「que」の検索結果

Prepares a change request pack (description and justification, scope, schedule, implementation plan, risk as stated, rollback, test evidence as provided, communications, approvals route) from an engineer's notes, ticket or pull request description, with UNKNOWN for anything not provided and a question list for the engineer. Never rates risk or marks a change tested or approved. Use when the user asks to "write the change request for this", "fill in the change ticket from my notes", "prepare the CAB submission" or "turn this pull request into an RFC". Do not use for the step-by-step procedure with commands and rollback, use runbook-drafter instead; for release notes describing what shipped, use release-notes-writer. Drafts for human review; never approves, authorises or signs off.

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。

Assembles a DRAFT capital expenditure request pack from the requester's inputs: business need, options including do nothing, costs exactly as provided, benefits as stated, risks, assumptions, budget status and the approvals route read from the organisation's own delegation of authority, with UNKNOWN for every missing figure, date or name. Use when the user asks to "prepare a capex request", "draft the business case for this equipment", "fill in the capital request form", "structure this investment proposal" or "what approvals does this spend need". Do not use for a board or committee decision paper, use board-paper-skeleton instead; for an IT change approval, use change-request-pack; to pressure-test a finished business case, use cfo-reviewer. Drafts for human review; never approves, authorises or signs off.

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。

Azure Queue Storage JavaScript/TypeScript SDK (@azure/storage-queue) for message queue operations. Use for sending, receiving, peeking, and deleting messages in queues.

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。

TanStack Query (React Query) v5 best practices for data fetching, caching, mutations, and server state management. Use when building data-driven React applications, setting up query configurations, implementing mutations/optimistic updates, configuring caching strategies, integrating with SSR, or fixing v4→v5 migration errors.

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。

ALWAYS use this skill when the user asks to schedule, automate, set up recurring tasks, create a cron job, or anything involving timed / periodic execution. Do NOT use the local system crontab — scheduled tasks are stored on the Unique AI Platform and executed by a Kubernetes CronJob, not locally. Scheduled tasks always run on the current assistant (`$UNIQUE_ASSISTANT_ID`); never ask the user which assistant to use, neither in chat nor via `unique-cli elicit ask`. This skill covers creating, listing, updating, enabling, disabling, and deleting scheduled tasks via the unique-cli schedule command.

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。

ALWAYS use this skill whenever you would otherwise ask the user a question in free-form chat -- for clarifications, confirmations (especially destructive actions), missing parameters, multiple-choice decisions, or structured form input. Elicitations are routed through the Unique AI Platform UI via `unique-cli elicit create` + `elicit wait` (the default polling pattern) or a single supervised `unique-cli elicit ask` call (only when your agent instructions say your environment supervises the wait) so the user gets a proper structured prompt and you get a structured answer back. Do NOT ask the user in plain chat when you can use this skill instead.

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。

Windows アプリ開発 (WinUI 3 / Windows App SDK) のテスト・パフォーマンス・ アクセシビリティ・スレッドリファレンス。MSTest, xUnit, NUnit, WinAppDriver, Appium, Playwright, WebView2 テスト, WACK 認定, MSIX サイドローディング, CI。 プロファイリング, WPT, WPA, GC, 起動性能, XAML レイアウト/読み込み最適化, ListView/GridView 仮想化, DispatcherQueue。UI Automation, AutomationProperties, automation peers, キーボード操作性, ハイコントラストテーマ, Narrator。 DispatcherQueue, DispatcherQueueTimer, WinRT 非同期パターン, async/await, ConfigureAwait, スレッドプール, STA/MTA, デッドロック回避, バックグラウンドタスク。

Agent fallback for CBaseEntity_GetHammerUniqueId (auto-generated, category: vfunc). Locate CBaseEntity::GetHammerUniqueId in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CBaseEntity_GetHammerUniqueId, CBaseEntity::GetHammerUniqueId

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。

[BETA] AEM Cloud Service expert skill — handle an explicitly-unbounded query (`p.limit=-1` predicate or JCR `setLimit(-1)`): bound it when capping is provably safe, otherwise flag it for human pagination. Use for "bound my query", "unbounded query", "query causing OOM", or a scan that flags `p.limit=-1`. Top CSO OOM cause: an unbounded result set traversed in a loop fills the heap and saturates the instance. The analyzer locates the explicit markers; the recipe triages each by how the result is consumed — single-result → 1, already-bounded list → N, iterate-all on the request path → escalate. Never silently cap a result the caller reads in full. This skill is in beta. Verify all outputs before applying them to production projects.

