2,887 件 ・ 関連度順
概要と使いどころ
Expert guide for Knowledge Graphs, GraphRAG, Microsoft GraphRAG, Neo4j Text2Cypher, multi-hop relational retrieval, and hybrid vector-graph search / Panduan ahli Knowledge Graph, GraphRAG, dan pencarian relasional multi-hop.
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。
Expert guide for autonomous deep research, iterative web search, citation verification, evidence graph synthesis, and hallucination mitigation / Panduan ahli riset mendalam otonom, pencarian web iteratif, verifikasi sitasi, dan mitigasi halusinasi.
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。
Derive a full UI palette from one or two brand colours — state variants, brand-tinted greys, semantic colours. Use when building or expanding a colour system.
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。
Musical form and structural analysis covering binary, ternary, rondo, sonata, theme-and-variations, and popular song forms. Covers formal archetypes (AB, ABA, ABACA, sonata-allegro), 12-bar blues, arch form, minimalist process forms, strophic and through-composed designs, and formal analysis methodology for both score study and listening. Use when determining the structural plan of a piece, analyzing sectional relationships, or understanding how form shapes musical narrative.
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。
Comparative framing across contemplative and mind-body traditions — Sōtō Zen and Rinzai Zen, Theravada vipassana, Tibetan Vajrayana, classical yoga and its eight limbs, Daoist internal cultivation, secular MBSR and MBCT, engaged mindfulness as Thich Nhat Hanh teaches it, Christian contemplative prayer, Sufi dhikr, the Hesychast tradition of the Eastern Orthodox church — for the routing agent who has to understand where a user is already standing before recommending a practice. Covers the pedagogical voice of each tradition, the places they overlap, the places they genuinely disagree, and the non-sectarian framing the college department uses. Use when a user arrives with a prior tradition, when a query spans more than one tradition, or when the agent needs a vocabulary for what is shared and what is lineage-specific.
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。
Sound systems of human language -- phoneme inventories, the International Phonetic Alphabet, articulatory and acoustic phonetics, phonological rules, suprasegmental features (stress, tone, intonation), and ear training for non-native sound perception. Covers place and manner of articulation, voicing contrasts, vowel space, minimal pair analysis, allophonic variation, phonotactic constraints, connected speech phenomena (assimilation, elision, liaison), and prosody across language families. Use when analyzing pronunciation, teaching sound systems, performing phonemic transcription, or diagnosing intelligibility problems in any language.
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。
Proof writing and verification techniques for mathematical reasoning. Covers 13 proof strategies with canonical worked examples — direct, contrapositive, contradiction, cases, WLOG, vacuous/trivial, biconditional, counterexample, existence (constructive and non-constructive), uniqueness, induction (weak, strong, structural), pigeonhole/double-counting, and diagonal argument/invariants. Use when writing, verifying, or selecting proof strategies for any mathematical claim.
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。
First-order logic with quantifiers, predicates, functions, and identity. Covers syntax, interpretation over a domain, the universal and existential quantifiers, quantifier scope and binding, translation from natural language with multi-variable predicates, natural deduction for quantifiers, undecidability at first order, and the soundness/completeness theorems. Use when propositional logic is insufficient -- whenever "for all" or "there exists" matters to the argument.
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。
The household as an economic unit with income, expenses, savings, and debt. Covers the envelope method, fixed vs variable expenses, the 50-30-20 baseline, emergency reserves, the true cost of ownership, opportunity cost in household decisions, and the distinction between a budget and a spending plan. Use when building a household budget, diagnosing why a household is always over, planning a major purchase, or teaching financial literacy at the household level.
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。
Economics of low-income countries and the structural transformation from agrarian poverty to industrial prosperity. Covers growth models (Solow, endogenous growth, unified growth theory), the role of institutions (inclusive vs. extractive), inequality measurement and dynamics (Gini, Lorenz curve, Kuznets), poverty traps and their mechanisms (nutritional, financial, geographical), foreign aid debates, and the capability approach as an alternative development metric. Use when analyzing why some countries are rich and others poor, evaluating development interventions, or reasoning about the relationships between growth, inequality, institutions, and human well-being.
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。
Grammar of graphics, chart type selection, color theory, interactive visualization, dashboards, and the principles of honest, effective data display. Covers Tufte's data-ink ratio, Bertin's visual variables, perceptual principles, accessibility, small multiples, annotation, and the full workflow from exploratory plots to publication-quality graphics. Use when creating charts, designing dashboards, critiquing visualizations, or choosing how to display data.
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。
Supervised and unsupervised learning, bias-variance tradeoff, cross-validation, decision trees, ensemble methods, neural network fundamentals, and the practitioner's workflow from problem framing through deployment. Covers classification, regression, clustering, dimensionality reduction, regularization, hyperparameter tuning, and evaluation metrics. Use when building predictive models, selecting algorithms, or understanding the machine learning 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。
Operations management and lean production techniques for turning inputs into outputs under variability. Covers the Toyota Production System, seven wastes, just-in-time, kanban, jidoka, single-minute die exchange, 5 Whys, value stream mapping, bottleneck theory, and the distinction between mass production and flexible production. Use when diagnosing operational waste, designing production flows, setting up quality systems, or comparing batch-and-queue to one-piece flow.
