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Calculates empty slots in a couple's calendar and generates an optimized date course using OpenAI.
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Basé sur la classification professionnelle SOC
Systematic debugging with root cause investigation. Four phases: investigate, analyze, hypothesize, implement. Iron Law: no fixes without root cause. Use when asked to "debug this", "fix this bug", "why is this broken", "investigate this error", or "root cause analysis". Proactively invoke this skill (do NOT debug directly) when the user reports errors, 500 errors, stack traces, unexpected behavior, "it was working yesterday", or is troubleshooting why something stopped working. (gstack)
Systematically QA test a web application and fix bugs found. Runs QA testing, then iteratively fixes bugs in source code, committing each fix atomically and re-verifying. Use when asked to "qa", "QA", "test this site", "find bugs", "test and fix", or "fix what's broken". Proactively suggest when the user says a feature is ready for testing or asks "does this work?". Three tiers: Quick (critical/high only), Standard (+ medium), Exhaustive (+ cosmetic). Produces before/after health scores, fix evidence, and a ship-readiness summary. For report-only mode, use /qa-only. (gstack)
Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues. Use when asked to "review this PR", "code review", "pre-landing review", or "check my diff". Proactively suggest when the user is about to merge or land code changes. (gstack)
Ship workflow: detect + merge base branch, run tests, review diff, bump VERSION, update CHANGELOG, commit, push, create PR. Use when asked to "ship", "deploy", "push to main", "create a PR", "merge and push", or "get it deployed". Proactively invoke this skill (do NOT push/PR directly) when the user says code is ready, asks about deploying, wants to push code up, or asks to create a PR. (gstack)
| name | ai_date_planner |
| description | Calculates empty slots in a couple's calendar and generates an optimized date course using OpenAI. |
목적: 커플 사용자의 일정 달력을 스캔하여 빈 슬롯을 찾아내고, 위시리스트 태그를 프롬프트로 엮어 LLM에 데이트 코스 큐레이션을 요청하는 스킬.
couple_id와 target_date를 파라미터로 받아서 해당 날짜의 schedules 레코드를 모두 읽어옵니다.wishlists에서 가장 많이 언급된 카테고리를 프롬프트 컨텍스트에 담아 GPT-4에 던져 가장 적합한 실내/실외 데이트 코스 JSON을 반환받습니다.이 스킬은 프론트엔드 달력 뷰(모달)에서 사용자가 "AI 코스 조율하기 ✨" 버튼을 누를 때 호출됩니다.
// 프론트엔드 클라이언트 호출 예시
const { data, error } = await supabase.functions.invoke('ai-date-planner', {
body: { couple_id: 'uuid-1234', target_date: '2026-03-24' }
})
if (data) {
console.log('AI Recommendation:', data.recommendation)
// 예: "오후 4시에 성수동 팝업스토어에서 만나는 것은 어떨까요?"
}