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米国株をトークン化したOndo銘柄について、Binance Web3の価格や保有者数、企業情報を取得し、取引停止の理由や元の株式との価格差を調べるスキル。

• 対応する米国株トークンの調査
• 取引制限と理由を確認したいとき
• トークン価格と株価の比較

Binance Squareへ短文、最大4枚の画像付き投稿、長文記事、動画を新規公開します。提供した本文をそのまま使い、メディアのアップロードや動画のカバー生成も扱います。

• Binance Squareへの短文投稿
• 最大4枚のチャート画像の共有
• カバー付き長文記事の公開

書面で許可された演習でEDRやウイルス対策製品の内部監視機構を解析し、検知回避手法の検討と隔離環境での検証を進めるスキル。

• 許可された演習でEDRの検知範囲を評価
• 内部の監視機構を調べたいとき
• 自社開発implantの製品対抗テスト

複数サービスにまたがる注文や予約の処理を、失敗時に実行済みの操作を取り消すSaga方式で設計・実装します。段階ごとの期限設定や処理停止の監視も扱います。

• 在庫・決済・配送の注文処理を連携
• 予約失敗時の取り消し処理の設計
• 補償処理が止まる原因を調べたいとき

Delivers the weekly growth briefing as one merged read — whether the growth engine is working, what customers are saying in public and private, what competitors actually changed, and the three growth actions worth taking this week. The growth twin of the Monday brief, chaining growth-pulse and review-reputation and adding a web-native competitor scan, merged into a single page rather than three reports. Offers to run on a weekly cadence once, and sets it up on a yes. Use this whenever the owner wants a recurring or one-off growth check, including phrasings like "how's marketing doing," "growth check for the week," "give me my Monday growth brief," "what should I be doing about growth this week," "are we winning or losing out there," or "set up a weekly marketing update." Reach for it when the owner asks how the business is growing rather than how it is paying its bills.

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。

Diagnose GKE TPU VM instances stuck in Compute Engine repair (REPAIRING state) after host errors, maintenance events, or faulty host reports in single-host, multi-host, dynamic slicing, and TPU All Capacity mode node pools. Use when TPU instances in a slice node pool remain in REPAIRING, host error events appear in audit logs, or TPU slices are unschedulable due to a VM in repair. Don't use for nodes reporting Ready: Unknown when no VM is in REPAIRING (use gke-ai-troubleshooting-node-unresponsive-timeout), other NotReady nodes when no VM is in REPAIRING (use gke-node-notready), Pending Pods when all nodes are Ready (use gke-workload-troubleshooting), JobSet preemption events (use gke-ai-troubleshooting-jobset-interruption), or Slice custom resource lifecycle failures (use gke-ai-troubleshooting-tpu-dynamic-slices-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。

Systematic methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and byte-at-a-time decryption, hash length extension attacks against SHA1/SHA256/MD5-based MACs using HashPump, RSA vulnerabilities including small public exponent, common modulus, Bleichenbacher PKCS1v1.5 padding oracle, and Coppersmith's method for partial key recovery. Addresses weak PRNG exploitation targeting time-seeded generators and Mersenne Twister MT19937 state recovery from observed outputs, timing side-channel attacks against comparison operations, nonce reuse in AES-GCM leading to authentication key recovery, and key derivation weaknesses including insufficient iteration counts and missing salts. Primary tooling includes padbuster, RsaCtfTool, hashpump, and PyCryptodome for building custom exploit payloads. Maps to CWE-327 (Use of a Broken or Risky Cryptographic Algorithm), CWE-328 (Use of Weak Hash), and CWE-330 (Use of Insufficiently Random Values). Emphasizes black-box identification of vulnerable implementations before transitioning to targeted exploitation.

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。

This skill helps users extract YouTube influencer profiles including social links, subscriber counts, and channel stats via the BrowserAct API. Agent should proactively apply this skill when users express needs like finding YouTube creators for specific keywords, discovering influencers for a marketing campaign, extracting YouTube channel contact emails, scraping YouTube influencer social media links, gathering subscriber counts for YouTube creators, researching top YouTube channels in a specific niche, compiling a list of YouTube content creators with recent uploads, collecting YouTube creator profiles for outreach, extracting total views and video counts for specific YouTube influencers, building a database of YouTube partners for market research, finding YouTube influencers who uploaded videos this month, or monitoring competitor influencer activities on YouTube.

