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概要と使いどころ
Monitor paid-ad account pacing, delivery, performance, creative fatigue, tracking, policy, and data quality across supported platforms. Use for daily or weekly checks, anomaly review, budget pacing, post-launch verification, or campaign 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 full-stack Web3 build with mandatory packaging and delivery phase
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。
Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow
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。
Trigger: RDD, receipt-driven development, review authority, receipt/lineage, correction/recovery, delivery gate/kill switch, bounded review defects. Guide 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。
Phishing campaign execution methodology for authorized red team engagements. Covers end-to-end campaign lifecycle: infrastructure provisioning (GoPhish, SMTP relay configuration, domain acquisition and aging, SPF/DKIM/DMARC alignment), payload delivery vectors (Office macro weaponization, HTA droppers, ISO/IMG container abuse, LNK shortcut hijacking, OneNote embedded payloads, HTML smuggling), email authentication bypass techniques (SPF softfail exploitation, DKIM replay attacks, display name spoofing, homoglyph and cousin domain registration), credential harvesting with MFA bypass (EvilGinx2 transparent proxy, Modlishka session relay, pixel-perfect HTML cloning), spear phishing pretext development informed by OSINT, email security gateway evasion, QR code phishing (quishing), and callback phishing for initial access. Integrates with GoPhish for campaign management, EvilGinx2 for adversary-in-the-middle credential interception, King Phisher for template design, and the Social Engineering Toolkit for payload generation. Maps to MITRE ATT&CK T1566 (Phishing) and sub-techniques T1566.001 (Spearphishing Attachment), T1566.002 (Spearphishing Link), T1566.003 (Spearphishing via Service). Assumes you have written authorization and a defined scope before any campaign execution.
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。
Social engineering attack techniques beyond email phishing for authorized red team and physical penetration testing engagements. Covers pretexting methodology (persona creation, authority and urgency psychological triggers, rapport building), vishing (voice phishing via caller ID spoofing, IVR system exploitation, VoIP infrastructure setup with Twilio/Asterisk), smishing (SMS-based phishing, carrier gateway abuse, short code impersonation), physical social engineering (tailgating and piggybacking, RFID badge cloning with Proxmark3, lock picking and bypass, dumpster diving for sensitive documents), USB drop attacks (Rubber Ducky keystroke injection, Bash Bunny multi-vector payloads, O.MG cable covert implants, BadUSB firmware attacks), watering hole attack planning and execution, and OSINT-driven targeting (LinkedIn harvesting, organizational chart reconstruction, employee pattern analysis). Integrates with the Social Engineering Toolkit for attack automation, Proxmark3 for RFID/NFC cloning, USB Rubber Ducky and Bash Bunny for physical payload delivery, and BeEF for browser exploitation. Maps to MITRE ATT&CK T1598 (Phishing for Information), T1566 (Phishing), T1091 (Replication Through Removable Media), and T1189 (Drive-by Compromise). All techniques require explicit written authorization and defined rules of 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。
Activate when the user explicitly names the narrator skill or requests production-ready narration in either case: (1) numbered takes fitted to fixed video windows, or (2) one continuous long-form story read in a locked voice that must be measured and retried for timbre or internal pauses. Collect missing text, voice_id, or voice_type after activation; their absence is not a reason to skip this workflow. Own pacing, speech-duration gates, retries, and ready audio delivery; never time-stretch. Do not use for ordinary TTS, "read this aloud", an unconstrained voiceover, voice browsing, music, SFX, singing, dubbing existing speech, or voice cloning.
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 project policy calls for a human decision or update, a human delivery is pending or failed, or a reply must resume the right 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。
Create UI mockups at three fidelity levels — ASCII wireframes for quick iteration, standalone HTML mockups for delivery with requirements, and live prototypes for interaction testing.
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。
Frame an epic as a testable hypothesis with target user, expected outcome, and validation method. Use when defining a major initiative before roadmap, discovery, or delivery planning.
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 choose between PLG and sales-led, design a sales motion, optimize time-to-first-value, or build a value-before-purchase experience. Also use when the user mentions 'PLG,' 'product-led growth,' 'sales-led,' 'sales motion,' 'free trial,' 'freemium,' 'self-serve,' 'demo-first,' 'time-to-first-value,' 'TTFV,' or 'agent-led sales.' This skill covers sales motion selection, value delivery design, and go-to-market motion architecture. Do NOT use for technical implementation, code review, or software architecture.
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。
Keep a Linear issue aligned with implementation evidence, acceptance criteria, code review, and deployment state while avoiding premature completion claims.
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。
Produce concise Linear project updates from current milestones, completed and blocked issues, delivery risks, and next actions.
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。
Package, deploy, and verify a playable Three.js or web game. Use for release builds, asset delivery, private/public deployment, production smoke tests, browser proof, release notes, rollback readiness, and cleanup of temporary QA resources.
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 sharp, physically coherent high-resolution materials for 3D rendering with appropriate PBR maps, texel density, UV direction, mipmaps, anisotropic filtering, and progressive asset delivery. Use for detailed wood, stone, fabric, foliage, and architectural close-ups without excessive download or GPU memory costs.
