「pe」の検索結果

Use this skill whenever the user wants to use AI agents to work with Penpot design files via the Penpot MCP Server. Triggers include: using Penpot through an AI agent, design files, design systems, design tokens, Penpot MCP, design-to-code, generating UI from design, auditing a design system, creating components/variants, renaming layers, exporting assets from Penpot, adding flows, interactions, animations, overlays, or prototyping in Penpot, or prompting an AI agent to read/modify a Penpot file. Also triggers when the user wants to set up Penpot MCP, connect any MCP-compatible AI agent or IDE to Penpot, or produce production-ready HTML/CSS/React from a Penpot design. Use this skill for Penpot-agent workflows — design, code, audit, prototyping, or setup.

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。

Product marketing and go-to-market strategy for B2B SaaS launches and positioning. Use this skill when planning a product launch, developing positioning and messaging, analyzing competitive landscape, building customer advocacy programs, designing a customer referral program (who may accept the reward, how the introduction is made), designing a win/loss interview program, working out why we lose deals, designing GTM strategy, creating category positioning, planning analyst briefings, or deciding which country to expand into and how far to localize. Also use it for an early-stage startup where the founder is still doing the selling — running founder-led sales, setting up a design-partner program, judging whether you have product-market fit, deciding what not to do yet, deciding when to hire the first AE or first marketer, and moving upmarket to larger buyers. Also use it when your company has just acquired another (or is about to), to plan the marketing integration: what you may and may not do between signing and close, the first letter to the acquired customers, whether to keep, endorse, fold in or retire the acquired brand, merging the two marketing databases without mailing people who opted out, when to start cross-selling, and announcing a product sunset. Also use it to design a demand-generation campaign and the channel plan it runs on: one campaign with one job, the offer for buyers who are and are not in market, what each channel is for, the kill and scale rules set before launch, the follow-up sales agrees to, the yearly calendar of always-on programs and tentpole campaigns, and which channels to keep, test or stop. Also use it for brand marketing and demand creation — how much to spend on brand versus performance, what to measure when a brand campaign produces no conversion event, and how to answer "we cannot attribute it". Also triggers on: founder-led sales, founder-led GTM, design partners, design partner agreement, first customers, first 10 customers, do we have product-market fit, PMF, Sean Ellis test, very disappointed survey, pre-seed, seed stage, when to hire our first AE, first sales hire, first marketing hire, moving upmarket, going upmarket, enterprise readiness, first enterprise deal, what do enterprise buyers need before they sign, positioning, product launch, beta program, early access program, design partners, private preview, public preview, general availability, GA launch, when can we call it GA, can sales sell a beta feature, selling the roadmap, launch tier, competitive intelligence, messaging, customer advocacy, win/loss analysis, win/loss interviews, why we lose deals, closed-lost analysis, loss reason, close-reason field, competitive displacement, displace an incumbent, rip and replace, competitive takeout, switch from a competitor, win deals from a competitor, incumbent contract, renewal window, auto-renewal notice period, switching costs, EU Data Act, cloud switching rights, why do we lose to no decision, GTM, category design, ideal customer profile, ICP, what is our real ICP, who actually buys from us, refresh our ICP from closed-won deals, ICP refresh before planning, analyst briefing, G2 review, international expansion, market entry, expand into Europe, which country should we launch in next, localization, translate our site, in-country go-to-market, regional GTM, is cold email legal in Germany, brand marketing, brand awareness, brand vs performance, brand versus demand gen, demand creation, demand capture, 95-5 rule, out of market buyers, category entry points, distinctive brand assets, mental availability, brand tracking, brand health, brand lift, share of search, how do we measure brand, justify brand spend, brand budget. Also triggers on public-sector marketing: sell to government, government marketing, public sector go-to-market, federal marketing, state and local government, SLED, FedRAMP, FedRAMP marketing claims, can we say FedRAMP ready, GovRAMP, StateRAMP, VPAT, accessibility confor