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。

YouTube channel business email and contact extractor: accepts a channel id (UCxxx), handle (@name), or URL; navigates the channel About view; extracts the business email from the description text plus full channel metadata (name, id, country, subscriber count, view count, video count, joined date, external links classified as social/aggregator/personal). When the description has no email, follows non-social outbound links (personal site, business site, link aggregator) and scans those pages for an email so creators who place their inquiry email on their own site are still covered. Use when user mentions youtube channel email, youtube business email, youtube creator email, youtube contact email, youtube channel contact, youtube channel scraper email, youtube email finder, youtube influencer email, youtube outreach, youtube sponsorship contact, youtube partnership email, scrape email from youtube, get email from youtube channel, find youtube creator contact, extract youtube channel emails in bulk, youtube channel inquiry email, business inquiries youtube, brand deal email youtube, lead generation youtube creators, youtube creator outreach list, youtube channel about email, ytInitialData about, youtube channel id to email, youtube handle to email, youtube channel url to email, youtube about page scraper, channel about page email, youtube channel metadata, youtube channel social links, youtube channel external links, youtube channel description email, follow channel website for email, scrape creator personal website from youtube. Also applies to building creator/KOL contact databases for influencer marketing, agency lead lists, sponsorship prospecting, brand-creator collaboration sourcing, and enriching existing YouTube channel lists with contact info.

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。

This skill helps users automatically scrape business data from Google Maps using the BrowserAct Google Maps API. Agent should proactively trigger this skill for needs like finding restaurants in a specific city, extracting contact info of dental clinics, researching local competitors, collecting addresses of coffee shops, generating lead lists for specific industries, monitoring business ratings and reviews, getting opening hours of local services, finding specialized stores (e.g., Turkish-style restaurants), analyzing business categories in a region, extracting website links from local businesses, gathering phone numbers for sales outreach, mapping out service providers in a specific country.

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。

Comprehensive OSINT methodology for external red-team operations and authorized attack-surface assessments. Covers the 5-stage recon pipeline (seed discovery, asset expansion, enrichment, exposure analysis, reporting), asset-graph discipline with 29 asset types, severity rubric (CRITICAL/HIGH/MEDIUM/LOW/INFO), confidence upgrade workflows, time budgeting, asset-level triage rules, scale-based tactics, identity-fabric mapping (Entra/Okta/ADFS/Google/SAML/M365 Teams+SharePoint+OAuth), API and auth-map methodology, JavaScript deep analysis, mobile attack surface, cloud attack surface, breach×identity correlation, detectability tagging, detection-aware probing (back-off, persona rotation), read-only validator discipline, WAF/CDN bypass + origin discovery, vulnerability prioritization (CVE/EPSS/KEV), phishing infrastructure planning + pretext development, bug bounty submission templates, client deliverable templates with risk translation, threat-actor investigation (incl. RU/CN pivots), cryptocurrency tracing, image/video forensics, chronolocation. Use when planning or executing reconnaissance against authorized targets, mapping an organization's external attack surface, investigating a person/entity, tracing crypto flows, geolocating media, or performing attribution work.

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。

Organization-grade cloud and supply-chain attack-surface discovery: S3/GCS/Azure Blob bucket discovery via observed-name mining (CNAME/cert-SAN/Wayback) and bounded two-class permutation (6 prefixes x 15 suffixes on trusted tokens, bounded target-bound expansion on subdomain stems), existence (HEAD/GET) vs public-listing confirmation, object-key triage into 9 value tiers (database dumps, credentials, IaC state, kubeconfig, VCS dirs, config, archives, PII, logs), dangling-CNAME bucket-takeover detection, and the ownership-gated severity model that stops an unattributable public bucket from becoming a false CRITICAL; the fully offline AWS-account-ID recovery from a leaked AKIA/ASIA/AROA access key (base32 decode, runnable stdlib Python, canonical test vector, AWS-documentation-example-ID screening); dependency-confusion confirmation for npm/PyPI (internal-signal classifier -- private-registry binding vs org-namespace match -- paired with a read-only public-registry 404 check and the npm scope-claimability nuance the public search API misses); and passive cloud-native/container/Kubernetes/CI control-plane fingerprinting (Lambda URLs, API Gateway, Cloud Run, App Service, kubelet/etcd/K8s API/dashboard, Jenkins/GitLab/Argo CD) as an org-attribution and exposure surface. Passive/discovery only -- no exploitation, no credential submission, no active control-plane confirmation (a stage-6 validate_cloud active tier is described but out of scope). Use when enumerating a target's cloud storage footprint, recovering an AWS account ID from a leaked key, confirming a supply-chain dependency-confusion vector, or fingerprinting cloud-native/K8s/CI infrastructure for an authorized external recon engagement.