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。
Plan, create, integrate, or audit a hybrid asset pipeline for a Three.js or web game. Use when choosing among imported meshes, procedural 3D geometry, AI-generated reference art, 2D UI media, sprites, VFX, and performance-ready runtime asset delivery.
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。
List OKX Agentic Wallet exclusive trading competitions, register users for contests, track participation and leaderboard rankings, and claim won rewards. Use when users want to list available trading competitions or trading cups, view competition rules / prize pool / total prizes, register or sign up or enroll or join a contest, check the leaderboard (who is winning) or their own rank (am I in the prize zone, what is my place), ask did I win or query participation / claim status, claim won rewards or prizes from completed competitions, see which wallet account they registered with, or submit Telegram / WeChat / Email / Twitter contact for prize delivery to top-tier winners.
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。
Qualify the exact final diff for a LoopX-managed goal. Use when goal policy enables change_quality_qualification, before a non-trivial delivery or merge, and when producing or repairing an exact-scope quality receipt. The workflow is language-neutral, permits at most one policy-authorized safe-fix pass, and never grants merge or repository authority.
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 LoopX must manage a multi-PR or multi-MR delivery program across one or more repositories: inventory current change requests, reconcile new/merged/closed or retargeted work, preserve requirement and dependency priorities, maintain a roadmap document, or monitor material lifecycle/check/review changes over time. Use provider-neutral snapshots and one grouped continuous monitor; do not use for deep per-PR code review, approval, commenting, or merge actions.
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。
Produces revision sheets with quick navigation by act, a master concept-to-URL table, Q&A cheat-sheet with 6-10 anticipated questions, glossary, and external resources list. Use when preparing for a talk with Q&A, creating shareable reference material for attendees, or building a safety-net glossary for live delivery.
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。
Amazon search and category listing scraper: extract product listings from any Amazon search results page, keyword search URL, or category browse page and return per-item cards (asin, title, url, image, price, listPrice, stars, reviewCount, badges, isAmazonChoice, isBestSeller, isSponsored, delivery, boughtInPast, positionIndex) plus pagination state (currentPage, hasNextPage, nextPageUrl, totalResultsApprox). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.in, amazon.fr, amazon.ca, amazon.com.au, amazon.it, amazon.es, amazon.com.mx, amazon.com.br, amazon.nl, amazon.se, amazon.sg, amazon.ae, amazon.sa, amazon.pl, amazon.tr, amazon.eg). Use when user mentions Amazon, amazon.com, Amazon SERP, Amazon search results, Amazon keyword search, Amazon category page, Amazon subcategory URL, scrape Amazon listings, extract Amazon search, Amazon product cards, Amazon browse page, Amazon /s URL, Amazon /s?k= URL, Amazon /b/ category URL, Amazon /gp/browse category, Amazon bbn category filter, Amazon rh filter, Amazon search pagination, Amazon 7 pages limit, Amazon subcategory scraper, Amazon keyword scraper, Amazon SERP scraper, Amazon by URL, Amazon by category, Amazon by keyword. Also applies to price monitoring across a keyword or category, competitive listing tracking on Amazon, brand keyword ranking on Amazon, category catalog audits, best-of category discovery from a search, paginated bulk extraction of Amazon search hits, and building ASIN lists from a search.
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。
Walmart product detail page extractor: given a walmart.com product URL (walmart.com/ip/...), extract full product data including itemId, title, brand, model, UPC, price, wasPrice, currency, availability, category path, seller info, all images, shortDescription, longDescription, product highlights, full specifications as key-value map, color/size variants with item IDs, fulfillment options (shipping/pickup/delivery with dates), return policy, and review summary with rating breakdown. Use when user mentions walmart product detail, walmart item page, walmart product page, scrape walmart product, extract walmart item, walmart product data, walmart item details, walmart product info, walmart product scraper, walmart item scraper, walmart product URL, walmart ip URL, walmart.com/ip, walmart specifications, walmart product specs, walmart product images, walmart variants, walmart color options, walmart size options, walmart seller info, walmart return policy, walmart fulfillment options, walmart shipping info, walmart availability, walmart product enrichment. Also applies to enriching a list of walmart product URLs with full details, monitoring walmart product price and availability changes, building a walmart product catalog, competitive product research on walmart, and batch collection of full product data from walmart item IDs.
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 is designed to help users automatically extract product data from Amazon search results. The Agent should proactively apply this skill when users request searching for products related to keywords, finding best-selling items from specific brands, monitoring product prices and availability on Amazon, extracting product listings for market research, collecting product ratings and review counts for competitive analysis, finding specific products with a maximum count, searching Amazon in different languages for localized results, tracking monthly sales estimates for brand products, gathering product URLs and titles for a product catalog, scanning Amazon for Best Seller tags in a specific category, monitoring shipping and delivery information for brand items, building a structured dataset of Amazon search results.
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 Nexent requirements and bugfixes through SPEC acceptance, traditional UT and applicable D1-D5 test design, product/test implementation, local verification, and delivery evidence. Use for features, fixes, refactors and post-development test backfill across APIs, UI, model and Agent behavior.
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。