「ai」の検索結果

Write B2B cold emails and follow-up sequences that get replies. Use when the user wants to write cold outreach emails, prospecting emails, cold email campaigns, sales development emails, or SDR emails. Also use when the user mentions "cold outreach," "prospecting email," "outbound email," "email to leads," "reach out to prospects," "sales email," "follow-up email sequence," "nobody's replying to my emails," or "how do I write a cold email." Covers subject lines, opening lines, body copy, CTAs, personalization, and multi-touch follow-up sequences. For warm/lifecycle email sequences, see emails. For sales collateral beyond emails, see sales-enablement.

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 B2B cold emails and follow-up sequences that get replies. Use when the user wants to write cold outreach emails, prospecting emails, cold email campaigns, sales development emails, or SDR emails. Also use when the user mentions "cold outreach," "prospecting email," "outbound email," "email to leads," "reach out to prospects," "sales email," "follow-up email sequence," "nobody's replying to my emails," or "how do I write a cold email." Covers subject lines, opening lines, body copy, CTAs, personalization, and multi-touch follow-up sequences. For warm/lifecycle email sequences, see emails. For sales collateral beyond emails, see sales-enablement.

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 the psychologically significant moment, not the logically significant metric — Rory Sutherland on experience. Use when the outcome is fine but the journey feels bad: complaints about waiting, anxiety, uncertainty, or 'it's technically fast/cheap/correct but people still hate it'; when the user asks 'how do we reduce complaints', 'how do we make waiting/onboarding/checkout feel better', 'people are anxious during X', or is about to spend big to shave a number (wait time, load time, steps) when the real pain is how the moment feels. Covers uncertainty reduction, idle vs occupied waiting, and the peak-end rule. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic. 日本語の相談（「待ち時間のクレームが多い」「手続きの途中で離脱される」「お客様を不安にさせている」）にも使う。中文咨询（“等待时间投诉多”“办理中途流失”“让客户感到不安”）也适用。

Write B2B cold emails and follow-up sequences that get replies. Use when the user wants to write cold outreach emails, prospecting emails, cold email campaigns, sales development emails, or SDR emails. Also use when the user mentions "cold outreach," "prospecting email," "outbound email," "email to leads," "reach out to prospects," "sales email," "follow-up email sequence," "nobody's replying to my emails," or "how do I write a cold email." Covers subject lines, opening lines, body copy, CTAs, personalization, and multi-touch follow-up sequences. For warm/lifecycle email sequences, see email-sequence. For sales collateral beyond emails, see sales-enablement.

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。

コーディングエージェントからgbrainを呼び出せるよう、CLI導入、PGLiteまたはSupabaseの初期化、MCP登録、接続先ごとの信頼方針の設定を進めるスキル。

• 初めてのマシンでgbrainを導入
• ローカルのPGLiteで初期化
• Supabaseを使う構成の設定

Bonsaiの操作をAIエージェントに任せるために、使えるツールと最新の入力形式を調べ、接続確認から実行、一括処理までの手順を案内するスキル。

• Bonsaiの利用可能な操作を調べたいとき
• 接続を確認して作業を実行したいとき
• Bonsaiの操作をまとめて処理したいとき

利用可能なツールと入力形式を調べ、Astica AIの操作を自動化するスキル。Rube MCP経由で接続状態を確認し、検索で見つけたツールを実行します。

• Astica AIの利用可能な操作を調べたいとき
• 作業前に接続状態を確認したいとき
• Astica AIの一連の操作を自動化したいとき

プロジェクトの内容や対象者に合うドメイン名を考え、.comや.aiなど複数の末尾で取得可否を確認し、候補の理由や取得済みの場合の代案も提案するスキル。

• 新製品のドメインを決めたいとき
• 取得済みの名前の代案を探したいとき
• 個人サイトの命名

AIチームの成果物を受け入れ条件と照合し、確認できた事実とエージェントの主張、不確実な点や未完了の作業を分けて、完了判断の根拠を整理するスキル。

• AIチームの実行終了前に証拠を確認
• 成果物が受け入れ条件を満たすか確認
• 確認済みの結果と主張を区別

Extracts Airbnb accommodation search results from a destination query via SSR-embedded data, returning listing ID, URL, name, coordinates, rating, price, photos, and badge info for each result, plus pagination cursors for multi-page retrieval. Use when user mentions Airbnb search results, Airbnb listings, vacation rental search, short-term rental listings, scrape Airbnb, get Airbnb data, find rentals on Airbnb, Airbnb destination search, Airbnb property list, Airbnb stays search, Airbnb accommodation results, pull Airbnb listings, collect Airbnb search data, Airbnb scraper, Airbnb search page extraction, Airbnb search by destination.

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。

Expert blueprint for responsive UI layouts using Container nodes (HBoxContainer, VBoxContainer, GridContainer, MarginContainer, ScrollContainer, HFlowContainer, SubViewportContainer). Covers size flags, anchors, split containers, virtual_list pooling, stretch_shrink previews, and dynamic layouts. Use when building adaptive interfaces OR implementing responsive menus. Keywords: Container, HBoxContainer, VBoxContainer, GridContainer, HFlowContainer, SubViewportContainer, virtual_list, stretch_shrink, size_flags, EXPAND_FILL, anchors, responsive.

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。

Expert blueprint for responsive UI layouts using Container nodes (HBoxContainer, VBoxContainer, GridContainer, MarginContainer, ScrollContainer, HFlowContainer, SubViewportContainer). Covers size flags, anchors, split containers, virtual_list pooling, stretch_shrink previews, and dynamic layouts. Use when building adaptive interfaces OR implementing responsive menus. Keywords: Container, HBoxContainer, VBoxContainer, GridContainer, HFlowContainer, SubViewportContainer, virtual_list, stretch_shrink, size_flags, EXPAND_FILL, anchors, responsive.

