Clinical Research Bias Assessment - Case-Control Study (NOS) v2.3.0. Use when you need to assess the bias of a case-control study using the Newcastle-Ottawa Scale (NOS) criteria, or when evaluating the quality of a medical paper.
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。
aipoch/medical-research-skills☆ 1,9512026年9月17日 更新
Use when the user is designing, prototyping, or rewriting a desktop app that must run on multiple OSes (macOS + Windows, optionally Linux) AND feel indistinguishable from a native app to its users — fast launch, native windowing, native input handling, native materials. Trigger words include "cross-platform desktop", "Electron alternative", "Tauri vs native", "WebView wrapper", "near-native performance", "Raycast architecture", "WebKit/WebView2 quirks", "WKWebView", "system tray app", "global hotkey app", "launcher app". Do NOT trigger this skill for pure web apps, pure mobile apps, or for greenfield projects that have no native-feel requirement.
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。
yetone/native-feel-skill☆ 1,9312026年5月31日 更新
Recommend suitable prompts from 10,000+ Nano Banana Pro image generation prompts based on user needs. Optimized for Nano Banana Pro (Gemini), but prompts also work with Nano Banana 2, Seedream 5.0, GPT Image 1.5, Midjourney, DALL-E, Flux, Stable Diffusion, and any text-to-image AI model. Use this skill when users want to: - Generate images with AI (any model — Nano Banana Pro, Gemini, GPT Image, Seedream, etc.) - Find proven AI image generation prompts and prompt templates - Get prompt recommendations for specific use cases (portraits, products, social media, posters, etc.) - Create illustrations for articles, videos, podcasts, or marketing content - Browse a curated prompt library with sample images - Translate and understand prompt techniques Also available: "ai-image-prompts" skill — a model-agnostic version of this library for universal image generation.
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。
YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill☆ 1,8752026年10月14日 更新
Use this skill when the user wants to build a financial model — 3-statement model, DCF valuation, LBO, SaaS unit economics, sensitivity / scenario analysis, debt schedule, or fundraising projections — in Excel. Trigger on: 'financial model', '3-statement model', 'P&L + BS + CF', 'DCF', 'WACC', 'NPV', 'terminal value', 'LBO', 'debt schedule', 'cash sweep', 'MOIC', 'IRR / XIRR', 'sensitivity table', 'scenario analysis', 'ARR model', 'unit economics', 'CAC / LTV', 'cap table forecast'. Output is a single formula-driven .xlsx. This skill is a scene layer on top of officecli-xlsx — it inherits every xlsx v2 rule (4-color code, visual floor, number formats, cache-drift, Known Issues, Delivery Gate minimum cycle). DO NOT invoke for a simple budget tracker, CSV dump, or operational KPI sheet — route those to officecli-xlsx base.
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。
zhu1090093659/deepseek-pp☆ 1,8632026年8月14日 更新
Google Text-to-Speech (gTTS) for converting text to audio. Use when creating audiobooks, podcasts, or speech synthesis from text. Handles long text by chunking at sentence boundaries and concatenating audio segments with pydub.
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。
benchflow-ai/skillsbench☆ 1,8462026年10月13日 更新
Get current weather and forecasts (no API key required).
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。
HKUDS/OpenOPC☆ 1,8432026年9月11日 更新
This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or requests 3-5 year financial planning for a startup.
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。
rmyndharis/antigravity-skills☆ 1,7582026年10月1日 更新
Character creation, protagonist/antagonist design and dramatic conflict for scripts (人物/对手/冲突) — merged from Lajos Egri (three-dimensional character, orchestration, unity of opposites, pivotal character, rising vs static vs jumping conflict, transition), William Indick's Psychology for Screenwriters (Freud, Erikson, Jung archetypes, Campbell/Murdock hero journeys, Adler, Rollo May), Robert McKee (characterization vs true character, dimensions, gap, antagonism principle), Neill Hicks (character invocation, self-concept, cognitive dissonance, five conflict focuses, Maslow), Lisa Cron (desire vs misbelief), and Lu Jun (人物要活八要, 对手要强, 给对手一把刀, 最强的对手是自己, 不许请祥云). Use when building a protagonist, an antagonist or a cast, when a character feels flat or acts out of character, when conflict stalls or jumps, when a villain is too weak, when designing an arc or motive, or when diagnosing melodrama.
