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cccskills

「large scale」の検索結果

166 件 ・ 関連度順

概要と使いどころ

Standardize a 2D animation baseline image with `/img2mo-std xxx.png/pos`. Use when preparing a character, creature, prop, or weapon baseline before motion generation, especially if the source image is too large, tightly cropped, lacks transparent action margin, has a white background, or later walk/attack/idle frames show clipping, overlap, scale popping, or inconsistent character size.

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。

WU-HAOTIAN34/2dimg2motion2122026年7月2日 更新

Review the working-tree changes (vs main) for correctness, concurrency, architecture, testing, and API/doc issues — following .github/CODE_REVIEW.md — and return a severity-graded report. Scales the machinery to the diff size: a single code-reviewer agent for a small change, or a fan-out-and-verify Workflow for a large/multi-unit one. Produces findings; it does not apply fixes (the caller does).

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。

adamayoung/TMDb1772026年10月13日 更新

BigCommerce is a hosted e-commerce platform with REST and GraphQL APIs for headless storefronts. Use when a user asks to set up a large-scale online store, build a headless store with the Storefront GraphQL API or the Catalyst Next.js storefront, manage products and orders through the REST API, or migrate from Shopify to a more API-friendly platform.

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。

TerminalSkills/skills1662026年10月14日 更新

Use this skill whenever you are reasoning about large-scale scientific projects, genomics, bioethics, data infrastructure, or long-term medical translation. Eric S. Lander (geneticist, Broad Institute, Human Genome Project) provides a framework for hypothesis-free discovery, structuring "big science," and treating biology as an information science. Reach for this when the user is discussing open science, collaborative ecosystems, CRISPR/gene editing ethics, managing massive datasets, or setting realistic timelines for technological breakthroughs. Apply his principles to avoid the "lone genius" myth, prevent overpromising, and build foundational infrastructure that serves the broader community.

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。

K-Dense-AI/mimeographs1302026年8月19日 更新

Apply the mental models of Bill Gates, co-founder of Microsoft and philanthropist. Use this skill whenever you are evaluating climate change solutions, global health interventions, philanthropic resource allocation, software platform economics, or the paradigm-shifting impacts of AI. Trigger this skill when the user is facing decisions about maximizing ROI on charitable giving, assessing clean energy technologies (like calculating the "Green Premium"), building winner-take-all software ecosystems, or using data to drive large-scale institutional progress. Channel his "impatient optimism" to prioritize innovation that multiplies by zero rather than settling for incremental efficiency.

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。

K-Dense-AI/mimeographs1302026年8月19日 更新

Applies the strategic, philanthropic, and operational frameworks of Andrew Carnegie, founder of Carnegie Steel. Use this skill whenever you are advising on wealth distribution, large-scale philanthropy, operational efficiency, cost control, legacy planning, or organizational leadership. Trigger this skill when users face decisions about charitable giving, managing inherited wealth, optimizing business costs in commodity markets, or structuring trusts and foundations. Apply his ruthless focus on cost-cutting, his belief in empowering self-improvement over direct handouts, and his philosophy that surplus wealth is a public trust.

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。

K-Dense-AI/mimeographs1302026年8月19日 更新

jeff-dean

無料

Applies the engineering and research philosophies of Jeff Dean, Chief Scientist at Google DeepMind and Google Research. Reach for this skill whenever you are designing large-scale distributed systems, optimizing latency and energy efficiency, or making architectural decisions about machine learning infrastructure. It should trigger automatically for topics involving hardware-ML co-design, model distillation, sparse activation, massively multi-task models, or scaling systems by 5x to 10x. Use this skill to evaluate system bottlenecks, transition from specialized to unified models, and optimize experimental velocity. Apply his mental models to avoid premature 100x scaling and to treat AI models as reasoning engines rather than memorization databases.

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。

K-Dense-AI/mimeographs1302026年8月19日 更新

pxmeter

無料

Used to invoke the PXMeter tool for rigorous quality assessment of biomolecular structure prediction models (e.g., proteins, nucleic acids, small molecules). This skill covers single-sample CIF evaluations and large-scale dataset benchmarks, providing rich result parsing support. Trigger this skill when the user asks to "run PXMeter", "compare PDB/CIF evaluation results of different tools", "check benchmark scores", or asks "how accurate is the structure generated by the model".

