328건 · 관련도순
Organize open pull requests by size, automated check results, inactivity, and overlapping files. Review selected changes in depth, prepare comments for approval, and optionally create separate local working directories for hands-on review.
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Agile product ownership for backlog management and sprint execution. Use for writing user stories and acceptance criteria, planning sprints, estimating story points, breaking down epics, or prioritizing a backlog.
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Use when 999.x backlog items need triage, or the user asks to review, promote, or prune the backlog. Shows each item with its accumulated context, promotes chosen ones into the active milestone, and removes stale ones.
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Complete Product Owner / Product Manager capability — a wiki-style knowledge map of product practice in active software development: the role and its boundaries, strategy cascade (vision → OKRs → roadmap → backlog), continuous discovery, backlog craft (epics, INVEST stories, acceptance criteria), prioritization frameworks (RICE, MoSCoW, Kano, WSJF), sprint delivery, metrics (North Star, AARRR), stakeholder management, and anti-patterns. The PO/PM owns what gets built, in what order, and why — including the end-to-end user flows and user journeys. Use when scoping a product or feature, decomposing an idea into outcomes/epics/stories, prioritizing a backlog, defining an MVP, mapping user journeys, measuring success, or saying no to a stakeholder. Pairs with super-ui-ux-design, which owns how each screen looks and behaves.
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Backlog integration. Manage Projects. Use when the user wants to interact with Backlog data.
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Review and assess every issue in the TMDb project board's Backlog column — re-verify each against current main with a read-only fan-out, close the mechanically dead, promote the actionable to Ready with priority, size and execution order, and leave the rest in Backlog naming the decision they need. Use to groom the backlog, before planning a release, or on a schedule. Runs headless: it decides for itself within the rules below.
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Use when creating, grooming, planning, or closing a backlog item. Bridges backlog items to SAM planning with issue, project, and milestone tracking against the configured backend. Activates on interactive browsing with no arguments, loading an item by issue reference or title match to run grooming and SAM planning, autonomous unattended runs that substitute evidence-derived decisions for clarifying questions, a quick path for one-file fixes where full grooming is disproportionate, dismissing an item without completion under a required reason (duplicate, out of scope, superseded, wontfix, blocked), marking an item done with an evidence trail and required summary, or initializing GitHub tracking infrastructure for a project. Stops when the item already has a plan or is blocked on missing information.
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Use when assigning backlog items to a GitHub milestone. Args: {milestone-number} [P0|P1|P2|title-filter]. Uses backlog list to load items, shows items with GitHub Issue status, lets user select which to assign. Creates missing GitHub Issues for selected P0/P1 items, assigns all to the milestone, updates Project V2 Status to Backlog. Use after create-milestone to populate a sprint or release.
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Triage the Gaia issue backlog and skill-batch intake queue. Use this skill when someone asks to: "triage issues", "clean up the issue tracker", "review the backlog", "close stale issues", "process the intake queue", "review skill-batches", "evaluate draft skill proposals", "approve or reject pending skills", "is this issue still valid?", "what's clogging the backlog?", "run a triage pass", or /gaia-triage. Covers two workstreams: (1) GitHub issue lifecycle — identifying resolved, stale, or need-more-info issues and acting on them via gh CLI; (2) skill-batch intake — evaluating draft proposals in registry-for-review/skill-batches/ and routing them toward promotion or rejection. This is the gatekeeping step before new skills enter the canonical registry; and (3) a cross-repo triage sweep — sizing, P0-P4 prioritization, umbrella/epic synthesis, and assignment across every gaia-research org repo, on the one headquarters tracker.
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Bootstrap a new or existing project with a small, file-based documentation system so Claude Code keeps context, lessons, and decisions across session restarts instead of starting cold every time. Sets up a handful of markdown files under .claude/ (standing rules, a free-form note to your next session, a phased roadmap, a prioritized backlog, and searchable history/changelog archives) sized and split so the files read every session stay small while the archives grow without ever costing context. Use this whenever someone is starting a new project and asks how to structure it for long-running AI-assisted work, wants Claude to "remember" things between sessions without relying on chat history, asks for a CLAUDE.md + backlog + changelog setup, mentions "session continuity", "persistent context", "project memory system", or is retrofitting an existing codebase that has no such system yet. Also use to explain or extend an already-bootstrapped bottle system (add a rule, start the archival script, add a new backlog section).
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Run OpenSpec backlog delivery — validate BACKLOG.md, plan TaskCards, orchestrate agents by phase, review gate, and update backlog state.
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Turn assumptions, funnel opportunities, and product questions into a prioritised, feasibility-checked experiment backlog. Filters by traffic reality, metric latency, and method feasibility — not just ICE/RICE scoring. Maintains a living portfolio with status (idea → designed → running → readout → archived). Load when the user says "what should we test next", "build an experiment backlog", "prioritise our tests", "where should we experiment", "what's worth testing", or when the experimentation orchestrator routes here.
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GitHub 이슈와 풀 리퀘스트를 분류하고 실행 예정 작업을 Linear에 연결하여 공개 진행 상황과 내부 담당자, 우선순위, 다음 조치를 정리합니다.
Organize open GitHub issues by category, risk, linked pull requests, duplicate candidates, and inactivity. Optionally analyze selected issues in depth, draft responses, and apply approved comments, labels, or closures to keep the backlog actionable.
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Organize open pull requests before a release, classify what to merge or defer, and track decisions in a resumable document. Guide review, merging, follow-up fixes, and closing requests already covered by other changes.
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Sort incoming email into decisions, drafted replies, and handled messages. Get a ranked list of important requests, deadlines, and past commitments, plus reply drafts based on your writing style, including from pasted email text.
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Identify maintenance problems across code, architecture, tests, dependencies, documentation, and infrastructure. Rank them by impact, risk, and effort, then produce a prioritized backlog with business reasons and a phased improvement plan alongside feature development.
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Review open GitHub issues, proposals, and pull requests to identify useful maintainer work. Get ranked candidates with evidence, dependencies, and validation needs, then begin work only on an item you explicitly select.
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Turn a new feature into user stories: short descriptions of what people need and why. Each story includes a design reference and testable acceptance criteria, with scope intended to fit within one sprint.
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Break a feature into job stories that describe the user's situation, motivation, and desired outcome. Add six to eight observable acceptance criteria per story, defining how success will be checked, and include links to designs or prototypes.
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Generate Terraform alerts for Cloud Run services, jobs, and worker pools using PromQL, a monitoring query language. Monitor errors, latency, resource usage, job failures, and queue delays, with configurable thresholds and explanations of when each alert triggers.
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Organize Linear or Jira backlogs through the Composio CLI, a command-line tool. Fetch issues in bulk, group likely duplicates, update labels, priorities, and owners, then share a summary of changes in Slack.
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Turn GitHub issue reports into actionable work by searching for duplicates, attempting reproduction, and assessing user impact. Organize issues with existing labels, appropriate owners, and milestones, while clearly recording what was and was not verified.
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Find Linear issues reporting the same underlying bug, compare their evidence, and propose which issue to keep. After approval, transfer unique findings and relevant people’s details, then close duplicates with links to the surviving issue.
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