2.2万 件 ・ 関連度順
概要と使いどころ
Onboard a NEW human peer ([коллега], [коллега], [коллега], future family/colleagues/clients) into building THEIR OWN Second Brain — the HUMAN layer that runs on… Trigger on “/brain-onboard“, “/brain-onboard <имя>“, “онбординг второго мозга“, “заведи <имени> второй мозг“, “onboard <name> into their second brain“, “личный волт для <имя>“, or when a peer's Claude receives the personal-vault-per-user rule
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 optimize their App Store listing for seasonal events, holidays, or trending moments — including keyword opportunities, metadata updates, screenshot theming, and timing strategy. Use when the user mentions "seasonal", "holiday", "Christmas", "New Year", "Valentine's Day", "summer", "back to school", "seasonal keywords", "trending now", "limited time", or wants to capitalize on a calendar event. For general keyword research, see keyword-research. For full metadata rewrites, see metadata-optimization.
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 improve their app's onboarding experience, increase activation rate, reduce Day 1 drop-off, or optimize the first-run flow. Use when the user mentions "onboarding", "first-run", "activation", "tutorial", "day 1 retention", "new user flow", "permission prompts", "sign-up conversion", "onboarding funnel", or "users dropping off early". For overall retention strategy, see retention-optimization. For paywall placement, see monetization-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。
When the user wants to analyze competitors' App Store strategy, find keyword gaps, or understand competitive positioning. Also use when the user mentions "competitor analysis", "competitive research", "keyword gap", "what are my competitors doing", or "compare my app to". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
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 optimize App Store metadata — title, subtitle, keyword field, or description. Also use when the user mentions "optimize my title", "ASO metadata", "keyword field", "character limits", "app description", or "write my subtitle". For keyword discovery, see keyword-research. For full ASO audits, see aso-audit.
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, plan, or optimize App Store In-App Events — the event cards that appear on the Today tab, search results, and your product page. Use when the user mentions "in-app event", "App Store event", "event card", "Today tab", "live event", "challenge", "game event", "seasonal event card", or wants visibility beyond organic search. For general ASO, see aso-audit. For seasonal keyword strategy, see seasonal-aso.
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。
Access security tokens and smart cards using CryptoTokenKit. Use when building token driver extensions with TKTokenDriver and TKToken, communicating with smart cards via TKSmartCard, implementing certificate-based authentication, managing token sessions, or integrating hardware security tokens with the system keychain.
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 this skill when creating or reviewing Next.js Route Handlers (app/api), adding rate limiting, input validation, or auth to API endpoints. Trigger words: API ルート, Route Handler, app/api, エンドポイント, レート制限, 入力検証, CORS, ヘッダー, 認証付き API, hardening.
Control Herdr, a terminal multiplexer for coding agents. Use only when the user explicitly mentions Herdr or asks to use Herdr to inspect or control panes, tabs, workspaces, commands, or another agent. Do not use merely because a task could benefit from a background terminal, delegation, or parallel work. Requires HERDR_ENV=1.
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。
Specialized skill for building production-ready Discord bots. Covers Discord.js (JavaScript) and Pycord (Python), gateway intents, slash commands, interactive components, rate limiting, and sharding.
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。
bu skill covers Dağıt:ing AWS Security Hub as a centralized cloud security posture management platform that aggregates Bul:ings from GuardDuty, Denetle:or, Macie, and third-party tools. It details enabling security standards like CIS AWS Foundations Benchmark, configuring automated remediation, and building executive dashboards for compliance tracking across multi-account AWS organizations.
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。
ScalarDBレビューエージェント - 設計レビュー（--mode=design）とコードレビュー（--mode=code）を実行。/review-scalardb --mode=design で呼び出し。
ScalarDBサイジング見積もりエージェント - Enterprise/OSSエディション別のインフラ構成・Pod数・コストを対話形式で見積もり。/scalardb-sizing-estimator で呼び出し。
ScalarDBアプリケーション設計パターンエージェント - ドメインタイプ判別に基づく設計パターン選択・データモデリング・DB選定・スキーマ設計。/design-scalardb-app-patterns [対象パス] で呼び出し。
ScalarDB設計エージェント - エディション設定に基づくマイクロサービスのデータアーキテクチャ設計。分散トランザクション、スキーマ設計、ポリグロット永続化を策定。/design-scalardb [対象パス] で呼び出し。
Plan, verify, and track demo/marketing video production in Busabase — idea to hook/pain-point/storyboard, codebase claim verification, recording progress, post-production handoff, and HyperFrame (Remotion) linkage. Use when the user invokes $kelly-demo-video-factory or /kelly-demo-video-factory, wants to plan a product demo video, write a storyboard, verify a video script's product claims against the codebase, track which shots are recorded, or hand a finished storyboard off to editing/Remotion.