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。
jtydhr88/screenwriting-skills☆ 1,6592026年10月3日 更新
Episode and season structure for TV series (剧集单集与季的结构) — teasers and cold opens, broadcast four/five/six-act grids with page anchors, three tests for finding the invisible acts in streaming scripts, act-out and cliffhanger taxonomies, Oberg's four information tools, A/B/C/runner weaving and scene-count ratios, the Calvisi pilot beat sheet, five-part scene structure, and season shape (tentpoles, bottle and container episodes, two-parters, finales). Merged from Calvisi, Douglas, Oberg, Landau, Goldberg & Rabkin, Miller, Rabkin and Blum, plus act lengths measured from published West Wing, Succession, Sopranos, Downton and Fleabag scripts. Use when breaking an episode into acts, deciding how many acts a script needs, placing act outs and cliffhangers, designing a teaser, weaving A/B/C stories and runners, beating out a one-hour pilot, auditing an episode that has no shape, reverse-engineering a show's structure, or planning a season's episode order (分幕、出幕、悬念结局、季弧、瓶子集).
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。
jtydhr88/screenwriting-skills☆ 1,6592026年10月3日 更新
Use when forecasting, estimating, or sizing risk — anchor on base rates, give ranges, update prior→likelihood→posterior on evidence, and factor unmeasured quantities into order-of-magnitude bounds.
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。
tjboudreaux/cc-thinking-skills☆ 1,6352026年8月8日 更新
Under genuine uncertainty with no reliable forecast, inventory means, cap downside at affordable loss, act for commitments, and let goals emerge from controllable moves.
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。
tjboudreaux/cc-thinking-skills☆ 1,6352026年8月8日 更新
Govern Azure costs with budgets, alerts, tags, and policy restrictions. WHEN: "Azure budget health", "configured budget overrun", "list Azure budgets", "create Azure budget", "budget alerts", "budget coverage", "missing CostCenter tags", "allowed VM SKUs", "allowed Azure regions", "would this SKU be denied", "cost guardrails". DO NOT USE FOR: planning-target forecasts, bill investigations, pricing, rightsizing, or commitments.
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。
microsoft/azure-skills☆ 1,5662026年10月14日 更新
Optimize existing Azure resources and analyze Reservations or Savings Plans. WHEN: "optimize Azure costs", "reduce cloud spending", "rightsize resources", "find idle resources", "orphaned disk", "deleted VM still charged", "public IP still charging", "reservation utilization", "Savings Plan coverage", "commitment recommendation", "why is pay-as-you-go still charged". DO NOT USE FOR: cost spikes, forecasts, pricing estimates, budgets, or governance.
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。
microsoft/azure-skills☆ 1,5662026年10月14日 更新
Analyze actual Azure spend, bill changes, and AKS or AI costs. WHEN: "Azure cost breakdown", "most expensive resources", "why did my bill increase", "cost spike", "unexpected charge", "Cosmos DB charges", "Foundry model costs", "AKS cluster cost", "namespace cost", "enable AKS cost analysis", "idle AKS capacity". DO NOT USE FOR: forecasts, pricing estimates, rightsizing, commitments, or budgets.
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。
microsoft/azure-skills☆ 1,5662026年10月14日 更新
Build Unreal Engine 5 gameplay with Blueprint visual scripting: Blueprint Classes, the Event Graph and Construction Script, variables/functions/macros, and Blueprint communication (Cast, Interfaces, Event Dispatchers). Use when working in Blueprints, wiring an event graph, deciding how Blueprints talk to each other, or when the user mentions Blueprint, BP, event graph, construction script, or a Blueprint .uasset.
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。
gamedev-skills/awesome-gamedev-agent-skills☆ 1,4992026年10月9日 更新
Build event-driven, decoupled Godot 4.7 gameplay with signals and node groups: declare and emit custom signals, connect with Callables (incl. bind/one-shot), and broadcast to many nodes via groups and call_group. Use when wiring node communication in a Godot project, replacing tight references with signals, emitting/connecting events, or porting 3.x connect("sig", self, "method") code.
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。
gamedev-skills/awesome-gamedev-agent-skills☆ 1,4992026年10月9日 更新
Review a bill of materials for cost, risk, and supply exposure — cost rollup, top-10 cost drivers, single-source and EOL risk, MOQ vs forecast mismatch, cost-down candidates, and tariff/logistics sensitivity. Use when asked to review a BOM, find cost-down opportunities, check component sourcing risk, or sanity-check BOM cost against target. Produces a structured BOM review with a cost driver Pareto, risk flags per line, and a prioritised cost-down list.
