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概要と使いどころ
Use when reviewing a codebase for architectural friction, shallow modules, poor test seams, scattered behavior, duplicated orchestration, or opportunities to deepen modules before implementing a ticket or workflow.
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Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).
日本語の概要は準備中です。原文の説明を表示しています。
Use when you have a written implementation plan to execute in a separate session with review checkpoints
日本語の概要は準備中です。原文の説明を表示しています。
Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.
日本語の概要は準備中です。原文の説明を表示しています。
Guidance for a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource.
日本語の概要は準備中です。原文の説明を表示しています。
name: advisory-committee description: "4-agent AI advisory committee for strategic decisions. Runs CS, Marketing, Finance, and Tech agents in sequence to analyze proposals and deliver a majority-vo...
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占事吉凶 · 测吉凶：针对**某一件具体事、某一天、某一刻**的吉凶研判与择吉建议。 运用「黄历择日 + 四柱命理本命喜忌 + 阴阳五行天时地利 + 天人感应/梅花心易」四层独立推演， 再交叉汇聚成【吉 / 平·宜谨慎 / 凶·宜改期】的整体倾向与可执行建议。 当用户问：测吉凶、占吉凶、这事能不能做、今天适不适合出门/旅行/搬家/开业/签约/求医、 出行吉凶、看日子、择日、挑个好日子、黄历、老黄历、今天宜不宜、宜忌、冲煞、起一卦、 算算这件事顺不顺、"临出发前忽然心悸/心慌，是不是预兆"、"我有种不好的预感" 时使用。 English triggers: "is today auspicious", "is it a good day to travel/move/sign", "should I go today", "pick an auspicious day", "Chinese almanac / huangli", "divination for a decision", "I have a bad feeling about going out today". 内置离线脚本：公历→农历+完整四柱+十神（bazi.py）、黄历宜忌/建除/值神/廿八宿/彭祖百忌/ 冲煞/吉神凶煞/逐时辰吉凶+梅花时间起卦（almanac.py）、经纬度定位+当天当地天气（geoweather.py）。 边界：要**批一生八字/大运流年**请用 `bazi` 技能；要**解梦**请用 `zhougong-dream-interpretation`。 即使用户只是随口问「今天出门好不好」「这事顺不顺」，也应主动使用本技能。
日本語の概要は準備中です。原文の説明を表示しています。
Research current job markets and hiring requirements, analyze recent job descriptions (JDs), compare them with a user's resume, projects, skills, and constraints, and turn evidence gaps into prioritized career actions. Use when students, job seekers, or career changers ask about current role or industry outlook (including “现在行情怎么样”), whether a role or JD fits them (including “这个JD适合我吗”), cross-platform JD sampling, resume evidence gaps or truthful tailoring, what career skill to learn next, target-role course or certificate decisions, application readiness, or a capacity-bounded 30/60/90-day job-search plan. Do not use for unrelated personal or education advice, simple factual lookups, automatic job applications, or unsupported resume rewriting.
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User asks for design, planning, or approach exploration before implementation. Covers new features, components, refactors, or architecture decisions. Creates design docs and proposes approaches with trade-offs.
日本語の概要は準備中です。原文の説明を表示しています。
Capture a solved, verified problem as a durable learning in `docs/solutions/` so the next agent or engineer does not repeat the mistake or redo the investigation, and keep the `CONCEPTS.md` glossary in step. Use after a fix, debugging session, or design decision whose reasoning is not readable from the final code, tests, or existing docs — "document this", "write up what we learned", "capture this learning", "add it to solutions", "that worked, save it for next time". Writes nothing for routine fixes the code already explains. For auditing or cleaning up existing learnings, use `learn-with-docs-refresh`.
日本語の概要は準備中です。原文の説明を表示しています。
Draft the QA scope and plain-language Given/When/Then test scenarios for a Jira ticket, built from the full ticket, the decisions made in its comments, and the actual code change read commit by commit (open PR, the ticket's merged PR, the branch against its base, or a named commit range). Saves a Markdown draft under docs/, iterates with the user, then posts it to the ticket as a new Jira comment only after explicit approval. Use on "QA scope for PROJ-123", "what should QA test", "write test scenarios for QA", "hand this ticket to QA", "prep the QA handoff", "gherkin scenarios for this ticket", or when a branch is ready for manual testing — even when the user only names the ticket or says "this branch".
日本語の概要は準備中です。原文の説明を表示しています。
Select, write, or review proportionate tests and verification for dygo Go packages, PostgreSQL behavior, metadata, CLI contracts, Studio, integrations, and releases. Use when test scope or confidence strategy is the main decision.
日本語の概要は準備中です。原文の説明を表示しています。
Creates comprehensive handoff documents for seamless AI agent session transfers. Triggered when: (1) user requests handoff/memory/context save, (2) context window approaches capacity, (3) major task milestone completed, (4) work session ending, (5) user says 'save state', 'create handoff', 'I need to pause', 'context is getting full', (6) resuming work with 'load handoff', 'resume from', 'continue where we left off'. Proactively suggests handoffs after substantial work (multiple file edits, complex debugging, architecture decisions). Solves long-running agent context exhaustion by enabling fresh agents to continue with zero ambiguity.
日本語の概要は準備中です。原文の説明を表示しています。
Use Notion to track meeting patterns, identify communication insights, and improve team coordination. Record decisions, attendees, and outcomes for trend analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Systematically document research findings, competitive analysis, market trends, and user insights in Notion. Build searchable research repository for data-driven decisions.
日本語の概要は準備中です。原文の説明を表示しています。
Grounds every implementation decision in official documentation. Use when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.
日本語の概要は準備中です。原文の説明を表示しています。
Capture meeting notes with clear structure: attendees, agenda, decisions, action items with owners and deadlines. Ensure accountability and alignment post-meeting.
日本語の概要は準備中です。原文の説明を表示しています。
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
日本語の概要は準備中です。原文の説明を表示しています。
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
日本語の概要は準備中です。原文の説明を表示しています。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
日本語の概要は準備中です。原文の説明を表示しています。
Select and implement the right Azure compute platform for a workload. Decision tree guides choice based on workload characteristics, scaling needs, and operational maturity. Covers serverless, PaaS, containers, Kubernetes, and IaaS patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Persistent vector memory for Claude Code via LanceDB. Use when: remembering across sessions, storing lessons, recalling past decisions, maintaining context continuity. Tools: memory_store, memory_recall, memory_update, memory_forget, memory_merge.
日本語の概要は準備中です。原文の説明を表示しています。
Relentless delivery mode for complex, multi-step tasks. Use when: multi-file features, unclear root cause debugging, multi-angle research, architecture decisions with trade-offs. Activates parallel subagent dispatch and strict verification.
日本語の概要は準備中です。原文の説明を表示しています。
Project documentation structure — standard proj-[name]/ layout with ADRs, stories, and operations guides. Use when: initializing docs for a new project, recording architecture decisions, or maintaining project knowledge bases.
日本語の概要は準備中です。原文の説明を表示しています。