195 件 ・ 関連度順
概要と使いどころ
Full SEO audit powered by the DataForSEO API. Orchestrates 5 specialist subagents (keywords, technical, competitors, content, backlinks) hitting DataForSEO Keywords Data, SERP, On-Page, Backlinks, and Labs endpoints in parallel, then produces a composite SEO Score (0-100) with prioritized action plan and audit JSON ready for PDF export.
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 Agency Onboard — launches 5 parallel audit teams and produces a unified client-ready report with composite scoring
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。
Image processing toolkit awareness. Use when: user uploads images for manipulation, requests format conversion, batch processing, compositing, resizing, optimization, analysis, effects, metadata inspection, montages, animated GIFs, color correction, or any image-related task. Also use when working with screenshots, photos, diagrams, icons, or visual assets. Triggers on 'resize', 'crop', 'convert', 'compress', 'optimize', 'thumbnail', 'watermark', 'montage', 'collage', 'gif', 'sprite sheet', 'color space', 'metadata', 'EXIF', 'compare images', 'diff', 'overlay', 'composite', 'batch process', 'image analysis', 'histogram', 'blur', 'sharpen', 'rotate', 'flip', 'border', 'shadow', 'round corners', 'favicon', 'icon set'.
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 has a video + an SRT and wants the subtitles either burned into the pixels (libass, always-visible) or soft-muxed as a togglable track. Also handles the final composite step for the localization pipeline — burn subs, mix a dub track, and keep the original audio as a low-volume bed, all in ONE ffmpeg encode (no cascade). Verifies libass availability and auto-downloads a static evermeet ffmpeg build when Homebrew's stripped binary lacks it. Triggers — "烧字幕", "硬字幕", "burn subtitles", "burn-in subs", "embed subtitle", "soft mux SRT", "把字幕烧进视频", "做最终合成".
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。
End-to-end production workflow guidance for Blender — the order to assemble scenes (block-out → camera → light → forms → materials → detail → render → composite → export), critique protocols, time budgets, and recovery patterns. Use whenever the user asks to "make a complete scene / hero shot / production-quality render", "what's the right order to do this", "set up a full pipeline", or has a multi-step request crossing modeling + lighting + materials + rendering. Make sure to use this skill for any request that spans multiple phases of 3D work, even if the user does not say "workflow" — also covers "make a final image of X", "produce a hero render", "professional-looking result".
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。
Present pathway options and orchestrate place-based curriculum design from a local place, curriculum requirement, or community issue. Use when place should become a primary text for learning.
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。
Present project-design pathway options and orchestrate regenerative projects using backwards design, PBL, SEEDS, compassionate systems action, or civic/service pathways.
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。
Coordinates UDL and differentiation tools through a universal-first hierarchy: barrier removal before targeted differentiation before individualised accommodation. Use when planning accessible learning.
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。
Orchestrate compassionate systems tools from issue or aspiration to wise action. Use when a class needs a complete inquiry 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。
Routes between five assessment pathways — formative, rubric/criteria, authentic/performance, peer/self, and diagnostic — with validity and equity checks. Use when a teacher needs help choosing how to assess.
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。
AI-driven image generation and editing tool for creating high-quality product images. Triggered when users ask to generate images, create product pictures, edit photos, text-to-image, image-to-image, replace backgrounds, transform styles, composite products into scenes, swap models, or create any type of AI-generated visual content. Even if the user does not explicitly say "AI image," this skill should be triggered whenever the request involves creating, modifying, or transforming images.
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。
Find Amazon same-niche competitors by ASIN, with multi-dimensional filtering by click conversion rate, composite conversion rate, click volume, sales volume, reviews, ratings, price, and gross margin to identify potential competitors. Triggered when users mention same-niche competitors, ASIN competitor mining, niche competitor analysis, similar product benchmarking, ASIN benchmarking, niche market competitor list, high-conversion competitor screening, Nexscope product mining, niche competitor by ASIN, ASIN competitor analysis, same niche products, similar products discovery, conversion rate comparison, potential competitor screening, Nexscope ASIN mining. Even if users do not explicitly mention "niche" or "same niche", this skill should be triggered whenever the task involves discovering competitor lists or screening potential competitors based on a specific ASIN within the same market segment.
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。
Prioritize drug targets from a ranked gene list (e.g., scRNA-seq DE output) by orchestrating parallel API queries against UniProt, OpenTargets (with integrated DepMap CRISPR essentiality + gnomAD constraint), PubMed, the Human Protein Atlas (HPA), and ChEMBL tool compounds, then re-ranking by a composite score combining protein localization, druggability, disease genetics, tissue specificity (safety), focus-cell-type expression, CRISPR essentiality, LoF safety constraint, and research maturity. Use whenever the user wants to filter, triage, prioritize, or "do due diligence" on a list of candidate genes for drug discovery, especially after a DE / DEG analysis when they say things like "which of these should I follow up on", "filter for druggable targets", "make a target dossier", "rank these for tractability", "annotate these genes for druggability", or "build a target report". Trigger even when the user says just "filter these candidate genes" or hands over a CSV from a DE pipeline.
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。
Flagship orchestrator that launches 5 parallel agents (cashflow, debt, investments, retirement, protection) to produce a comprehensive financial health analysis with a composite Financial Health Score (0-100), letter grade (A+ through F), and a prioritized 90-day action plan. Use when the user says "/finance analyze", "full financial analysis", "financial health check", "analyze my finances", or any request for a complete financial picture.
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 materials selection for engineering design using performance indices, Ashby charts, multi-constraint optimization, and case-based reasoning. Covers the five-step Ashby method — function, objective, constraint, free variable, index — with worked examples for stiffness-limited beams, strength-limited ties, thermally shocked vessels, and minimum-cost components. Use when choosing among metals, polymers, ceramics, and composites under competing objectives.
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。
Classic image manipulation with Python Pillow - resize, crop, composite, format conversion, watermarks, brightness/contrast adjustments, and web optimization. Use this skill when post-processing AI-generated images, preparing images for web delivery, batch processing image directories, creating responsive image variants, or performing any deterministic pixel-level image operation. Works standalone or alongside bria-ai for post-processing generated images.
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。
DeFi Protocol Analysis — analyzes TVL, revenue, yields, liquidity, security, governance, and competitive positioning with a composite DeFi Score (0-100)
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。
Risk Assessment & Position Sizing — analyzes volatility, drawdown, correlation, liquidity, smart contract, regulatory, concentration, and unlock risks with crypto-specific position sizing calculators and a composite Risk Score (0-100, higher = safer)
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。
Crypto Fundamental Analysis — evaluates project viability, team quality, technology, adoption metrics, and competitive moat with a composite Fundamental Score (0-100)
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。
Crypto Technical Analysis — analyzes trend, momentum, volume, chart patterns, and market structure across 24/7 crypto markets with a composite Technical Score (0-100)
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 Crypto Analysis Orchestrator — launches 5 parallel subagents for comprehensive multi-dimensional token analysis with composite Crypto Score
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。
Creates and manages CloudWatch alarms using the AWS SDK for JavaScript v3 (@aws-sdk/client-cloudwatch). Configures metric math expressions, composite alarms, and SNS notification routing via @aws-sdk/client-sns.
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 ASE skill uses zizmor to audit GitHub Actions workflows and composite actions for security mistakes before they ship. An agent can scan local repos or remote GitHub repositories, flag risky permission scopes and unsafe workflow patterns, and return plain output, GitHub-native findings, or SARIF for follow-up automation.
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。
Evaluates completed agent pipelines across 5 scoring dimensions and produces a composite verdict with actionable recommendations
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。