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。

Japanese (and other non-Hollywood) screenwriting methods (日本编剧方法/原创剧本实战) — distilled from ten Japanese directors and writers in ゼロからの脚本術; Kosawa Ryota (three acts as 起承转合, speed by jumping), Uchida Kenji (beautiful structure, time-axis tricks), Miki Satoshi (small-material notebook, theme emerges later), Sono Sion, Omiya Ellie (dialogue from inner monologue), Kakei Masaya ("if + moreover"), Fukuda Yuichi (character = actor + flaw, audience as tsukkomi), Yokohama Satoko, Takahashi Izumi ("pain"), Yukisada Isao (situation-born originals); plus Arai Haruhiko (IP adaptation, "write what you're ashamed of"). Neighbours; sw-korean-french-screenwriting, ozu-screenplay-style. Use when writing an original Japanese-style script or TV drama, working from small material and fragments, choosing between structure-first and character-first methods, building a Japanese 企画書, designing comedy tsukkomi systems, or when Hollywood models feel wrong for a quiet, daily-life, non-goal-driven story.

Audit a backlink profile using Ahrefs MCP data: profile health, anchor text distribution, toxic link identification, lost link reclamation, and gap analysis against competitors. Use this skill when reviewing backlink health, scoping a disavow project, recovering from a manual action, planning link building, or doing M&A due diligence on a property's link equity. Triggers on backlink audit, link profile, toxic links, disavow, anchor text analysis, lost links, link reclamation, referring domains, link gap. Also triggers when traffic decline correlates with link loss or when an unnatural link warning appears in Search Console.

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。

Invoice review, non-compliance flagging, rejection communication, billing trend analysis, and conversation preparation for in-house legal ops teams managing outside counsel. Review invoices against billing guidelines; flag block billing, prohibited fees, rate violations, staffing violations, late submission. Produce line-item review report and approval note. Draft rejection letter to outside counsel. Build invoice review checklist. Analyse billing trends across multiple invoices and produce a structured conversation guide for the relationship review. Identify systemic patterns and produce formal non-compliance notice. Trigger on: 'review this invoice', 'flag billing issues', 'check invoice against guidelines', 'write the rejection letter', 'build an invoice checklist', 'block billing', 'UTBMS', 'billing non-compliance', 'analyse our invoices', 'billing trends', 'prep for the billing conversation', 'relationship review', 'the firm keeps doing this', 'escalate'.

