autonomous-backlog-maintenance

name	autonomous-backlog-maintenance
description	Trigger — "groom the backlog", "close stale tickets", "split this epic", "re-prioritize tickets", "backlog health check", "find duplicate issues", "triage open tickets". Skip — when the user is creating new tickets (not maintaining existing ones), when the backlog has fewer than 5 items, or when manual human triage is explicitly requested.
license	Apache-2.0
compatibility	{"clients":["openai-codex","gemini-cli","opencode","github-copilot"]}
metadata	{"owner":"codex","domain":"autonomous-backlog-maintenance","maturity":"draft","risk":"low","tags":["backlog","grooming","triage","tickets","maintenance"]}

Purpose

Autonomously maintain a project backlog by closing stale tickets, splitting oversized work items, detecting duplicates, and recalculating priority based on evidence. Keeps the backlog actionable without requiring constant human grooming sessions.

When to use

• The backlog has accumulated tickets with no update in 30+ days.
• An epic or ticket scope exceeds what a single agent can complete in one run.
• Priority rankings are outdated because project goals or dependencies have shifted.
• Duplicate or near-duplicate tickets exist across the backlog.
• A periodic backlog health audit is needed.

Do NOT use when

• The user is actively creating new tickets — let them finish first.
• The backlog has fewer than 5 items (manual review is faster).
• The user explicitly requests human-only triage with no automation.
• Tickets belong to a different team's backlog that this agent does not own.

Operating procedure

1. Run grep -rl "status" tickets/ docs/tickets/ (or equivalent) to locate all ticket files in the repo.
2. Parse each ticket and extract: id, title, status, last_updated, assignee, labels, description length (words).
3. Load results into a table: | ID | Title | Status | Days Since Update | Word Count | Labels |.
4. Staleness check: Flag every open ticket with no update in >30 days. List them under a "Stale Candidates" heading.
5. Duplicate detection: Compare ticket titles and descriptions pairwise using keyword overlap. Flag pairs with >60% keyword overlap as potential duplicates.
6. Oversized ticket detection: Flag any ticket whose description exceeds 500 words or whose acceptance criteria list exceeds 8 items — these need splitting.
7. For each oversized ticket, propose a split: create 2–4 sub-tickets with MECE scopes, each under 200 words, each with ≤3 acceptance criteria.
8. Priority recalculation: Score each open ticket as priority = (blocked_count × 3) + (dependency_count × 2) + (days_since_update > 14 ? 1 : 0). Rank by descending score.
9. Produce a Backlog Health Report with sections: Stale (count + list), Duplicates (count + pairs), Oversized (count + split proposals), Priority Ranking (top 10).
10. For stale tickets with no linked PR and no comments in 60+ days, draft a close-comment explaining the reason and mark status as closed-stale.
11. Write all proposed changes as a diff or patch — do not auto-apply without confirmation unless the agent is in full-autonomous mode.

Decision rules

• Never close a ticket that has a linked open PR — mark it blocked instead and note the PR.
• Never close a ticket labeled pinned, evergreen, or do-not-close regardless of staleness.
• Splitting must preserve the original ticket as a parent/epic linking to the new sub-tickets.
• Priority recalculation must not override manually-set P0 or critical labels — keep those at top.
• If duplicate detection confidence is below 60% keyword overlap, flag for human review instead of auto-merging.

Output requirements

1. Backlog Health Report — summary table with stale count, duplicate count, oversized count, top-10 priority list.
2. Stale Ticket Actions — list of tickets to close with drafted close-comments.
3. Split Proposals — for each oversized ticket, the proposed sub-tickets with titles and acceptance criteria.
4. Priority Ranking — ordered list of all open tickets by computed score.
5. Duplicate Pairs — table of suspected duplicates with overlap percentage.

References

• references/checkpoint-rules.md — checkpoint after each batch of ticket modifications.
• references/failure-escalation.md — escalate when ticket data is malformed or inaccessible.
• Repo ticket directory conventions (typically tickets/, docs/tickets/, or .github/ISSUES/).

Related skills

• collaboration-checkpoints — checkpoint after bulk backlog changes before applying.
• goal-decomposition — splitting oversized tickets uses decomposition patterns.
• human-interrupt-handling — escalate to human when auto-close confidence is low.
• autonomous-run-control — backlog sweeps are long-running operations needing run budgets.

Failure handling

• Ticket parse failure: If a ticket file is malformed, skip it, log the path and error, and continue with remaining tickets.
• No tickets found: If the ticket directory is empty or missing, report "No backlog found at expected paths" and list paths searched.
• Ambiguous duplicates: If overlap is 40–60%, list the pair under "Needs Human Review" instead of auto-acting.
• Split disagreement: If a ticket cannot be cleanly split into MECE sub-tasks, keep it intact and flag it as "Needs manual decomposition".