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概要と使いどころ
Evaluates factor crowding with positioning analysis, valuation spread monitoring, and unwind risk assessment. Use when analyzing factor crowding, assessing unwind risk, or monitoring factor valuation extremes.
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 one milestone is too large for a single specification or plan and must ship as several ordered stages across sessions.
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。
Java and Spring Boot expert including REST APIs, JPA, and microservices
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。
Jira project management and issue tracking integration
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。
Linear project management - issues, projects, cycles, and roadmaps. Use for Linear-related tasks like managing issues, tracking sprints, and organizing 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。
Hunt Server-Side Template Injection (SSTI) in Jinja2, Twig, Freemarker, Velocity, Smarty, ERB, Handlebars, Mustache, and Spring (SpEL). Use when input is reflected in a way that suggests template rendering — error pages, email templates, PDF generators, dynamic content systems.
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。
Extract data from subcontractor bid PDFs and produce a comparison spreadsheet. Feeds into /bid-evaluator. Triggers: 'tabulate bids', 'bid comparison', 'compare bids', 'buyout analysis', 'bid tab'.
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。
Phase 1 of 5 — Socratic interview capturing WHAT and WHY; outputs a sprint-sized REQ doc for plan-architecture. Use only when the user asks to run Phase 1, plan requirements, or start the requirements interview — never trigger automatically from a feature description.
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。
Recreate grainient.supply's 16 dark-mode visual effects as single-file HTML pages: WebGL shader gradients, vignette overlays, 9-layer box shadows, smooth scroll, spring animations, hover-zoom, ticker marquees, glassmorphism, 3D card flips, bento grids, gradient CTAs. Dark-mode-first with lime green (#C2F13C) accent. Triggers on grainient effects, dark-mode landing page, cinematic depth, glow effects, SaaS showcase, visual effects page.
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 the user needs to finalize a deal, handle tough objections, or create a "Mutual Action Plan" to close a sale.
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 a single LinkedIn connection request message using Jay Abraham's Preeminence approach. Lead with their work, peer-to-peer tone, no pitch, under 300 characters.
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 a LinkedIn prospect connects, updates their status in the master tracker, creates their outreach message file, and generates a ready-to-post comment on their latest post.
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。
Query the FDA's public openFDA APIs for post-market drug data — FAERS adverse-event reports, Drugs@FDA approval and submission history, Structured Product Labels including boxed warnings, the National Drug Code directory, recall enforcement reports, and drug shortages. Use this skill to check what a regulator has already concluded about a molecule or its class, to date an approval and count its efficacy supplements, to read an approved indication or boxed warning, and to score a drug-event pair for disproportionate reporting with PRR, ROR, and chi-squared. Also trigger on openFDA, api.fda.gov, FAERS, Drugs@FDA, SPL, NDC, pharmacovigilance, boxed warning, adverse event report, drug recall, or safety signal.
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。
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
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。
Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski rule of five, Veber, Oprea, CNS, lead-like, rule of three), structural alert catalogs (PAINS a/b/c, NIBR screening-deck severity, Brenk, BMS, Glaxo, Dundee, ChEMBL common alerts), ZINC-15 percentile complexity metrics (Bertz, SAscore, QED, Whitlock, Barone), chemical-group detection, Lilly demerits, and the medchem query language (MATCHRULE, HASALERT, HASPROP, HASGROUP) for filtering a library at scale. Also trigger on medchem, `import medchem as mc`, RuleFilters, NIBRFilters, CommonAlertsFilters, NamedCatalogs, QueryFilter, PAINS filtering, or structural alerts.
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。
Generate a polished release video for a tbh-meter release in the Claude-Code motion style (recreated animated UI + real game sprites + synth soundtrack), to post with a launch. Primary input is a GitHub release LINK — the skill turns it into a video named after that release, covering ONLY the features that shipped in that release, version stamped on the intro. Use when asked to make/update a release video, showcase clip, feature trailer, or promo video for a meter release, or "make the video for <release link>".
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。
审视、设计、从零启动或改进 HarmonyOS、OpenHarmony 与 ArkUI 产品界面。用于检查 ArkTS UI、建立新项目设计基线、区分永恒原则与当前平台视觉语言、规划跨手机/平板/折叠屏/PC 的导航和布局、多输入控件状态、animateTo、transition、geometryTransition、springMotion、手势跟手与可打断动效、异步状态真实性、视觉分层参数、无障碍或动画性能，或建立鸿蒙 Motion Token 时。不要用于签名、构建、网络、存储、权限、数据库等纯工程问题，也不要用于通用视频剪辑或其他移动平台的设计规范评审。
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 and reviews Swift App Intents code that exposes app actions and data to Siri, Shortcuts, Spotlight, widgets, Control Center, and Apple Intelligence. Use when adding AppIntent, AppEntity, OpenIntent, AppShortcutsProvider, EntityQuery, Focus Filters, AssistantEntity/AssistantIntent schemas, on-screen awareness, LongRunningIntent/CancellableIntent, EntityCollection, SyncableEntity, AppIntentsTesting, or when wiring SwiftData/networked data into intents.
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 a truthful Japanese App Store metadata pack and app-name shortlist in twelve minutes without a multi-agent research round. Use for a live launch sprint, fallback ASO copy, app naming under a hard deadline, or when local product evidence is available but market research is intentionally deferred.
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。
Route a 50-minute live iOS launch sprint across the lightweight requirements, Claude Design handoff, SwiftUI implementation, landing page, ASO, Simulator screenshot, promo-video, and privacy-scan skills bundled in this plugin. Use as the main entry point when the whole talk workflow should be planned or executed.
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。
Restore legibility to an auto-generated graph diagram that has outgrown its canvas - rendering at single-digit percent scale with sub-pixel labels. Covers the levers that measurably reduce layout units (source-level label wrapping, invisible chain links so unconnected nodes stop spreading into one row, per-cluster splitting, layout direction picked by rendering both and measuring) and the rejected ones (raising the render font is a no-op because layout engines measure in text units; a topology heuristic for direction regressed 13 of 38 diagrams). Use when a generated Mermaid/Graphviz/DOT diagram is too small to read; not for hand-authoring a small diagram.
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。
Maintain the 8 essential garden hand tools through sharpening, handle care, rust prevention, and seasonal storage. Covers bypass secateurs, hori-hori, hand fork, trowel, pruning saw, sharpening stone, watering can, and soil rake. Use after each garden session for quick cleaning, monthly during the growing season for sharpening and oiling, at end of season for winter storage preparation, before spring for pre-season readiness checks, or whenever a tool feels dull, stiff, or shows rust.
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 and maintain a product or project backlog with prioritized items, acceptance criteria, and estimates. Covers user story writing, MoSCoW prioritization, backlog grooming, item splitting, and status tracking. Use when starting a new project and converting scope into actionable items, during ongoing grooming before sprint planning, re-prioritizing after stakeholder feedback or scope changes, or splitting oversized items into implementable pieces.
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。
Grade a trading card using PSA, BGS, or CGC standards. Covers observation-first assessment (adapted from meditate's unbiased observation), centering measurement, surface analysis, edge and corner evaluation, and final grade assignment with confidence interval. Supports Pokemon, MTG, Flesh and Blood, and Kayou cards. Use when evaluating a card before professional grading submission, pre-screening a collection for high-grade candidates, settling condition disputes between buyers and sellers, or estimating the grade-dependent value spread for a card.
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。