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。

Calls m6A peaks from MeRIP-seq / m6A-seq paired IP-vs-input data using exomePeak2 (transcript-aware, GC-bias-corrected Poisson GLM), MeTPeak (HMM over sliding windows), MACS3/MACS2 with --nomodel --broad --keep-dup all (genome-wide broad alternative), and DRACH motif enrichment via HOMER or ggseqlogo as a sanity check (NOT a filter). Covers BED12 vs narrowPeak output, exonic vs intronic peak handling, multi-tool reconciliation (intersection vs union), the m6A-vs-m6Am ambiguity at 5'UTR peaks that antibody methods cannot resolve, and orthogonal validation (miCLIP/GLORI/m6A-SAC-seq/m6Anet). Use when calling peaks from paired IP/input genome BAMs, choosing exomePeak2 (transcript-aware default) vs MACS3 (broad genomic) vs MeTPeak (HMM-smoothed low-coverage), confirming DRACH enrichment as a sanity check on the peak set, reconciling differing peak sets across tools, validating MeRIP peaks against single-base methods, interpreting 5' peaks where m6Am contamination is possible, or recommending a consensus strategy.

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。

Stripe CLI の `stripe fixtures` コマンドで実行可能な fixture JSON を、対話的に整理しながら生成・検証する。test_clock を使った時間進行、サブスクのライフサイクル、失敗カードでの payment_intent 失敗、Connect 配下の Destination charge、bulk 件数のテスト顧客作成など、複数ステップの API リクエスト連鎖を扱う。「Stripe の fixture を書いて」「fixtures.json を作って」「このシナリオを fixture 化」「テストデータを大量に作りたい」「サブスクの月次失敗をテストしたい」「stripe trigger と fixture どっち使う」のような依頼で起動する。"fixture" という単語が無くても、複数ステップの Stripe テストデータ準備、 test clock を使った時間進行、 bulk なテスト顧客作成、 失敗パターンの再現といった意図が見えたら起動する。単発 API 呼び出しが目的なら起動せずに `stripe trigger` か API 1コールを案内する。

WooCommerce Stripe Gateway skill for the fragile My Account payment-methods and add-payment-method flows. Use when editing or replacing Woo account templates, payment-methods.php, form-add-payment-method.php, Stripe card/token UI, saved cards, SetupIntent, Payment Element/UPE, billing details, WC payment tokens, customer account payment-method endpoints, Subscriptions change-payment-method compatibility, or code contains add_payment_method, add-payment-method, form#add_payment_method, payment_method_stripe, wc-stripe-upe-element, wc-stripe-setup-intent, stripe_source, wc_stripe_create_setup_intent, wc_stripe_upe_params, wc-stripe-payment-method, or woocommerce-gateway-stripe.

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。

Interactive Domain-Driven Design modeling sessions based on DDD Distilled (Vaughn Vernon) and Domain Modeling Made Functional (Scott Wlaschin). Guides users through strategic and tactical design via 13 phases: discover, storming, contexts, mapping, aggregates, events, validate, glossary, workflows, types, simulate, publish, sync. Phase 13 (sync) reconciles divergences found by --analyze between the domain model and the implementation — judging whether the model or the code is authoritative, then planning and implementing the fix and re-aligning the model. Phases 9-11 take the conceptual model from phases 1-8 and produce workflow pipeline designs, compilable type definitions (TypeScript, Kotlin, Scala, Rust, C#, F#), workflow verification via type-level tests, and automatic UI field enumeration from the domain model. Phase 12 (publish) renders all docs/domain artifacts into one self-contained, cross-linked HTML site (separate files joined by a shared nav). Each phase is an interactive dialogue where AI acts as facilitator and domain expert challenger. Use when: "DDD", "ドメイン設計", "ドメインモデリング", "Event Storming", "Bounded Context", "集約設計", "ユビキタス言語", "コンテキストマップ", "ワークフロー設計", "パイプライン設計", "ステップ分割", "中間型", "型駆動フロー", "型駆動設計", "Domain Modeling Made Functional", "Railway Oriented Programming", "入力画面項目", "フォーム項目洗い出し", "UI 項目抽出", "HTMLにまとめる", "ドキュメントサイト化", "成果物を1つのHTMLに", "publish", "モデルと実装の差異", "差異解消", "実装との乖離", "モデルとコードを一致", "差異の実装計画", "sync", "複数フェーズを逐次実行", "フェーズをまとめて実行", "/ddd run", "サブコマンド一覧", "/ddd list", "/ddd", "ドメイン分析したい", "モデリングしたい", or any domain design / type modeling activity.