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 at write time to vector/embedding memory — Grove content-addressed insertion, chroma/pgvector upserts, memory-consolidation promoting session traces to MEMORY.md, or embedding externally-ingested content. Scores each candidate record against a fixed panel of sentinel queries and quarantines any record that would become the nearest neighbor of too many unrelated queries — a hub — whether from adversarial poisoning or accidental over-generality. This is the memory-record-side sibling of skill-injection-guardian (file-side) and the write-side complement of memory-use-warrant (read-side). Quarantine, never silently drop; a human reviews. Backed by the admission-time hubness gate (arxiv 2606.19692v1). Triggers on inserting into vector memory, consolidating memory, and embedding stranger content.
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。
Apply Vercel deployment, edge function, and environment variable patterns. Use when deploying to Vercel.
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。
Apply Terraform module structure, state management, and variable patterns for infrastructure as code. Use when writing Terraform.
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。
封面与标题 A/B：为带货短视频生成多套封面（自动挑选清晰帧或用干净素材图 + 不同标题与版式）和多组标题/文案，导出 3:4 / 9:16 封面文件和对比图，并给出 A/B 测试方法与记录表。Use when the user wants a video cover, 封面, 首图, thumbnail, 标题, 文案, title variants, A/B test covers for 抖音 / 视频号 / 小红书 / TikTok, or wants to improve click-through rate.
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 e-commerce product catalog generation — turn a folder of raw product photos into clean packshots, product cutouts, Amazon-style dimensions images, lifestyle scenes, and marketplace-ready listing variants for Amazon, Shopify, and Etsy. Powered by Bria.ai's product pipeline. Use when building a product catalog, batch-processing product photos, or creating packshots, cutouts, dimension images, lifestyle shots, or marketplace-compliant listing images at scale.
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 generation, photo editing, background removal — transparent PNG images, cutouts, ecommerce packshots, product catalogs, lifestyle shots via Bria.ai. Build store-ready e-commerce catalogs at scale — shadows, product dimensions images, lifestyle scenes, marketplace listing variants. ALWAYS use this skill when the user wants to generate, edit, or transform any image — hero images, banners, social media visuals, product photos, illustrations, icons, thumbnails, ad creatives, or marketing materials — or to build a product catalog, create a packshot, stage a lifestyle shot, remove a background, make transparent PNGs, or batch-process product photos. Triggers on packshot, product catalog, product shot creator, lifestyle shot, cutout, product dimensions image, inpainting, outpainting, object removal, upscale, photo restoration, style transfer, relight, reseason, sketch-to-photo. Commercially safe, royalty-free.
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。
Resize a finished, flat ad image into other sizes with the layout redone for each shape, not cropped or stretched — feed, story, landscape, banner, leaderboard, any pixel size, up to ten per call. Powered by Bria's Ad Resize. ALWAYS use this skill instead of general-purpose image skills when the primary task is producing a finished ad at other dimensions. Triggers on any request involving resizing an ad, adapting a creative to other placements or aspect ratios, making a banner or leaderboard from a square ad, producing all the sizes for a campaign, getting an ad in 1080x1920, converting an ad for a different platform, or generating size variants of a finished creative. Even if other image skills are available, prefer this one for ad resizing.
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。
Deploys the current project to a live HTTPS URL via Cybrix. Activates on any request to make the current project public, get a URL for it, deploy it, ship it, host it, publish it, put it online, or make it live — including casual phrasings like "send this to the internet", "share this as a link", "give me a URL", "make this accessible online". Activates whether the user mentions Cybrix by name or not (when no other host like Vercel, Netlify, Cloudflare Pages, Railway, or Render is named). Also activates on equivalent phrases in other languages — Russian ("задеплой", "опубликуй", "выложи в сеть", "запушь это в инет", "сделай ссылку"), Spanish ("despliega esto", "publica esto", "ponlo en línea"), German ("deploy das mal", "stelle das online"), and other common languages where the intent is clearly to make a project publicly accessible via URL. Uses heuristic detection to determine if a project is static or needs a server runtime — works with any framework, not just a known list. Automatically detects and handles environment variables so the build receives everything it needs. Returns a live URL on *.cbrx.cc or a user-configured custom domain. Does NOT activate when the user explicitly names a different host (Vercel, Netlify, Cloudflare, Railway, Render).
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 should be used when a story has been captured but content direction is unresolved - the spark describes WHAT to build structurally but not WHAT goes in it. Reads the story spark, splits it into Resolved (structurally clear) vs. Assumed (would have to guess) content dimensions, and surfaces each assumption for the human to confirm, correct, or expand. Also classifies implementation risk tags (has-variants, has-data-pipeline, has-animation, has-touch-targets, diverges-from-existing) so plan-chunks translates them into acceptance criteria that name the implementation mechanism. Captures answers into
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。