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。
mohitagw15856/pm-claude-skills☆ 1,4522026年10月13日 更新
Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes. Use when a CFO asks what the AI tools returned, when renewing AI contracts, when consolidating overlapping AI subscriptions, or to build the measurement plan before the next spend. Produces an ROI audit with per-tool verdicts (keep/consolidate/cut), the honest-measurement method behind each number, and a baseline plan for whatever can't be scored yet. To forecast ROI before an investment use roi-estimator; this skill measures what already happened.
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。
mohitagw15856/pm-claude-skills☆ 1,4522026年10月13日 更新
Use this skill when the user wants to build a financial model — 3-statement model, DCF valuation, LBO, SaaS unit economics, sensitivity / scenario analysis, debt schedule, or fundraising projections — in Excel. Trigger on: 'financial model', '3-statement model', 'P&L + BS + CF', 'DCF', 'WACC', 'NPV', 'terminal value', 'LBO', 'debt schedule', 'cash sweep', 'MOIC', 'IRR / XIRR', 'sensitivity table', 'scenario analysis', 'ARR model', 'unit economics', 'CAC / LTV', 'cap table forecast'. Output is a single formula-driven .xlsx. This skill is a scene layer on top of officecli-xlsx — it inherits every xlsx v2 rule (4-color code, visual floor, number formats, cache-drift, Known Issues, Delivery Gate minimum cycle). DO NOT invoke for a simple budget tracker, CSV dump, or operational KPI sheet — route those to officecli-xlsx base.
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。
Team-Commonly/commonly☆ 1,3612026年10月14日 更新
Use when optimizing the performance of an existing native scalar expression in the datafusion-comet-spark-expr crate (native/spark-expr/) — casts, string/JSON/array/math kernels that run per-row or per-batch. Covers benchmarking, keeping output bit-identical, and the no-regression gate. Not for adding new expressions (use implement-comet-expression) or wiring upstream functions (use wire-datafusion-function).
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。
apache/datafusion-comet☆ 1,2882026年10月14日 更新
Repurposes long-form video (podcasts, interviews, talks) into short-form vertical clips for Instagram Reels, TikTok, and YouTube Shorts. Handles transcription, moment selection, clip extraction, speaker-tracked reframing (16:9 to 9:16), and animated captions.
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。
gooseworks-ai/goose-skills☆ 1,2472026年10月14日 更新
Comprehensive GTM analysis of any target company. Researches what a company is currently doing across all go-to-market dimensions — content/blog, founder LinkedIn activity, SEO/traffic, hiring signals, social/community presence, customer acquisition channels, podcast appearances, review sites, competitive positioning, and partnerships. Produces a structured report identifying what's working, what's missing, and where white space exists for new strategies. Use before designing GTM strategies for a client or prospect.
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。
gooseworks-ai/goose-skills☆ 1,2472026年10月14日 更新
Assemble a narrated motion-graphic LISTICLE video ad from a config — a spoken voiceover (cloned or cast, in the chosen tone) carries a numbered listicle while N web-animated hyperframe beats (HTML plus the Web Animations API, one branded design system of alternating tiles, big hero numerals, and callouts in the chosen visual style) are rendered frame-by-frame via Playwright and anchored to the VO's word-level timestamps, optional color-graded breather windows (brand clip, AI clip, or motion-graphic) give visual breath, and captions burn ONLY inside those B-roll windows (2-word chunks, ASS Format header carrying a Name field so none drop) with the VO mixed under a low music bed. This is the FREE deterministic assembly stage (Playwright beat render plus ffmpeg concat plus window-masked caption burn plus VO-and-music mix plus final composite) — the VO, the music bed, and any AI breather clips come from create-vo-elevenlabs, create-music-elevenlabs, and create-video-fal. Use for the vo-anchored-motion-listicle format.
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。
gooseworks-ai/goose-skills☆ 1,2472026年10月14日 更新
Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating candidate spacers, applying hard filters (Pol-III TTTT terminator, 5' G, GC), ranking on-target activity with the context-appropriate model (Rule Set 2/Azimuth for U6/lentiviral, CRISPRscan for T7/embryo, DeepHF for high-fidelity variants, DeepCpf1 for Cas12a), and predicting the indel/frameshift outcome (Bae out-of-frame score, inDelphi, FORECasT, Lindel). Use when selecting sgRNAs to knock out a gene, choosing a nuclease/PAM for a constrained locus, picking which exon to target, or shortlisting guides before an off-target check. Off-target specificity, base/prime editing, and HDR donors are separate 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。
GPTomics/bioSkills☆ 1,2192026年8月15日 更新