'tip' 검색 결과

Evaluate threat intelligence platforms, which collect and organize cyber threat information. Define requirements, compare integrations and operating costs, plan practical trials, and use weighted scoring to select a platform and outline its rollout.

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• Preparing requirements for TIP procurement
• Comparing platforms before a TIP migration
• Checking whether an existing TIP meets team needs

Explain tips shown in senpi or omo by checking the installed tip list, user settings, and implementation code. Learn what a feature actually does, why a tip appears, and which tips your setup can show.

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• Understand a Tip: line shown during a session
• Check which tips your settings allow
• Explore how model fallback guidance works

Update an EXISTING Tip in the ai-product-dev-tips repository — edit its README, add or fix code, refresh outdated information, fix mistakes — while keeping the repo's format conventions and syncing the root README link. Use this whenever the user wants to update, edit, fix, revise, refresh, correct, or complete an existing Tip in this repo — e.g. "nlp_processing/29 の README を更新して", "〇〇の Tip を最新仕様に直して", "image_processing/11 の説明を修正して", "あの Tip のリンク切れを直して", "この Tip を完成版にして". It locates the target Tip, studies the current format conventions (shared with the ai-product-dev-tips-create skill), applies consistent edits, verifies the content with web research (no fabrication), and syncs the root README link (title text / [In-progress]). This is for UPDATING existing Tips, not creating new ones — to add a brand-new Tip use the ai-product-dev-tips-create skill instead. Trigger this even if the user doesn't say "skill".

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Scaffold a new Tip in the ai-product-dev-tips repository following the existing directory/format conventions, and register its link in the root README.md. Use this whenever the user wants to add, create, or write a new Tip in this repo — e.g. "nlp_processing に〜の Tip を追加して", "新しい Tips を作って", "〜の解説 Tip を書いて", "this repo に〜のネタを追加". It picks the right category and next sequential number, matches the README format of nearby Tips, generates code scaffolding (Dockerfile / requirements.txt / *_cpu.sh / *_gpu.sh / *.py) only when the Tip needs runnable code, and inserts the link into the correct <details> section of the root README. Trigger this even if the user doesn't say the word "skill" — any request to add a new entry to this Tips collection should use it.

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Implement and review Apple TipKit feature-discovery UI for iOS 17+ apps. Use when adding or auditing in-app tips, contextual help, coach marks, Tip, TipView, popoverTip, rules, events, actions, display frequency, testing overrides, reusable tip identifiers, or iOS 18+ TipGroup and CloudKit tip sync; avoid for generic SwiftUI navigation or layout outside tip presentation.

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Implement, review, or improve in-app tips and onboarding using Apple's TipKit framework. Use when adding feature discovery tooltips, onboarding flows, contextual tips, first-run experiences, coach marks, or working with Tip protocol, TipView, popoverTip, tip rules, tip events, or feature education UI.

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Expert patterns for adding multiplayer to single-player games including client-server architecture, authoritative server design, MultiplayerSynchronizer, lag compensation (client prediction, server reconciliation), input buffering, and anti-cheat measures. Use when retrofitting multiplayer, porting to online play, or designing networked gameplay. Trigger keywords: MultiplayerPeer, ENetMultiplayerPeer, SceneMultiplayer, MultiplayerSynchronizer, rpc, rpc_id, multiplayer_authority, client_prediction, server_reconciliation, lag_compensation, rollback.

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Expert patterns for adding multiplayer to single-player games including client-server architecture, authoritative server design, MultiplayerSynchronizer, lag compensation (client prediction, server reconciliation), input buffering, and anti-cheat measures. Use when retrofitting multiplayer, porting to online play, or designing networked gameplay. Trigger keywords: MultiplayerPeer, ENetMultiplayerPeer, SceneMultiplayer, MultiplayerSynchronizer, rpc, rpc_id, multiplayer_authority, client_prediction, server_reconciliation, lag_compensation, rollback.

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Claude Code の過去のセッション記録（~/.claude の履歴・セッションログ・memory）から、他のメンバーと共有できる運用 Tips を抽出し、公式ドキュメントや論文などの一次情報で裏付けを取って、Markdown・Artifact・Notion に公開する。「過去の会話から Tips をまとめて」「Claude Code の使い方をチームに共有したい」「今月の学びを Tips にして」などの依頼で使う。セッション 1 本の効率採点ではない（それは evaluate-session の領域）。週次のナレッジカード提出は knowledge-cards で行い、このスキルはカードや記録から Tips 文書を作る下流工程にあたる。

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Review tooltips so their extra information is available to screen reader users. Check accessible names, meaning labels available to assistive technology, and links to the elements that trigger them, then suggest fixes and verification steps.