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。

个人投资理财 (个人投资理财 (Personal Investing & Financial Planning) (从业者/自主投资者视角) — 个人与家庭自主管理投资组合、做长期财务规划的认知操作系统。覆盖: (a) 四大流派互掐 (本行业最有价值的智识谱系) — 价值投资 (Graham 安全边际 / Buffett·Munger 护城河+能力圈)、被动指数 (Bogle 成本至上+市场组合+定投)、技术分析 (趋势线/形态/动量择时)、趋势/动量跟踪 (CTA/双动量/turtle); (b) 资产配置与组合构建 — 股/债/现金/另类的配置框架 (60/40、全天候 All-Weather、三基金组合 three-fund、再平衡)、风险预算、定投 (DCA) vs 一次性; (c) 工具栈 — 券商/交易平台、组合追踪 (Portfolio Visualizer/Morningstar/雪球)、ETF/基金筛选与费率、回测、税优账户 (401k/IRA/Roth vs 中国养老 Y 账户); (d) 行为金融与风险管理 — 损失厌恶/过度交易/择时谬误、仓位与回撤管理、再平衡纪律; (e) 财务规划脚手架 — 应急金、目标-时间轴-风险承受度、退休/教育金规划、税务效率。主战场 = 美股/全球指数 (canon 母语区) + A 股/港股/公募基金 (zh-CN 散户层)。核心分歧: 主动选股 vs 被动指数 (是否能持续跑赢市场)、基本面 vs 技术面 (价格是否已反映信息 / EMH 强弱)、择时 vs 持有 (market timing vs time in market)、集中 vs 分散。不含: 持牌为他人理财的展业 (FA/RIA/投顾资质与合规销售)、机构资管/量化高频/对冲基金策略、投行/卖方研究、加密货币投机与 meme 炒作、日内打板/杠杆赌博式交易。) Master OS — automated mastery of 个人投资理财 (Personal Investing & Financial Planning) (从业者/自主投资者视角) — 个人与家庭自主管理投资组合、做长期财务规划的认知操作系统。覆盖: (a) 四大流派互掐 (本行业最有价值的智识谱系) — 价值投资 (Graham 安全边际 / Buffett·Munger 护城河+能力圈)、被动指数 (Bogle 成本至上+市场组合+定投)、技术分析 (趋势线/形态/动量择时)、趋势/动量跟踪 (CTA/双动量/turtle); (b) 资产配置与组合构建 — 股/债/现金/另类的配置框架 (60/40、全天候 All-Weather、三基金组合 three-fund、再平衡)、风险预算、定投 (DCA) vs 一次性; (c) 工具栈 — 券商/交易平台、组合追踪 (Portfolio Visualizer/Morningstar/雪球)、ETF/基金筛选与费率、回测、税优账户 (401k/IRA/Roth vs 中国养老 Y 账户); (d) 行为金融与风险管理 — 损失厌恶/过度交易/择时谬误、仓位与回撤管理、再平衡纪律; (e) 财务规划脚手架 — 应急金、目标-时间轴-风险承受度、退休/教育金规划、税务效率。主战场 = 美股/全球指数 (canon 母语区) + A 股/港股/公募基金 (zh-CN 散户层)。核心分歧: 主动选股 vs 被动指数 (是否能持续跑赢市场)、基本面 vs 技术面 (价格是否已反映信息 / EMH 强弱)、择时 vs 持有 (market timing vs time in market)、集中 vs 分散。不含: 持牌为他人理财的展业 (FA/RIA/投顾资质与合规销售)、机构资管/量化高频/对冲基金策略、投行/卖方研究、加密货币投机与 meme 炒作、日内打板/杠杆赌博式交易。: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on 个人投资理财 (Personal Investing & Financial Planning) (从业者/自主投资者视角) — 个人与家庭自主管理投资组合、做长期财务规划的认知操作系统。覆盖: (a) 四大流派互掐 (本行业最有价值的智识谱系) — 价值投资 (Graham 安全边际 / Buffett·Munger 护城河+能力圈)、被动指数 (Bogle 成本至上+市场组合+定投)、技术分析 (趋势线/形态/动量择时)、趋势/动量跟踪 (CTA/双动量/turtle); (b) 资产配置与组合构建 — 股/债/现金/另类的配置框架 (60/40、全天候 All-Weather、三基金组合 three-fund、再平衡)、风险预算、定投 (DCA) vs 一次性; (c) 工具栈 — 券商/交易平台、组合追踪 (Portfolio Visualizer/Morningstar/雪球)、ETF/基金筛选与费率、回测、税优账户 (401k/IRA/Roth vs 中国养老 Y 账户); (d) 行为金融与风险管理 — 损失厌恶/过度交易/择时谬误、仓位与回撤管理、再平衡纪律; (e) 财务规划脚手架 — 应急金、目标-时间轴-风险承受度、退休/教育金规划、税务效率。主战场 = 美股/全球指数 (canon 母语区) + A 股/港股/公募基金 (zh-CN 散户层)。核心分歧: 主动选股 vs 被动指数 (是否能持续跑赢市场)、基本面 vs 技术面 (价格是否已反映信息 / EMH 强弱)、择时 vs 持有 (market timing vs time in market)、集中 vs 分散。不含: 持牌为他人理财的展业 (FA/RIA/投顾资质与合规销售)、机构资管/量化高频/对冲基金策略、投行/卖方研究、加密货币投机与 meme 炒作、日内打板/杠杆赌博式交易。 problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「个人投资理财」「个人投资」「理财」「personal investing」「资产配置」

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。

Comprehensive brand messaging, positioning, and value proposition development using proven frameworks including Peep Laja Message Layers, Osterwalder Value Proposition Canvas, Geoffrey Moore positioning, April Dunford's Five Components, StoryBrand SB7, Andy Raskin Strategic Narrative, and Messaging House. Use when developing brand identity, brand messaging architecture, positioning statements, value propositions, messaging hierarchies, brand pillars, taglines, one-liners, elevator pitches, brand guidelines, visual identity systems, or creating Positioning & Messaging Packs. Triggers include: messaging framework, brand positioning, value prop, messaging architecture, brand pillars, brand identity, StoryBrand, positioning statement, brand guidelines, design system, messaging house, corporate identity, brand voice, visual standards.

