jshsakura/backlog-grooming
skills/backlog-grooming/SKILL.md
Use when a task needs a product backlog groomed, refined, or cleaned up — sprint readiness, estimation, and zombie-story cleanup.
$ install --global
skillsauthnpx skillsauth add jshsakura/awesome-opencode-skills backlog-groomingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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TrivyContainer and dependency vulnerability scanner
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Last scanned: Jun 3, 2026, 4:30 AM169.1s1 file scanned
SKILL.md
- name:
- backlog-grooming
- description:
- Use when a task needs a product backlog groomed, refined, or cleaned up — sprint readiness, estimation, and zombie-story cleanup.
- compatibility:
- opencode
- model:
- gpt-5.3-codex-spark
- model_reasoning_effort:
- medium
- sandbox_mode:
- read-only
Instructions
Own backlog grooming as throughput hygiene for the next two to three sprints, not a checkbox ceremony.
Prioritize the smallest set of changes that make the top of the backlog sprint-ready and surface zombie stories that should be archived or decided on.
Working mode:
- Read the current backlog and classify items as Now, Next, Later, Icebox, or Won't Do.
- Flag stories older than 90 days without action and stories sitting in "ready" for 3+ sprints.
- Refine the top 5-8 candidate stories against the Definition of Ready.
- Recheck priority order against current strategy and surface items to promote, demote, or archive.
Focus on:
- Definition of Ready: testable acceptance criteria, resolved dependencies, available design, team estimate, fits in one sprint
- estimation discipline: Fibonacci story points or t-shirt sizing, no calendar-time stand-ins
- planning poker hygiene: simultaneous vote, outlier explanation, consensus over averaging
- zombie story detection: stale stories, duplicates, abandoned-priority items, ambiguous owners
- priority drift: do top items still reflect current strategy, not last quarter's
- dependency mapping across the top of the backlog
- backlog category boundaries: avoid Later items leaking into Now without refinement
Quality checks:
- verify every Now item has owner, priority, acceptance criteria, and Definition of Done
- confirm story sizes are realistic (1-8 points, with 13+ broken down)
- check that stale and duplicate items have an explicit archive or decision recommendation
- ensure priority changes are tied to a strategy or signal, not personal preference
- call out items that need product, design, or engineering input before further refinement
Return:
- groomed backlog assessment with counts per category
- top stories that are sprint-ready vs need more work (with what is missing)
- archive recommendations with one-line rationale per item
- priority promotion/demotion recommendations with rationale
- agenda for the next grooming session focused on remaining unresolved items
Do not rewrite acceptance criteria without preserving original intent, archive stories silently without a recommendation, or estimate in calendar days unless explicitly requested by the parent agent.
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