Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.
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。
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概要と使いどころ
Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.
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 implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
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。
Archive multiple completed changes at once. Use when archiving several parallel changes.
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。
Complete the Classic technical design and obtain user confirmation. Use when the user invokes /comet-design or Classic Runtime enters Design.
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。
Complete browser automation with Playwright. Auto-detects dev servers, writes reusable test scripts, and supports screenshots, responsive checks, UX validation, login flows, link checks, and arbitrary browser automation. Use when the user wants to test a website, automate browser interactions, validate web functionality, or perform browser-based testing.
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。
Discover, find, compare, audit, repair, adapt, craft, run, debrief, save, and prepare repeatable AI-agent loops for publication. Use when a user asks to analyze code or coding threads for recurring work, find a published loop, interview them to turn a goal into a bounded loop, review a loop for weak checks or unsafe authority, execute a loop with an evidence receipt, learn from completed runs, save or reuse a project loop, or validate and submit a loop to Loop Library.
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。
Lookup documented AKS fixes only when the prompt includes an exact catalog signature and all of its qualifiers: VMCannotFitEphemeralOSDisk; NodePoolMcVersionIncompatible; 'NodeImageVersion is not accepted'; AKS SkuNotAvailable with size, location, and zone; ZonalAllocationFailed with insufficient zone capacity; OverconstrainedAllocationRequest with listed constraints; nested AKS vmssCSE/CSE VMExtensionError_OutboundConnFail, VMExtensionError_K8SAPIServerConnFail, or VMExtensionError_K8SAPIServerDNSLookupFail; or AllocationFailed with the full cataloged internal-error or insufficient-regional-capacity message. Never use for quota errors, code-only or bare wrappers, generic symptoms, incomplete signatures, or failures outside AKS; use aks-troubleshooting or azure-diagnostics.
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。
Assess whether source code is ready to deploy to Azure — the check BEFORE infrastructure work. Evaluates build health, app completeness, dependencies and local services, stack compatibility, and deployment feasibility. Answers questions about what your app needs before it can be deployed — frameworks, dependencies, and configuration. Checks whether dependencies are compatible and identifies deployment blockers and unsupported frameworks. WHEN: "evaluate my repo", "is my app ready to deploy", "what does my app need to deploy", "what do I need before deploying", "does my app need", "can I ship this to Azure", "scan my repo for issues", "is this app deployable", "check if my app is ready for Azure", "do I need a Dockerfile", "what's blocking my deployment", "are there any blockers", "are my dependencies compatible", "does Azure support my framework", "what needs to change before deploying", "check my app configuration".
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。
Apply Steve McConnell-inspired construction rules when implementing routines, variables, classes, control flow, defensive code, or tests.
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。
Design new Claude skills from structured idea specifications. Use when the skill auto-generation pipeline needs to produce a Claude CLI prompt that creates a complete skill directory (SKILL.md, references, scripts, tests) following repository conventions.
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。
Stops defensive writing across the entire paper lifecycle — writing, revising, cutting, and organizing experiments. Treats the paper as a press conference, not a project summary, lab log, or self-audit: identify the single most publishable strength of the work and build the most favorable, complete, and persuasive narrative around it. Never present everything evenly, never volunteer weakness, never write an experiment diary, never attack the paper on the reviewer's behalf. Triggers: polish my paper, revise manuscript, write abstract, write introduction, write conclusion, shorten paper, rebuttal, respond to reviewers, organize experiments, defensive writing, AI-flavored academic writing.
