Build and verify Multi-step workflow for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design verification.
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。
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Build and verify Multi-step workflow for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design verification.
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。
Build and verify Multi-step workflow for Commerce and checkout with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design verification.
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。
Designs and documents structured incident response playbooks that define step-by-step procedures for specific incident types aligned with NIST SP 800-61r3 and SANS PICERL frameworks. Covers playbook structure, decision trees, escalation criteria, RACI matrices, and integration with SOAR platforms. Activates for requests involving IR playbook creation, incident response procedure documentation, response runbook development, or SOAR playbook design.
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。
Focused Signals scout for PostHog projects with web traffic. Watches the acquisition and site-health layer the web analytics product reports on: per-channel session volume diverging from the site's own rhythm (an acquisition source silently collapsing or surging), attribution breakage (paid/campaign traffic reclassifying into Direct or Unknown when tagging breaks), landing pages that break (bounce-rate steps, 404 spikes, entry-path cliffs), and page-performance regressions (web vitals p75 steps). Emits findings only when they clear the confidence bar; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet.
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。
Execute a user flow step-by-step in Cursor's built-in browser while documenting each action, then emit a Playwright test that replays the same flow using stable selectors derived from the accessibility tree.
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。
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework
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。
Orchestrates an end-to-end long-read structural-variant pipeline - basecalling to minimap2 alignment (platform-matched preset) to Sniffles2/cuteSV/pbsv calling to optional assembly-based calling (dipcall/PAV) to two-step .snf cohort merging to Truvari benchmarking - chaining ONT and PacBio HiFi runs while handing the SV signal mechanism off to the component skills. Use when running a long-read SV workflow from reads to a benchmarked callset, choosing the minimap2 preset and SV caller by platform and goal, deciding when long reads are worth it for the insertions and repeat-mediated SVs short reads physically miss, building a joint-genotyped cohort with the two-step .snf design, or parameterizing a Truvari benchmark against GIAB HG002 Tier 1 plus CMRG. Not for the SV signal mechanism itself (see variant-calling/structural-variant-calling) or short-read SV.
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。
Orchestrates an end-to-end CRISPR editing experiment design from target gene to delivery-ready, validatable constructs. Sequences guide design, off-target assessment, edit-modality selection (knockout, base editing, prime editing, HDR knock-in), and template/donor design, with a QC checkpoint at each handoff. Use when designing a complete CRISPR experiment for knockout, point correction, or tagging and the order of operations, the modality decision, and the cross-cutting traps are needed rather than a single step. Defers each step's mechanics to the genome-engineering 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。
Orchestrates the end-to-end germline short-variant pipeline from FASTQ to a filtered, normalized, benchmarked VCF, chaining QC/trim, BWA-MEM2 alignment, duplicate marking, optional BQSR, calling (bcftools/GATK HaplotypeCaller/DeepVariant/DRAGEN), normalization, site+genotype filtering, annotation, and hap.py/vcfeval benchmarking. Use when deciding the pipeline-wide reference-genome commitment (GRCh38 analysis set vs T2T, ALT/decoy handling), sequencing the steps in the defensible order (normalize BEFORE annotate, filter site- then genotype-level), choosing the calling engine and single-sample vs cohort joint-calling, picking a filtering strategy by cohort size, or benchmarking stratified within GIAB confident regions. Hands off mechanism to the variant-calling and read-alignment component skills; not a re-teach of any single step.
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。
Start a new OpenSpec change using the experimental artifact workflow. Use when the user wants to create a new feature, fix, or modification with a structured step-by-step approach.
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。
Reads and changes a running CARLA server's WorldSettings via apply_settings — synchronous vs asynchronous mode, fixed_delta_seconds (fps), physics substepping, and no_rendering_mode — and keeps the Traffic Manager's sync state matched automatically. Use when the user asks to "enable/disable sync mode", "set synchronous mode", "run at a fixed fps/step", "turn off rendering", "make the sim deterministic", or "restore async mode", and as the prerequisite for keeping settings across a map load.