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• Checking whether tooltip information can be read aloud
• Reviewing links between tooltips and their triggers
• Auditing shared tooltip components

Review tooltips so keyboard and screen reader users can access their explanations. Check the rendered HTML, accessible associations, hover and focus behavior, Escape dismissal, and contrast, then identify the elements and attributes that need fixes.

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• Checking keyboard access to tooltips
• Reviewing tooltip associations for screen readers
• Checking hover, focus, and Escape behavior

Simulate quantum dynamics, steady states, and spectra with QuTiP 5. The skill guides solver selection and checks physical assumptions, units, state validity, and numerical convergence so local simulation results can be reviewed with their limitations.

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• Simulating quantum dynamics with environmental dissipation
• Choosing a solver for a quantum model
• Checking numerical convergence and state validity

Implement Kotlin applications with asynchronous tasks, shared code across platforms, Android interfaces, and servers. The skill covers state modeling, cancellation handling, tests, and code checks, with guidance for Compose, Ktor, and Flow data streams.

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• Implement asynchronous tasks with coroutines and Flow
• Design shared code for Kotlin Multiplatform
• Build Android interfaces with Jetpack Compose

Build networked games with Godot 4.7 high-level multiplayer: set up an ENetMultiplayerPeer server/client, define RPCs with the @rpc annotation (call via rpc()/rpc_id()), set per-node multiplayer authority, and replicate state with MultiplayerSpawner and MultiplayerSynchronizer. Use when adding multiplayer/networking to a Godot project, writing @rpc functions, or syncing player/world state across peers.

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API reference: TipKit. Tip protocol, TipView, PopoverTipView, Tips.configure, inline and popover tips.

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最新AI技術動向のレポート（最新 / 週次 / 月次 / 特定トピック別）を Web 検索・WebFetch・GitHub/Hugging Face MCP で調査して生成し、Yagami360/ai-product-dev-tips リポジトリの GitHub Issue として投稿するスキル。ユーザーが「AI技術のキャッチアップ」「最新AIニュースまとめ」「週次/月次のAI動向レポート」「〇〇（例: AI Agent, RAG, VLM, Physical AI, Claude Code）についての技術調査レポート」「AI Tech Catchup レポートを作って」などを求めたとき、たとえ "skill" や "Issue" という単語が無くても必ずこのスキルを使うこと。直近のAI業界の最新情報を調べてまとめてほしい・GitHub Issue 化してほしいという依頼全般で発動する。AI とは無関係な一般的な技術調査や、このリポジトリへの Tip 追加（ai-product-dev-tips-create スキルの領分）には使わない。

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YouTube動画の文字起こしから約5,000字のTips向けノウハウ記事を作成しoutput/に保存する。「Tips記事にして」「/tips-post」で起動。

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Kotlin Coroutines와 Flow로 Android 및 Kotlin Multiplatform의 비동기 작업과 데이터 갱신을 구현하고 병렬 실행, 화면 상태, 취소, 오류 처리와 테스트를 다룹니다.

• 여러 데이터를 병렬로 불러옵니다
• StateFlow로 화면 상태를 관리합니다
• 검색 입력을 조절하고 통신을 재시도합니다

Evaluates and selects Threat Intelligence Platform (TIP) products based on organizational requirements including feed integration capability, STIX/TAXII support, workflow automation, analyst interface, and total cost of ownership. Use when conducting a TIP procurement, migrating between TIP solutions, or assessing whether the current TIP meets program maturity requirements. Activates for requests involving ThreatConnect, MISP, OpenCTI, Anomali, EclecticIQ, or TIP procurement decisions.

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Evaluate code generation models with HumanEval, MBPP, and other benchmarks. Test generated programs, compare models across programming languages, and record pass@k scores, which estimate the chance that at least one of k solutions passes the tests.

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• Comparing code generation models on shared benchmarks
• Measuring correctness across programming languages
• Evaluating models trained to follow instructions

Evaluate code generation models with HumanEval, MBPP, and multilingual benchmarks. The skill guides test execution and model comparisons using pass@k, an estimate of whether at least one of k generated solutions passes the tests.

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• Compare code generation models on shared benchmarks
• Measure code generation performance across languages
• Evaluate instruction-tuned coding models

Simulate quantum systems in Python with QuTiP, including open systems that interact with their surroundings. Calculate time evolution, energy loss, and entanglement, then visualize states and results for physics research or educational experiments.

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• Simulate the decay of a harmonic oscillator
• Track changes in two-qubit entanglement
• Study interactions between an atom and a cavity

Evaluate code generation models with HumanEval, MBPP, and multilingual benchmarks. The skill guides test execution and model comparisons using pass@k, an estimate of whether at least one of k generated solutions passes the tests.

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• Compare code generation models on shared benchmarks
• Measure code generation performance across languages
• Evaluate instruction-tuned coding models

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

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