Agent Automation & UI Design Skills

Present a decision or confirmation request in the user's four-part format: 전후맥락 (context) → 추천 + 이유 (recommendation) → UI/UX 형태 (a scannable table/option-list) → ASIS→TOBE contrast, led by the recommendation so the user can say yes fast. Fire at genuine A-or-B / approval / explicit-ASIS-TOBE moments. Triggers on the user's verbatim phrases "ASIS TOBE로 설명", "ASIS-TOBE로 알려줘", "화면으로 ASIS TOBE로 설명", "의사결정 / 컨펌 요청", "이거 진행할까요?", and the softer "다음 진행할 것들 알려줘"; English equivalents: "present this as ASIS/TOBE", "give me the as-is to-be", "should I do A or B", "ask for my approval", "lay out the options". Do NOT fire for pure information with no decision, or trivial reversible actions you would just do.

Create a compact, reconstructible checkpoint immediately before context compaction. Persist only durable facts and decisions, overwrite one current resume anchor, verify Git and open-PR state, and emit one concrete next action plus a short /compact line. Use for "컴팩션 준비해줘", "컴팩션하고 이어서 진행할 수 있게 준비해줘", "핸드오프 준비해줘", or "prepare for compaction", or equivalent. Repeated execution must be idempotent and must not grow state files without bound.

Two-mode chained gap analysis. DETECT scans the current service end-to-end through three lenses — north-star alignment, correctness (bugs), and user-perspective (UX) — and enumerates concrete, severity-ranked gaps. Then BENCHMARK researches how reference/benchmark services actually solved each high-ranked gap and PROPOSES a closing approach. Use when the user says any of: "북극성 기준으로 부족한 점", "사용자 관점에서 부족한 점", "다른 벤치마크 서비스는 이 부분을 어떻게 해결했는지", "갭분석", "레퍼런스 서비스랑 비교해서 부족한 점 찾아줘" — or the English equivalents: "gap analysis", "what are we missing vs the ideal/north-star", "benchmark against reference services". Fires for both Korean and English phrasing. NOT for a whole-codebase multi-dimension audit (use ultracode-service-audit) or single-artifact prose review (use multi-persona-review) — this is the narrower gap-vs-benchmark loop.

Audit the health of an AI-coding harness — the CLAUDE.md / AGENTS.md files, rules, skills, agents, hooks, and commands that steer an agent in a repository — across four questions a linter cannot answer: is it TRUE (does it match the real code?), is it USED (do skills actually trigger and does the loop actually verify?), is it AFFORDABLE (is it inside the budget where instructions are still followed?), and is it SAFE (is a live, accurate instruction still a good idea — permission bypasses, unpinned remote scripts, untrusted content flowing in as instructions? — safety findings are flagged for the user's decision, never auto-removed). Then surgically correct or remove only what is proven wrong or dead. Use whenever the steering layer may have rotted or may not be working: "하네스 점검해줘", "하네스 드리프트 감사", "CLAUDE.md가 실제랑 맞는지 봐줘", "룰/스킬이 최신인지 확인해줘", "스킬이 제대로 활용되는지 봐줘", "루프 엔지니어링 잘 되고 있는지 검토해줘", "죽은 훅/커맨드 정리해줘", "하네스 안전한지 점검해줘", "audit my harness", "check the rules still match the real stack", "are my skills actually being used", "review the agent loop", "is my harness safe", after a stack or tooling migration, or when onboarding a repo whose steering docs look stale. Not a codebase security audit — it reads the steering layer, not application code. Every finding must be backed by stated-versus-measured evidence; never guess the correct value, and never remove a live path because it merely looks unused.

Apply the fixed model-role and thinking-effort policy whenever work is delegated to subagents or a model/effort choice is made: the orchestrator (top-tier model) DIRECTLY sets service direction, reviews plan/spec documents (with multi-persona-review), improves shipped features, and hunts performance/security problems; plan/spec/planning documents are AUTHORED by Opus, which also owns core implementation and V&V, at xhigh or above; repetitive implementation and E2E tests go to Sonnet at high or above — never delegate below those effort floors. Use whenever you are about to spawn an Agent/Task/Workflow worker, pick a model for a subtask, set a thinking/effort level, assign verification, or hand off orchestration because the current model's quota is exhausted. Trigger on "위임해", "에이전트로 돌려", "오케스트레이션", "모델 역할분담", "어떤 모델로", "effort 얼마로", "thinking level", "서브에이전트", or in English "delegate this", "spawn an agent for", "which model should", "route this task", "verify with", "orchestrate". Fire even when the user doesn't name the policy — any delegation decision is in scope.

