid opening a second artifact unless the new scope is clearly distinct.
- De-duplicate against existing issues/PRs before opening new work.
- When an improvement changes recurring workflow guidance, codify it in durable repo instructions:
AGENTS.md for cross-cutting agent behavior, or .agents/skills/ for repeatable task workflows.
- If no justified improvement exists now, choose a no-op outcome.
- Prefer direct implementation over opening new issues when the change is fully in-repo and low-risk.
Output
- Keep rationale explicit: observed gap, change made (or plan), and expected impact.
- Prefer durable artifacts over transient notes: land guidance updates in
AGENTS.md and/or recipe docs when that is the primary improvement.
- Treat local-only edits as incomplete work. If you modify files, publish the result (commit/push and open or update a PR per
.agents/skills/author-pr/SKILL.md) before finishing this scrub run.
- If publish is blocked (auth, permissions, CI infra, etc.), report the blocker and set a future
needs_followup_at instead of ending the run.
- If you choose no-op, include explicit inspected signals and why no justified improvement exists now.
- 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.
For no-op outcomes, include at minimum:
- which issue/PR/commit windows were inspected,
- why each candidate was not suitable for this run,
- and why deferring to the next scheduled run is preferable to opening a low-signal artifact now.