Document and type a Sentry API endpoint. Write or fix @extend_schema decorators, specify response TypedDicts, type request parameters, correct type drift between the declared schema and the runtime response, and validate the generated spec. Use when asked to "document an endpoint", "add OpenAPI docs", "add/fix @extend_schema", "type an endpoint response", "fix the response type", "fix type drift", "reuse a response type", "split an overloaded endpoint", "specify the response schema", "add a TypedDict response", "migrate a legacy api-docs path", "fix a parameter type", or "make an endpoint public" / "promote an endpoint" (promotion is one section here).

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。

Rory Sutherland's 'psycho-logic' approach to marketing, product, and business problems — solve the human perception, not just the engineering or economic metric. Use when the obvious 'logical' fix is expensive, slow, or already done by every competitor; when the user asks 'how do we make people want X', 'the product/price/funnel is fine but nobody converts', 'how do we stand out', 'is there a cheaper way to fix this', or mentions behavioral economics, nudges, irrational behavior, perception, or 'it doesn't make sense but it works'. This is the ROUTER skill: it diagnoses the problem in human terms, then dispatches to reframing, costly-signaling, counterintuitive-tests, or experience-design. Inspired by Rory Sutherland's book *Alchemy*. 日本語の相談（「商品はいいのに売れない」「値下げしかない？」「競合と差別化できない」）にも使う。中文咨询（“产品很好却卖不动”“只能降价吗？”“无法差异化”）也适用。For a catalogue of individual biases, use marketing-psychology (separate plugin) instead.

OpenClawの画面をSolid 2で実装・移行・レビューするスキル。状態管理やLitとの共存、ダイアログなどの表示、テストと性能確認を扱います。

• Litの画面をSolid 2へ移行したいとき
• 状態管理と画面更新をレビューしたいとき
• プラグイン画面やダイアログの実装

OpenClawのテストやプラグイン検証の遅さ・メモリ使用量を計測し、読み込みや起動処理の原因を調査。テストの検証範囲を保ちながら改善し、前後の数値を比較します。