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 the user asks to "triage launch feedback", "cluster reviews, comments, and board posts into themes", or "set up a you asked, we shipped loop"; produces a feedback theme digest (frequency, severity, representative quotes per theme), an open→planned→started→completed/declined status loop with duplicate-merge and notification rules, shipped-change announcement material, and a compliant social-proof harvest protocol (never incentivized store reviews). Not for repurposing or amplifying the harvested proof — use content-amplifier; not for executing testimonial outreach threads — use outreach-manager. 反馈分诊/状态环/社证收割/评测合规
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 the user asks to "run a deliverability pre-flight before I send", "check my SPF/DKIM/DMARC/BIMI", "why am I landing in spam / promotions", or "score my sender reputation and list hygiene"; runs the ONE-TIME pre-send SEND S1 authentication pre-flight and builds the SEND S (Sender-integrity / Deliverability) evidence read — DNS + DMARC-RUA auth, domain/IP reputation, inbox placement, content/link/render, and point-in-time bounce/complaint hygiene — using Pass/Partial/Fail/Unknown/N/A states and scoring only at complete applicable coverage. Not for the recurring hygiene trend — use list-hygiene-monitor; not for final EQS or veto verdicts — use email-quality-auditor; not for segments/suppression lists — use list-segment-builder. 邮件送达率预检/SPF DKIM DMARC认证/发件域声誉
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 the user asks to record/query the brand narrative canon, tagline, message hierarchy, voice/naming rules, or a canon re-version; curates complete versioned canon events through the append-only narrative stream and derived views. Not for TALE scoring — use narrative-quality-auditor; not for authoring the system — use message-system-architect. 品牌叙事台账/canon 记录/语气与命名规范
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。
当用户明确要求"填充示例内容""生成示例""补充 LaTeX 示例"时使用。AI 增强版 LaTeX 示例智能生成器,实现 AI 与硬编码的有机融合:AI 做"语义理解"(分析章节主题、推理资源相关性、生成连贯叙述),硬编码做"结构保护"(格式验证、哈希校验、访问控制)。
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。
Complete AI coding workflow system. Orchestration patterns, 18 hook events, 8 agents, cross-agent support, reference guides, and searchable learnings. Works with Claude Code, Cursor, and 32+ agents.
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。
Apply the Zeigarnik Effect — incomplete tasks stay mentally active. Use when designing progress indicators, saved drafts, and return hooks. For the emotional shape of the ending, use `peak-end-rule`.
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。
Specify one micro-interaction completely — trigger, rules, feedback, loops, and modes. Use when handing a single interaction to engineering. For motion craft alone use `animation-principles`; for multi-state components use `state-machine`.
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。
Apply the Law of Closure — the eye completes implied shapes from partial forms. Use when reducing visual weight by dropping borders or letting negative space suggest structure. For explicit containers, use `law-of-common-region`.
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 a complete Amazon Aurora database cluster with instances, handling cluster creation, instance provisioning, and Secrets Manager password management in the proper sequence. Use when setting up new Aurora MySQL or PostgreSQL clusters with production-ready configuration.
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。
Guides the end-to-end AWS resilience lifecycle integrating Resilience Hub v2, Fault Injection Service, and Application Recovery Controller. Covers the Define → Test → Operate workflow: from policy creation through failure mode assessment, to FIS experiment validation, to ARC operational controls. Applicable when the user wants a complete resilience strategy, needs to connect findings to experiments to controls, or is planning a resilience program. Also applicable for the meta question of whether marking NGRH findings as resolved is enough, whether they are "done" after resolving findings, or how to validate findings before resolving them. Not applicable for resolving or remediating a specific individual finding (see resilience-hub-failure-mode-assessment), or when a single service is explicitly named (e.g. "what FIS experiment should I run").
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。
Guides Amazon SES onboarding for domain-based email sending. Covers identity configuration, production access, an optional first test send, and troubleshooting setup, authentication, or sending failures. Use when setting up SES, resuming incomplete onboarding, or leaving the sandbox. Does not cover inbound email or Mail Manager, SMS/voice, WhatsApp, SNS, Pinpoint, or WorkMail.
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。
Provides authoritative compatibility checks, pricing estimates, connection troubleshooting, pre-warming guidance, and infrastructure mutations for Amazon Keyspaces (for Apache Cassandra). Covers LWT/batch operations, secondary indexes, materialized views, capacity modes, TTL, PITR, CDC, auto-scaling, multi-region keyspaces, UDTs, nodetool diagnostics parsing, SQL-to-Cassandra migration, and Cassandra-to-Keyspaces migration scenarios. Agents frequently produce incomplete or incorrect answers about Keyspaces feature support without this skill loaded.
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。
Build a complete web scraping Actor with Crawlee and deploy to Apify. Use when you need end-to-end web scraping on Apify: defining an input schema, building a router-based Crawlee crawler, extracting structured data, storing results in a dataset, testing locally, and deploying the Actor to the platform. Trigger with "apify scrape website", "build apify actor", "crawlee scraper", "apify main workflow".
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。