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 Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_prep_search, ai_query, ai_forecast) to add AI capabilities directly to SQL and PySpark pipelines without managing model endpoints. Also covers document parsing and building custom RAG pipelines (parse → prep_search → index → 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。

JeecgBoot AI 编排流程（AIFlow）全生命周期管理——通过自然语言描述需求，自动创建、编辑、查询、删除、调试、发布 AI 编排流程。 只要用户意图涉及「AI编排」「AIFlow」就必须使用本技能，包括但不限于： 创建 AI 编排流程（"做一个AI流程"、"创建aiflow"、"新建编排"、"做一个知识库问答流程"、"创建一个大模型对话流程"）， 修改已有流程（"给流程加个节点"、"改一下LLM的提示词"、"修改流程"）， 查询流程（"查看流程列表"、"有哪些AI流程"）， 删除流程（"删除流程"、"移除XX流程"）， 调试运行流程（"调试流程"、"运行流程"、"测试流程"）， 发布管理（"发布流程"、"取消发布"）， 复制流程（"复制流程"、"克隆流程"）。 关键词触发：aiflow、ai-flow、AI编排、AI流程、编排流程、大模型流程、知识库流程、LLM流程。 注意：本技能仅处理 AI 编排流程（AIFlow），不处理 BPMN 工作流（使用 jeecg-bpmn）、 不处理简流（使用 jeecg-lowcode-miniflow）。

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。

Email marketing operations and automation for B2B SaaS. Use this skill for newsletter strategy, email automation sequences, lifecycle campaigns, nurture workflows, onboarding sequences, deliverability optimization, email copywriting, lead scoring, marketing automation platform setup, and cold-email sending infrastructure — secondary sending domains, SPF/DKIM/DMARC, and domain warmup. Also triggers on: email, newsletter, drip campaign, lifecycle, nurture, onboarding sequence, deliverability, email automation, lead scoring, marketing automation, our emails are going to spam, SPF, DKIM, DMARC, sender reputation, sending domain, cold email domains, domain warmup, mailbox setup, blacklist, bounce rate.

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。

macOS上のOpenClawをmainの最新版へ更新し、Gatewayとアプリの動作を確認します。CIの失敗修正や、公開を伴わないリリース検証も扱います。

• macOSのOpenClawを更新したいとき
• 更新後のGatewayとアプリの動作確認
• 現在のmainに対するCIの失敗修正

予約済みのItô GPU環境で機械学習の訓練が利用可能かを確認するスキル。現状は訓練を実行せず、未提供の機能と将来の引き渡し条件を整理します。

• GPU予約後に訓練可否を確認したいとき
• 追加学習の引き渡し要件の確認
• 予約・予算・確認手続きの整理

大量のベクトルから似たデータを探す検索を実装するスキル。FAISSの索引選びや保存、GPU利用を案内し、検索速度・精度・メモリ使用量の調整を支援します。

• 大量ベクトルの類似検索を実装したいとき
• 速度・精度・メモリに合う索引の選択
• GPUでの一括検索

ponytailの公開ベンチマークに基づき、コード量・出力トークン・費用・時間の削減結果を棒グラフで確認できます。現在の作業の実測値とは区別します。

• コード量や費用の削減結果の確認
• 実行時間と出力トークンの比較
• 削減結果と品質指標の確認

人とAIが実装役・案内役を分担し、役割を切り替えながら開発を進めるスキル。テスト生成やコードレビュー、デバッグ、学習向けの説明にも対応します。

• AIのレビューを受けながら実装したいとき
• 方針を伝えてAIに実装を任せたいとき
• テストを先に書いて機能開発したいとき

Browseaiの操作をAIエージェントに任せるためのスキル。Rube MCP経由で利用可能なツールと接続状態を確認し、最新の入力仕様に沿って処理を実行します。

• Browseaiの対応操作を調べたいとき
• 処理前に接続状態を確認したいとき
• 一連の操作をまとめて実行したいとき

Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engineering AI/ML skills.

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。

The way to answer "how are my production AI agents doing?" and to run the team's agent-observability deployment — reach for it even on casual phrasing that names no tool. Trigger when the user wants to: • inspect agent telemetry — did agents error/fail/go flaky; sessions, events, latency, token usage, slowest models; eval/quality scores and whether quality dropped; • operate the deployment — ack/assign/resolve/mute/dismiss issues (alerts, reports, and audit findings) with notes; run and triage audits; see who has access and change roles (e.g. read-only); create or scope API keys (e.g. a push-only CI key); change settings; run saved or ad-hoc ClickHouse queries. Served by the `fp` CLI against FailproofAI Cloud. NOT for writing or designing an evaluator service / scoring logic (that's `agenteye-evaluator`), adding SDK/instrumentation to your app (that's `failproofai-sdk`, imported as `failproofai_sdk`), debugging the collector/daemon, or unrelated dev work (why a build/CI run failed, rotating non-FailproofAI Cloud secrets).

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。

Delegate a coding task to Aider (`aider`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Aider - phrasings like "have Aider do X", "delegate this to aider", "run it through Aider", or "use Aider to implement/fix/refactor" - or wants to run a queue of coding tasks through Aider while staying the reviewer. This includes asking Aider to drive a local or self-hosted OpenAI-compatible endpoint ("have Aider use my local model", "run Aider against llama.cpp / Ollama / vLLM / LM Studio"), which Aider reaches via `--api-base`. DO NOT USE for local-model or coding requests that do not name Aider, for tasks small enough to do inline, or when the user wants the code written directly without delegating.

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。