A panel-review skill that critiques ONE artifact (launch post, README, doc, markdown, plan, design) via 3-5 disjoint user-perspective personas running in parallel, then synthesizes deduped, severity-ranked improvement points (P0/P1/P2). Use when the user says "작성글을 사용자 관점의 페르소나를 여러명 만들어서 (손넷 모델정도로) 피드백 받아바", "다면 리뷰 해볼까", "페르소나로 리뷰", "여러 관점으로 피드백", or in English "multi-persona review", "review this from different user perspectives", "get persona feedback on this post/README/doc", "panel review this artifact". Lighter than a full service audit — point it at ONE artifact, not a whole codebase. NOT for a whole-codebase multi-dimension audit (use ultracode-service-audit) or a single-axis gap-vs-benchmark loop (use gap-analysis-e2e).

Read the project's NORTHSTAR / vision doc, measure current state against the goal, then propose a forward direction plus prioritized feature proposals — persisted as a durable roadmap in docs/plans + memory so the plan survives /compact and new sessions. Use when the user asks where the project should go next or wants a backlog grounded in the vision. Fires on the user's real phrasings: "앞으로 어떤 방향으로 개선·발전시킬지 고민해봐", "NORTH.md / NORTHSTAR 보고 나아갈 방향 + 기능 제안", "나아갈 방향 + 기능제안 (수용 → 계획 수립하고 메모리에 기록)", "북극성 정렬 로드맵", as well as the English equivalents: "what direction should we take next", "propose a roadmap / feature backlog from the north star", "plan the next milestones and save it to memory". Not for detecting bugs or auditing current quality (see gap-analysis-e2e / ultracode-service-audit) — this skill DIRECTS forward planning.

When the same defect, mistake, or incident happens AGAIN — a recurrence, not a one-off — verify it against prior evidence (memory, rule case tables, git/CHANGELOG history), classify it as a simple slip vs a complex harness problem, then escalate the countermeasure one level up the ladder: record (1st) → forced rule with a case table (2nd) → structural gate — test, hook, or derive — once prose has failed (3rd+). Complex problems get countermeasure candidates designed by a multi-persona panel instead of a quick patch. Use for "재발했어", "같은 실수 또 했네", "이거 저번에도 그랬잖아", "재발방지 대책 등록해줘", "재발방지 룰 만들어", "this happened again", "same bug as last time", "add a recurrence countermeasure", "postmortem this failure". NOT for a first-time defect (fix it, record it, stop) and NOT a general steering-layer audit (that's harness-health-audit).

Detects when SPEC.md or PRD.md exceeds 300 lines and proposes feature-based splitting with a master route document. Use when SPEC.md grows too large to be effectively used as a single document.

Captures screenshots of key UI flows after E2E tests pass, runs an agent-side first-pass diff (regressions, console errors, layout shifts), then surfaces a checklist for the user's final approval. Use after /uzys:test passes on a UI track (csr-, ssr-, full). Adapts the GoalTrack screenshot-review pattern into a repeatable workflow.

Run a multi-agent, adversarially-verified full-service audit across 7 dimensions (code / UX / scalability / planning+north-star / security / promotion / extensible), separating findings into confirmed / unverified / rejected and producing a priority-ranked, M-numbered milestone roadmap (as many milestones as the findings warrant). Use when the user says "ultracode 전체 서비스 점검", "전체 서비스를 점검하자", "코드·UX·확장성·기획·북극성지표·보안·홍보 문제점을 파악하고 우선순위에 따라 개선", "다차원 서비스 감사", or in English "audit the whole service / full multi-dimensional service audit / find code, UX, scalability, planning, security, and marketing problems and prioritize fixes". The heavyweight superset audit — orchestrate it as a Workflow with fan-out finders and an adversarial verify pass. NOT for a single-artifact prose/README review (use multi-persona-review) or a single-axis gap-vs-benchmark loop (use gap-analysis-e2e) — those are the lighter siblings.