# Backlog Cleanup Agent

Backlog cleanup is engineering work. Replicas helps teams triage stale issues, validate old tasks, group related work, and turn actionable items into reviewable outputs.

- Canonical: https://tryreplicas.com/use-cases/backlog-cleanup
- Start a workspace: https://tryreplicas.com/auth?mode=signup
- Backlog blog: https://tryreplicas.com/blog/we-gave-replicas-our-entire-backlog

## What is backlog cleanup?

Backlog cleanup is the process of reviewing old issues, stale tasks, ambiguous requests, duplicate work, and low-signal tickets so the team knows what still matters.

A coding agent can help because cleanup often requires repository inspection, product context, test runs, bug reproduction, and judgment about whether an issue is still actionable.

## How Replicas approaches backlog cleanup

The best backlog cleanup agent does not blindly close issues. It separates stale noise from real engineering work and returns evidence.

- **Select a slice:** Start with a label, project, milestone, repo area, or stale issue set instead of the entire backlog.
- **Inspect reality:** The agent checks current code, docs, tests, recent commits, and linked PRs to see whether the issue still applies.
- **Group and classify:** Replicas can identify duplicates, blocked tasks, quick fixes, product questions, and issues that need human prioritization.
- **Return useful outputs:** The result may be a cleanup summary, suggested closures, grouped issues, PRs for small fixes, or follow-up tasks for humans.

## Backlog cleanup outputs are not always PRs

Backlog work often creates information before it creates code. That is still valuable engineering output.

- A list of stale issues that appear fixed by current code.
- Duplicate groups with recommended canonical issues.
- Small PRs for obvious cleanup tasks.
- Reproduction notes for bugs that still exist.
- Clarifying questions for issues that are too vague to implement.
- A prioritized follow-up list for the next engineering planning pass.

## How to evaluate backlog cleanup automation

The risk in backlog cleanup is false confidence. The agent should show evidence, avoid over-closing, and make human review easier.

- Does it cite files, commands, issues, and linked PRs behind each recommendation?
- Does it distinguish stale, duplicate, blocked, vague, and actionable work?
- Does it create small PRs only when the implementation is clear?
- Does it preserve human prioritization for product decisions?
- Does it reduce planning time without hiding uncertainty?

## FAQ

### Can Replicas clean up an entire backlog?
It is better to start with a scoped slice such as one label, repo area, or stale issue set. That keeps the output reviewable and avoids broad unsupported claims.

### Does backlog cleanup mean closing issues automatically?
No. Replicas is most useful when it produces evidence and recommendations that humans can review before closing, merging, or reprioritizing work.

### Can backlog cleanup produce PRs?
Yes, but only for clearly scoped tasks. Many backlog cleanup sessions should produce summaries, triage notes, duplicate groups, or clarification requests.

## Related docs

- [Cloud coding agents](https://tryreplicas.com/cloud-coding-agents): Learn why cloud workspaces make delegated engineering tasks practical.
- [Code review follow-up](https://tryreplicas.com/use-cases/code-review-follow-up): See how PR comments, CI failures, and review findings become follow-up work.
- [Automations docs](https://docs.tryreplicas.com/features/automations): Configure event-driven and scheduled workflows for Replicas workspaces.