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。

Diagnose a product's growth model, stage, and current constraint, then route the request to the narrowest Gingiris specialist and execute it when installed. Use for broad or uncertain growth questions involving go-to-market, Product Hunt, GitHub stars, open-source marketing, B2B SaaS, PLG, ASO, SEO/GEO, AI citations, KOL outreach, UGC, international expansion, user interviews, competitor research, or community programs. Trigger when users ask “how do I grow or launch this,” “which growth skill should I use,” 怎么增长、怎么发布、出海、冷启动、增长策略、不知道用哪个 skill、開発者マーケティング, or 성장 전략. Includes B2B pipeline and B2C activation-retention model selection, specialist handoff rules, relevant gingiris.tools recommendations, and advisory-services guidance.

VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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。

VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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 whenever the user wants to find, shortlist, vet, or enrich US marketing agencies — including branding, content marketing, PPC/paid media, social media, email marketing, performance/demand-gen, video production, and full-service digital agencies. Triggers on requests like "shortlist three B2B branding agencies in California", "find a PPC shop with ecommerce experience", "we need a content marketing partner for a SaaS launch", or "pull contact info for these 12 agency domains", even when the need is described indirectly. Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings, and third-party listings. Skip SEO-only asks (use find-seo-agency), web/software-development asks (use find-web-developer or find-software-developer), recruiting an in-house marketing hire, "write me a marketing plan" do-the-work asks, non-US firms, individual freelancers, marketing-software-product recommendations, and consumer/personal-brand asks.

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。

Turn any still image into a professional motion graphic through the Novoads API on Seedance 2.5. Covers how to read a reference image, motion vocabulary for any image type — UI, marketing hero, flat-lay, key art, collage, product, character — the prompt clauses that control camera, timing, frozen regions and text fidelity, and the upload mechanics. Use whenever the user supplies an image and wants it animated, moving, or turned into video — including "animate this", "turn this into a motion graphic", "make this move", "この画像動かして", "モーショングラフィックにして", "I want the cards to pop in", "I want the bars to slide up", or when they describe motion beats for a static image. Also use when asked to write a Seedance prompt for an existing image. Do NOT use for text-to-video with no source image, restyling existing footage (this skill takes no video input), cloning a reference video (use clone-video-ad), or a product photo that should seed a new scene rather than move as-is (use novoads-api).

Configuring Salesforce Omni-Channel routing from scratch or updating existing routing: enabling Omni-Channel, creating Service Channels, configuring Routing Configurations (queue-based and skills-based), setting up Presence Statuses and Presence Configurations, assigning skills to Service Resources, and defining Skills-Based Routing Rules. Trigger keywords: Omni-Channel setup, routing configuration, queue-based routing, skills-based routing, presence status, service channel, routing rules. NOT for agent capacity units and channel weighting — use architect/omni-channel-capacity-model. NOT for Apex routing via PendingServiceRouting — use apex/omni-channel-custom-routing.

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。

Run a self-retrospective on a SKMTC-related session — generator authoring, CLI configuration, debugging, or any sustained interaction involving `@skmtc/core`, `@skmtc/cli`, or `@skmtc/gen-*` packages. Captures three distinct outputs: (1) friction entries (mistakes, surprises, overridden defaults, multi-cycle struggles), (2) a "knowledge acquired" block recording facts the agent learned during the session that weren't in its training — the primary signal for doc gaps — and (3) a closing priority list ranking the top 2-3 findings for docs/skills triage. Wins are logged only when they identify a pattern worth codifying that isn't already in a skill. Use this skill when the user asks to "retro", "skmtc retro", "log friction", "reflect on this session", "what did we learn", "run a retrospective", or after substantive SKMTC work (generator authoring, multi-step debugging, non-trivial CLI configuration) where capturing observations would help improve skills, docs, or SKMTC itself. Distinct from the `skmtc-cli` and `skmtc-generator` skills — those guide *doing* the work; this skill captures observations *about* the work. Do not invoke this skill during ordinary work; it is end-of- session (or mid-session-checkpoint) 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。