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。

bytedance/PXMeter1032026年8月7日 更新

Use for every task that plans, writes, edits, debugs, tests, refactors, reviews, or maintains code. Apply to professional repositories, scripts, apps, services, prototypes, beginner work, vibe coding, and bounded code changes inside large systems. Choose the fewest clear lines, files, paths, states, and abstractions that correctly implement the requested behavior. Do not invent fallbacks, compatibility paths, defensive layers, or future scale without evidence. Do not use for ordinary conversation, emotional support, prose, translation, summarization, social-media content, or general research or technical discussion that is not part of planning, changing, or reviewing code. Never weaken real security, integrity, concurrency, compatibility, privacy, accessibility, legal, or regulatory requirements.

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。

See-Sol-Lab/private-house-code-v2.5932026年9月7日 更新

Expert guide for designing Micro-Frontend architectures using Webpack Module Federation, Vite Federation, and Single-SPA for large scale Vue and React applications.

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。

roedyrustam/vibes-plug752026年10月9日 更新

arboreto

無料

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

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。

plurigrid/asi672026年7月10日 更新

anndata

無料

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

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。

plurigrid/asi672026年7月10日 更新

Orchestrates Apify actors for large-scale web scraping via the Apify Client SDK. Manages actor runs, dataset exports, and proxy configuration through the Apify API v2.

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。

agentskillexchange/skills522026年10月13日 更新

Navigate make-on-demand catalogues — ZINC-22 through CartBlanche and Enamine REAL Space — to find compounds that can actually be ordered. Use this skill to look substances up by ZINC identifier or structure, understand tranche partitioning by heavy-atom count and logP, and choose between screening an enumerated subset and searching a combinatorial synthon space with a fragment-growing method such as V-SYNTHES. Also trigger on ZINC22, CartBlanche, Enamine REAL, make-on-demand, tangible library, synthon, tranche, giga-scale enumeration, or ultra-large virtual screening.

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。

K-Dense-AI/drug-discovery-agent-skills372026年10月12日 更新

Use for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.

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。

cline/skills352026年7月21日 更新

Go code refactoring with automated tools: gofmt -r, gopatch, and rsc.io/rf. Use this skill when performing mechanical rewrites across a codebase — renaming identifiers, migrating API calls, moving types between packages, rewriting expressions, or replacing deprecated patterns. Triggers when the task involves bulk code transformation, API migration, structural rewrite, or the user mentions gofmt -r, rf, gopatch, coccinelle-style patching, or large-scale rename/move in Go.

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。

gotd/botapi302026年9月22日 更新

dask

無料

Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.

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。

charlieviettq/awesome-agent-skill262026年7月20日 更新

Master orchestrator for B2B SaaS marketing campaigns using the CATALYST framework (Coordinated Agents for Targeted, Analytics-Led, Year-round SaaS Transformation). Coordinates 90 specialist agents across 17 marketing disciplines. Use this skill for ANY large-scale marketing initiative: full GTM launches, annual marketing plans, multi-channel campaigns, quarterly planning, or any task requiring coordination across content, SEO, paid media, social, email, design, sales enablement, product marketing, analytics, project management, and client operations. Also triggers on: marketing strategy, campaign plan, GTM launch, quarterly plan, marketing ops, full-funnel campaign, marketing audit, growth plan.