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 add or configure Maven plugins in your pom.xml — including quality tools (enforcer, surefire, failsafe, jacoco, pitest, spotbugs, pmd), security scanning (OWASP), code formatting (Spotless), version management, container image build (Jib), build information tracking, and benchmarking (JMH) — through a consultative, modular step-by-step approach that only adds what you actually need. This should trigger for requests such as Add Maven plugins in pom.xml; Improve Maven plugins in pom.xml. Part of cursor-rules-java project
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。
Upstash サーバーレスデータプラットフォームリファレンス。 @upstash/redis — REST API、pipelining、transactions、JSON、Search、グローバルレプリケーション。 @upstash/ratelimit — Fixed Window、Sliding Window、Token Bucket、limit、blockUntilReady。 QStash — publishJSON、schedules、queues、DLQ、URL Groups、callbacks、flow-control。 @upstash/vector — upsert、query、ANN、hybrid index、sparse index、embedding models、namespace。 Rust 製ローカル vector DB エンジン fandhe-db とは別(こちらはマネージド SaaS の JS SDK)。 @upstash/workflow — durable execution、serve、context.run/sleep/call/invoke、waitForEvent、parallel steps、agents。 Upstash Search — search、upsert、fetch、range、filtering、reranking、algorithm、@upstash/search。 Upstash Box — サンドボックス、agent、filesystem、git、browser(CDP/AI actions/recordings)、network policy、snapshots、schedules。
GitHub 公式ドキュメント リファレンス。 REST API、GraphQL API、GitHub Actions (workflow, jobs, steps, expressions)、 Webhooks、GitHub Apps、gh CLI、認証 (PAT / GITHUB_TOKEN / OAuth Apps)、 pull requests, issues, projects (Projects v2), releases, Codespaces, Packages, Copilot API, security (code scanning / secret scanning / Dependabot), activity (events / notifications)。
Driver.js (JavaScript プロダクトツアー・要素ハイライト・オンボーディングライブラリ) リファレンス。 driver(), highlight, tour steps, popover, overlay, theming、 configuration、ホットキー、コールバック、アニメーション、ステップナビゲーション。
CadQuery (Python 製 3D CAD スクリプティングライブラリ) リファレンス。 Workplane API (lineTo / extrude / revolve / sweep / loft / fillet / chamfer / shell)、 Sketch API、Assemblies (Constraint solver, 9 種制約)、Free Function API、 Selectors、Class hierarchy (Shape / Vertex / Edge / Wire / Face / Shell / Solid)、 Import / Export (STEP / DXF / STL / glTF / SVG)、Visualization (VTK, Jupyter)、CQGI。
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。
変更内容からミューテーション/E2Eの推奨度を判定し、強く推奨・範囲が小さい・副作用なしのものは確認なしで実施し、それ以外は最後の報告で確認する。quality-check Step 5から参照実行されるほか、開発中の任意タイミングで単体実行できる。
UI実装後の検証時に使用。agent-browser CLIでブラウザ上の動作を手動検証する。「UIを確認」「画面テスト」と言われたら使用(プロジェクトの E2E スイート実行は quality-check Step 5(推奨度・範囲で自動実施または確認)/ server-startup が担当)。
Help a user talk through whether to change jobs, stay, or change something in their current work, starting from uncertainty, distress, a vague sense of stagnation, an offer in hand, a counter-offer from the current employer, or pressure from family or colleagues. Clarify what matters, separate deadlines that order the next steps from the decision itself, compare conditional options, and agree on a small next step and a time to revisit it. Use when someone asks whether they should quit, wonders whether leaving is just running away, has second thoughts after receiving an offer or being asked to stay, feels stuck because others say it would be a waste, wants to leave soon after joining, or wants advice before deciding to start a job search; do not make the final stay-or-leave decision, evaluate offer terms, plan the resignation, or predict hiring outcomes.
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。
Facilitate Kimball-style dimensional (data warehouse / BI) modeling sessions through conversation, producing DimML (Dimensional Modeling Language, YAML) as the primary artifact plus a bus-matrix + star-schema HTML. Use whenever the user wants to design fact tables, dimensions, a star schema, or a bus matrix — declaring grain, choosing SCD types, identifying conformed dimensions and measures (additivity) — by grilling one step at a time. Also invoke for refining an existing DimML, or when the user says "ディメンショナル・モデリング", "ディメンションモデリング", "スタースキーマ", "バスマトリクス", "ファクト表を設計したい", "グレインを決めたい", "DimML を育てたい", "Kimball で整理したい".
Take a guided tour of Open SaaS — walks you through step-by-step through the project structure, features, and customization checklist.
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。
Refresh the Key Metrics table in a thesis with current data from Financial Modeling Prep, with a scoped web-search fallback (Step 4b) when FMP has no data or resolved the wrong company. Use when user says "numbers", "refresh metrics", "update key metrics", or "refresh [TICKER]" with no other action implied. Surgical edit only — does NOT create research notes or propagate via $sync. Also flags (never auto-edits) stale price/valuation framing in the thesis Summary — see Step 10b.
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。
Sequential multi-step setup flow (assistant/wizard) with AdwNavigationView, Back/Forward navigation, progress indication. Use when building onboarding or setup flows with ordered steps.
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。