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。

Snowflake, BigQuery, clustering, partitioning, and materialized views for warehouse performance. Activate on: Snowflake, BigQuery, Redshift, query optimization, clustering, partitioning, materialized view, warehouse cost, query profile. NOT for: dbt model structure (use dbt-analytics-engineer), data modeling (use dimensional-modeler).

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。

Author a pull request an AI coding agent can actually get merged: a scoped, coherent diff; a Summary and Test Plan backed by real evidence; correct triage of required-and-blocking CI gates versus external/advisory checks (e.g. a Cloudflare Pages preview build); draft-while-WIP discipline; named fixup commits for real review findings; and a clean landing through a merge queue without force-pushing or bypassing branch protection. Use when opening, updating, triaging red CI on, or landing an agent-authored GitHub PR. NOT for this repo's internal release ceremony, actor embodiments, or contributor mirror-sync mechanics (use port-daddy-internal-dev), tracking backlog/issue lifecycle across a board (use agent-issue-tracker-workflow), or deciding what to build next / sequencing a roadmap (use legible-roadmap-with-sidequests).

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。

FaceTimeの内部状態や発信準備を確認し、設定済みの所有者宛てに承認付きで音声・ビデオ通話を発信したり、通話の終了をリクエストしたりします。

• 通話の内部状態と発信準備の確認
• 設定済みの所有者へ音声通話したいとき
• 明示的にビデオ通話を頼みたいとき

AIへの依頼文から目的や不足情報を整理し、作業範囲に合うECCのコマンドやスキルを提案します。診断と改善理由を添え、そのまま貼り付けて使える依頼文に書き直します。

• 曖昧な開発依頼を具体化したいとき
• 依頼文に完了条件と検証を加えたいとき
• 作業に合うECCの構成を選びたいとき

Ruby on Railsアプリの実装・レビューで、業務処理や検索、フォームの責務を整理するスキル。データ取得の無駄を防ぎ、バックグラウンド処理や画面部品の設計も支援します。

• 大きなcontrollerの業務処理の分離
• 複数モデルを更新するフォームの設計
• 重複する検索やデータ取得の見直し

H100やH200のGPU在庫を調べ、固定料金の見積もり依頼や調達状況を確認します。端末の認証解除と、明示的な許可に基づくノード検証にも対応します。

• H100やH200の在庫確認
• 固定料金の見積もりを依頼したいとき
• 見積もりや調達の進捗確認

Spring Bootのデータベース処理を設計・改善するスキル。JPA/Hibernateのデータ構造や関連付け、検索、トランザクションを見直し、不要な問い合わせを減らします。

• データ構造と関連を設計したいとき
• 関連データ取得のSQLを減らしたいとき
• 更新処理や変更履歴を見直したいとき

複数の視点でまとめた重要な意思決定の草案に、Codexによる外部批評を一度追加します。結論の弱点や見落とし、反対意見の扱いを確認するスキルです。

• 判断が難しい重要な草案の検討
• 草案にない失敗の可能性の確認
• 強い反対意見の見落としの確認

Webサイトの通信をHARファイルに記録し、JSON取得に使われるAPIを読み解いてHTTPクライアントを作るスキル。検索などの処理をブラウザなしで再実行できます。

• Webサイト用のCLIを作りたいとき
• ブラウザなしで検索を繰り返したいとき
• 検索候補やフィードの通信を調べたいとき

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," "lifecycle emails," "trigger-based emails," "email funnel," "email workflow," "what emails should I send," "welcome series," or "email cadence." Use this for any multi-email automated flow. Emails avoid AI tells like 'it's not X, it's Y' reveals, 'no X, no Y, no Z' lists, and fake 'Re:' subject lines. For cold outreach and outbound sequences, see cold-email. For in-app onboarding, see onboarding.

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。

Queries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and descriptive mutation frequencies. Use for variant surveillance, Pango lineage validation, dominant submitted lineages, Nextclade assignment provenance, SARS-CoV-2, influenza/H5N1 clades, RSV, mpox, measles, dengue, or LAPIS queries. Distinguishes sequence prevalence from infection prevalence, clades from genotypes, missing calls from reference matches, and sampling changes from biological growth advantage.

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 querying or extending GitNexus's PDG control/data-dependence surface (the `pdg_query` MCP tool, CDG/REACHING_DEF edges), or reasoning about "what controls X" / "where does Y flow" / guard clauses. Examples: "what guards this statement?", "trace this variable within the function", "why is the pdg_query result empty?", "add a CDG query".

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。

Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use for SQL queries, resource management, data ingestion, or AI applications on BigQuery.

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。

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.

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。

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.

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。