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。

shalintripathi/saas-marketing-agents212026年10月13日 更新

Product marketing and go-to-market strategy for B2B SaaS launches and positioning. Use this skill when planning a product launch, developing positioning and messaging, analyzing competitive landscape, building customer advocacy programs, designing a customer referral program (who may accept the reward, how the introduction is made), designing a win/loss interview program, working out why we lose deals, designing GTM strategy, creating category positioning, planning analyst briefings, or deciding which country to expand into and how far to localize. Also use it for an early-stage startup where the founder is still doing the selling — running founder-led sales, setting up a design-partner program, judging whether you have product-market fit, deciding what not to do yet, deciding when to hire the first AE or first marketer, and moving upmarket to larger buyers. Also use it when your company has just acquired another (or is about to), to plan the marketing integration: what you may and may not do between signing and close, the first letter to the acquired customers, whether to keep, endorse, fold in or retire the acquired brand, merging the two marketing databases without mailing people who opted out, when to start cross-selling, and announcing a product sunset. Also use it to design a demand-generation campaign and the channel plan it runs on: one campaign with one job, the offer for buyers who are and are not in market, what each channel is for, the kill and scale rules set before launch, the follow-up sales agrees to, the yearly calendar of always-on programs and tentpole campaigns, and which channels to keep, test or stop. Also use it for brand marketing and demand creation — how much to spend on brand versus performance, what to measure when a brand campaign produces no conversion event, and how to answer "we cannot attribute it". Also triggers on: founder-led sales, founder-led GTM, design partners, design partner agreement, first customers, first 10 customers, do we have product-market fit, PMF, Sean Ellis test, very disappointed survey, pre-seed, seed stage, when to hire our first AE, first sales hire, first marketing hire, moving upmarket, going upmarket, enterprise readiness, first enterprise deal, what do enterprise buyers need before they sign, positioning, product launch, beta program, early access program, design partners, private preview, public preview, general availability, GA launch, when can we call it GA, can sales sell a beta feature, selling the roadmap, launch tier, competitive intelligence, messaging, customer advocacy, win/loss analysis, win/loss interviews, why we lose deals, closed-lost analysis, loss reason, close-reason field, competitive displacement, displace an incumbent, rip and replace, competitive takeout, switch from a competitor, win deals from a competitor, incumbent contract, renewal window, auto-renewal notice period, switching costs, EU Data Act, cloud switching rights, why do we lose to no decision, GTM, category design, ideal customer profile, ICP, what is our real ICP, who actually buys from us, refresh our ICP from closed-won deals, ICP refresh before planning, analyst briefing, G2 review, international expansion, market entry, expand into Europe, which country should we launch in next, localization, translate our site, in-country go-to-market, regional GTM, is cold email legal in Germany, brand marketing, brand awareness, brand vs performance, brand versus demand gen, demand creation, demand capture, 95-5 rule, out of market buyers, category entry points, distinctive brand assets, mental availability, brand tracking, brand health, brand lift, share of search, how do we measure brand, justify brand spend, brand budget. Also triggers on public-sector marketing: sell to government, government marketing, public sector go-to-market, federal marketing, state and local government, SLED, FedRAMP, FedRAMP marketing claims, can we say FedRAMP ready, GovRAMP, StateRAMP, VPAT, accessibility confor

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。

shalintripathi/saas-marketing-agents212026年10月13日 更新

Four-phase skill for planning and executing large-scale codebase migrations using full-context AI analysis. Produces an impact map, ordered batch plan, subagent execution protocol, and cross-codebase validation pass. Optimized for Fable 5's 1M-token context window.

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。

tinh2/skills-hub-registry202026年9月5日 更新

Use when designing, reviewing, or troubleshooting Salesforce duplicate prevention, matching rules, duplicate rules, and merge governance. Covers cleaning up duplicates that already exist at ordinary volume: merge sequencing, survivorship, stewardship ownership. Also covers the deployable MatchingRule / DuplicateRule metadata, the Alert-vs-Block action pair, DuplicateRecordSet reporting, and the Apex DMLOptions.DuplicateRuleHeader.allowSave bypass. Triggers: 'duplicate rule', 'matching rule', 'merge strategy', 'dedupe', 'survivorship', 'D&B', 'same contact twice', 'clean up duplicate records', 'clean up duplicate accounts', 'DUPLICATES_DETECTED', 'allowSave', 'FindDuplicates'. NOT for cleanup at volume — hundreds of thousands of records, batch merge jobs, DemandTools/Cloudingo — use data/large-scale-deduplication. NOT for which field values and child records the platform keeps in a merge - use data/record-merge-implications.

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。

PranavNagrecha/AwesomeSalesforceSkills192026年10月4日 更新

workgraph

無料

Orchestrate work as a cyclic directed graph of subagent-executed nodes with transition criteria on edges, budgeted cycles, and per-node gates (runtime verification, metric, or artifact). Use when the user says "workgraph", "run this as a graph", "graph this work", or when a goal has parallel branches, feedback loops, or mixed gate types that a linear loop cannot express. Every node is sized to a 64k context budget, so small goals run as a two-node do/verify graph and large goals scale out without caps. For clock-driven or metric-driven single loops, timeboxed-iterating and autoresearch remain lighter.

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。

av/skills192026年10月12日 更新

Coordinate large-scale codebase migrations and multi-file refactors across hundreds of files. Manage framework upgrades, API renames, and config rewrites using batched PRs, issue tracking, and CI verification.

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。

manu14357/zskills162026年7月24日 更新

Monetization strategies for indie developers, solopreneurs, and small teams. Covers freemium models, SaaS pricing, sponsorships, donations, email list building, and passive income for developer tools, content sites, and educational apps. Activate on 'monetization', 'make money', 'pricing', 'freemium', 'SaaS', 'sponsorship', 'donations', 'passive income', 'indie hacker'. NOT for enterprise sales, B2B outbound, VC fundraising, or large-scale advertising (use enterprise/marketing 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。

curiositech/windags-skills142026年10月12日 更新