• 遅いテストや重い読み込みの原因調査
• プラグイン検証の時間とメモリ削減
• テスト中のメモリ増加を調べたいとき

OpenClawのQAシナリオを模擬環境や実サービスで実行し、失敗原因の修正、結果レポートの確認、複数モデルの応答スタイル比較まで支援するスキル。

• 模擬環境や実サービスでQAを実行
• 失敗シナリオの原因調査と再検証
• 複数モデルのキャラクター比較

Discordのテスト用ボットで接続情報や読み取り権限を確認し、メッセージ・ファイル・スレッド操作やOpenClawの応答を証拠付きで検証するスキル。

• ボットの識別情報と読み取り権限確認
• メッセージ・ファイル・スレッド検証
• OpenClawの返信・逐次送信・入力表示検証

OpenClawの課題やプルリクエストを、現在のソースとテスト結果に基づいて調査・レビューし、許可された範囲で修正からマージ完了の確認まで進めるスキル。

• OpenClawのPRをレビューしたいとき
• 報告された不具合のローカル修正
• 課題が既に解決済みか確認したいとき

OpenClawの記憶をまとめたWikiを、元資料に基づいて更新・点検します。手書きのメモを保ちながら、ページの重複や情報の矛盾、出典の不足を確認します。

• 元資料からWikiを更新したいとき
• 蓄積した知識を確認・引用したいとき
• 更新後の矛盾や出典不足の点検

OpenClawにモデル提供サービスを追加し、実際の応答まで確認するスキル。認証情報は環境変数やファイルへの参照で扱い、設定の検証と結果報告も進めます。

• OpenClawにモデルを追加したいとき
• 認証情報を参照形式で設定したいとき
• モデルの実際の応答を確認したいとき

音声ファイルをローカルで文字起こしし、テキストや翻訳字幕に出力するスキル。APIキー不要で、モデルの大きさを選び、処理速度と精度を調整できます。

• 録音音声を文字起こししたいとき
• 音声から翻訳字幕を作りたいとき
• 速度や精度に合わせたモデル選び

Perlのテスト作成・実行から、外部処理の置き換え、例外の確認、テスト範囲の測定まで支えるスキル。テスト先行の開発や既存テストの移行にも使えます。

• テスト先行でPerlを開発
• Test::Moreからのテスト移行
• APIやDB連携を独立して検証

Sync delta specs from an OpenSpec change to main specs. Use when the user wants to update main specs with changes from a delta spec, without archiving the change. Also use when the user says "openspec sync" or "opsx sync".

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。

Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory, coverage-bounded integrity checks, two-stage peer review, and auditable quality-assurance artifacts. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow, 연구부터 논문까지, 연구 주제 설정부터 논문 완성까지, 논문 전체 워크플로, flujo de trabajo académico, investigación a artículo, flujo completo de artículo, pipeline de investigación completa, publicación de investigación, flujo de trabajo completo del artículo.

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。

Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정, revisar artículo, revisión entre pares, revisión de manuscrito, informe de árbitro, revisa mi artículo, criticar artículo, simular revisión, revisión editorial, calibrar revisor.

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。

Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications. Use when implementing complex type logic, creating reusable type utilities, or ensuring compile-time type safety in TypeScript 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。

Competitive analysis two ways - the in-deal play against a named competitor, and win/loss patterns, competitor mentions, and battlecards across the book. Use when the user asks "competitive intel", "research competitors", "how do we compare to [competitor]", "what's new with [competitor]", "battlecard for [competitor]", "how do we beat [competitor]", "what's the play against [competitor] in [deal]", "where are we losing to [competitor]", "win/loss patterns", "competitive analysis", "refresh the battlecards", or on a weekly schedule.

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 building a Kubernetes Operator — custom controllers that reconcile CRD state. Triggers on "build an operator", "CRD design", "reconcile loop", "controller-runtime", "kubebuilder", "operator-sdk", "metacontroller", "KOPF", "operator capability levels", or "custom resource". Ships CRD validator, reconcile-loop linter, and OperatorHub capability auditor (all stdlib Python), 4 references on the operator pattern + CRD design + reconcile patterns + tooling landscape, and a /operator-audit slash command. NOT a generic k8s skill — specifically the Operator pattern.

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。

Export raw OpenTelemetry traces from an AI application to Confident AI's Observatory. TRIGGER when the user wants to send OpenTelemetry or OTLP traces/spans from an LLM app, agent, RAG pipeline, or chatbot to Confident AI; configure the Confident AI OTLP endpoint; set confident.span.* or confident.trace.* attributes; export AI-app traces without the deepeval Python package; wire an OTLPSpanExporter, OpenTelemetry Collector, or vendor-neutral OTel SDK to Confident AI; or pick the US vs EU OTLP endpoint. Language-agnostic: the mechanism is OTLP attribute keys plus an exporter endpoint. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill); for instrumenting with the DeepEval SDK's @observe decorator or framework integrations (use the `deepeval-tracing` skill); or for non-AI software such as web servers, CRUD backends, or infrastructure: the confident.* attributes describe AI components only.

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。