「event」の検索結果

Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini). Creates authentic, authoritative content that becomes the go-to citation source for AI models answering user questions. Use this skill when: - Creating content that should appear in AI search results (Perplexity, ChatGPT, Claude) - Building topical authority to become THE source AI cites for a topic - Launching a new product and need compelling, citable content - Creating blog posts, articles, social media, or press releases - Need content that references real trends, people, and recent events - Want AI-assisted content that doesn't sound AI-generated - Creating thought leadership content in any industry Triggers: "create content for", "write about", "research and write", "find experts for", "content for launch", "blog post about", "article on", "press release for", "AI search", "show up in AI", "Perplexity", "be cited by AI"

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Amplitude integration. Manage Users, Events. Use when the user wants to interact with Amplitude data.

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Deploy funnelcake (api + relay) to ANY environment (production, staging, poc) on GKE via ArgoCD. Use when: (1) Deploying new funnelcake commits, (2) Building Docker images for GKE (amd64), (3) Running ClickHouse migrations, (4) Troubleshooting ImagePullBackOff errors, (5) Syncing staging/poc after production deployment. Covers complete workflow with PRE-FLIGHT CHECKLIST to prevent common deployment failures.

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Fix NDK (Nostr Dev Kit) operations hanging indefinitely when relay connections stall. Use when: (1) App freezes during fetchEvents or publish calls, (2) No timeout errors despite network issues, (3) Relay connection appears stuck, (4) Using NDK with unstable or slow relays. NDK operations have no built-in timeout - wrap with Promise.race.

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。

Fix "content disappears after publishing" bugs caused by REST API indexing lag. Use when: (1) User publishes content but it doesn't appear in their feed/profile, (2) REST API returns stale data immediately after write operations, (3) Async indexing backends (ClickHouse, Elasticsearch, etc.) haven't processed new events, (4) Content shows briefly then vanishes on refresh. Applies to any system with separate write path (WebSocket/direct DB) and read path (REST API with async indexing).

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Fix Dart/Flutter services where calling start() after stop() is a silent no-op because stop() sets a _disposed (or similar) flag that start()'s guard short-circuits on. Use when: (1) A repository/service/controller has startListening/stopListening, subscribe/unsubscribe, open/close, or similar lifecycle methods, (2) Re-opening the service after closing it appears to do nothing — no subscription, no events, no error, (3) Unit tests that only exercise a single mount/open/start cycle pass while the real app breaks on the second visit to a screen, (4) A boolean flag is used both for "in the middle of tearing down this instance forever" AND for "currently stopped, can be re-started". Common in Riverpod/Bloc-driven screens that wire startListening() in initState and stopListening() in dispose — the second time the user visits the screen, nothing happens.

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 need to display chronological events and activities.

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 need to display dates and events in calendar format.

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。

Write spoken daily planning notes into an Obsidian Mandala Grid day-plan Markdown file. Use when the user says 今日的日計畫, 今日的日計劃, 日計畫, 日計劃, 青蛙, frog, 🐸, 九宮, 曼陀羅, Mandala Grid, 時段, time block, 日記, or asks to place spoken tasks/events/reflections into today's Obsidian daily plan sections.

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Create Fantastical calendar events and reminders from Codex on macOS. Use when the user asks Codex to add, schedule, parse, preview, or send a meeting, appointment, task, reminder, time block, daily plan item, 行事曆, 日曆, 會議, 待辦, or 提醒 into Fantastical.

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Instruments programs to record execution information for deterministic replay debugging. Use when debugging hard-to-reproduce bugs (race conditions, timing issues, intermittent failures, heisenbugs), reproducing production failures, or analyzing complex execution sequences. Records non-deterministic events (I/O, threading, randomness, time) to enable exact replay of program executions. Supports Python, JavaScript, Java, and C/C++ with both custom instrumentation and existing replay tools.

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Generate integration tests for multiple interacting components in Python. Use when testing interactions between: (1) Multiple services or APIs (REST/GraphQL endpoints, microservices), (2) Database operations with repositories/ORMs (SQLAlchemy, Django ORM), (3) External services (payment gateways, email services, third-party APIs), (4) Message queues and event-driven systems, (5) Full stack workflows (API + database + business logic). Provides test structure templates, fixtures, test data builders, and patterns for pytest-based integration testing.

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Automatically repair buggy code and generate comprehensive tests for Python, Java, and C++ programs. Use when users need to fix logic errors or runtime errors in functions, modules, or repositories. Accepts specifications via natural language descriptions, existing test cases, or input/output examples. Generates corrected code, creates or updates tests to verify correctness and prevent regressions, and produces a detailed report explaining the bug, fix, and testing strategy. Triggers on requests like "fix this bug", "repair this code", "debug this function", or "this code is broken".

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。

Write blameless incident postmortems with timeline reconstruction, root cause analysis, action items, and preventive measures

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Audit Meta Ads measurement, Pixel and Conversions API, attribution, Facebook and Instagram creative, audiences, placements, automation, budgets, account structure, and policy. Use for Meta Ads, Facebook Ads, Instagram Ads, Advantage+, Pixel, CAPI, Events Manager, creative fatigue, or Meta campaign optimization.

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Runs a structured clarifying interview for new project requests before building. Instead of writing code, it outputs a fully specified prompt.md for a fresh agent session to execute, preventing expensive mistakes.

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Translate a vague request or GitHub issue into a concrete, testable spec using five structured elements (problem, scope, acceptance criteria, edge cases, success criterion) before writing any code. Prevents scope creep, PR churn, and mid-implementation pivots.

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Enterprise BPMN 2.0 diagram generator — converts natural language process descriptions into OMG-compliant BPMN 2.0 XML files and SVG previews via a 4-phase pipeline: Intent Extraction (LLM → JSON Logic-Core) → Validation (deadlock detection, structural soundness) → ElkJS Auto-Layout → BPMN XML + SVG output. Supports: multi-pool collaborations, message flows, boundary events (timer/error/signal), loop/multi-instance markers, data objects, all gateway types with correct gatewayDirection, and all BPMN 2.0 task types. Use this skill whenever the user wants to create, generate, or model a BPMN diagram, process flow, or workflow — even if they say "draw a process", "model this workflow", "make a BPMN for...", "create a Prozessmodell", "visualize this process", or describe a business process in natural language. Also use for editing or extending existing BPMN Logic-Core JSON.

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Use when designing, querying, or troubleshooting the Financial Services Cloud data model — including managed-package (FinServ__ namespace) and Core FSC (standard objects, no namespace) object structures, household relationship modeling, financial account ownership, and the FSC rollup framework. Trigger keywords: FSC data model, FinancialAccount, FinancialHolding, FinancialAccountRole, FinancialAccountParty, FinServ namespace, household rollup, AssetsAndLiabilities, FinancialGoal, LifeEvent, AccountContactRelation FSC. NOT for setting up financial accounts and roles in Setup — use admin/financial-account-setup. NOT for household membership and rollup scheduling — use admin/household-model-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。

Handle async operations and prevent flaky 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。

Enforces baseline comparisons, cross-validation, interpretation, and leakage prevention for ML pipelines

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 reworking a change to prevent tech debt, or auditing existing debt to categorize, score, and prioritize the refactor backlog.

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 microservices architectures with service boundaries, event-driven communication, and resilience patterns. Use when building distributed systems, decomposing monoliths, or implementing microservices.

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Code review practices with technical rigor and verification gates. Use for receiving feedback, requesting code-reviewer subagent reviews, or preventing false completion claims in pull requests.

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。