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。
Generates and maintains competitive battlecards from win/loss data, competitor intel, G2 reviews, and sales feedback. Use when building battlecards for a specific competitor, updating existing battlecards with new intel, preparing BDRs or AEs for competitive deals, analyzing win/loss patterns against a competitor, or responding to a competitor's product launch or pricing change. Also use when asked to "build a battlecard," "update competitive intel," "how do we beat [competitor]," "what do we say when a prospect mentions [competitor]," or "analyze our win/loss against [competitor]." Designed for B2B SaaS teams selling against known competitors in deals with multi-persona buying committees.
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。
Full SEO audit: Google Search Console data + URL Inspection API + PageSpeed Insights API + technical crawl + keyword research + metadata audit + schema markup audit + search intent analysis + Core Web Vitals monitoring. Feeds real GSC data and PageSpeed metrics into AI to surface quick wins, diagnose traffic drops, find content gaps, identify metadata mismatches, detect schema gaps, monitor page performance, and produce an actionable 30-day plan. Use this skill whenever the user asks about SEO, search rankings, organic traffic, Google Search Console, keyword performance, traffic drops, content gaps, search visibility, technical SEO, meta tags, schema markup, structured data, URL indexing, keyword research, indexing issues, page speed, performance, Core Web Vitals, LCP, INP, CLS, or Lighthouse scores. Also trigger on: "why is my traffic down", "what keywords am I ranking for", "improve my rankings", "check my search console", "SEO audit", "analyze my SEO", "technical SEO", "meta tags", "indexing issues", "crawl errors", "content strategy", "keyword cannibalization", "search intent", "schema markup", "structured data", "URL inspection", "page speed", "performance score", "core web vitals", "lighthouse", or any organic search question. If in doubt, trigger. This skill handles everything from quick GSC checks to deep technical audits with performance monitoring.
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。
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
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。
Inspects a recorded CARLA .log without replaying it — show_recorder_file_info for the header/actors/frames, collision queries between actor categories, and blocked-actor queries for vehicles that got stuck. Use when the user asks to "what's in this recording", "show recorder info", "which vehicles collided", "find collisions in the log", or "which actors were blocked/stuck".
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。
Runs a route through ScenarioRunner's RouteScenario mode (--route / --route-id) with an autonomous agent driving the ego — the same mechanism the CARLA Leaderboard uses, and the only way to reach the ~34 route-only scenario classes (Accident, ParkedObstacle, HazardAtSideLane, InvadingTurn, HardBreakRoute, YieldToEmergencyVehicle, junction and actor-flow scenarios). Inspects route files, lists route ids and their scenarios, and runs one or all of them. Use when the user asks to "run a route", "drive a route with my agent", "run leaderboard scenarios without the leaderboard", or names a route-only scenario type.
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。
Runs the CARLA Leaderboard evaluator over a set of routes with your agent — routes/routes-subset/repetitions/track selection, checkpoint and live-results endpoints, resume after a crash, recording, and the debug levels — for leaderboard 1.0, 2.0 or 2.1. Preflights the whole stack (version pairing, maps, ports, agent class, sensor budget) before spending hours, and hands the world back in async mode. Use when the user asks to "run the leaderboard", "evaluate my agent", "run routes_training", "resume an evaluation", or "reproduce my submission locally".
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。
Writes an autonomous agent for the CARLA Leaderboard — an AutonomousAgent subclass with setup/sensors/run_step/destroy, a sensor suite inside the track's budget, and the right constructor signature for the leaderboard version (1.0 and 2.x differ). Generates a working skeleton, validates the sensor configuration against the real per-track limits offline, and covers the ROS1/ROS2 agent base classes. Use when the user asks to "write a leaderboard agent", "make my agent work with the leaderboard", "add sensors to my agent", "port my agent to 2.1", or hits SensorConfigurationInvalid.
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 a CARLA Leaderboard results.json — per-route driving score, route completion, infraction penalty and the infraction lists — explains how the score was computed for that leaderboard version, and rescores an existing result under the other version's rules (2.0 multiplicative vs 2.1 additive) without re-running anything. Also diffs two runs and merges sharded result files. Use when the user asks "what did I score", "why is my score low", "did my agent pass", "why don't my scores match the leaderboard", or hands over a results.json.
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。