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cccskills

「data framework」の検索結果

528 件 ・ 関連度順

概要と使いどころ

Build applications with React Router in Framework, Data, Declarative, and unstable RSC modes. Use when configuring routes, route modules, loaders, actions, forms, fetchers, navigation, pending UI, SSR/SPA/pre-rendering, middleware, URL params/search params, or React Router upgrades.

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。

foxlau/react-router-v7-better-auth1242026年8月12日 更新

Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new 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。

alirezarezvani/claude-cto-team1172025年12月18日 更新

scrapling

無料

Scrape web pages using Scrapling with anti-bot bypass (like Cloudflare Turnstile), stealth headless browsing, spiders framework, adaptive scraping, and JavaScript rendering. This skill should be used when asked to scrape, crawl, or extract data from websites; web_fetch fails; the site has anti-bot protections; write Python code to scrape/crawl; write spiders.

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。

archibate/dotfiles-opencode1082026年4月29日 更新

Comprehensive competitor analysis, competitive intelligence, and comparison page creation. Use when analyzing competitive landscape, creating competitor comparison pages (alternative pages, vs pages, competitor A vs B pages), performing market research, building SWOT analysis, creating feature matrices, pricing comparisons, competitor teardowns, battle cards, or positioning maps. Covers research workflows, SEO-optimized comparison content, data-grounded reports with citations, 7-layer analysis framework, review mining, and sales enablement. Triggers include competitor analysis, competitive analysis, competitor teardown, vs page, alternative page, competitor comparison, market research, competitive intelligence, SWOT analysis, battle card, competitor pricing, market landscape, feature comparison, positioning map.

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。

manojbajaj95/claude-gtm-plugin1062026年9月18日 更新

Designs and executes compatibility-preserving migrations across APIs, schemas, frameworks, dependencies, protocols, storage, and infrastructure with baselines, coexistence, staged cutover, rollback or forward-fix paths, and explicit removal criteria. Use for deprecations, upgrades, data moves, contract changes, and replacing live implementations. Not for a local refactor with no external state or compatibility boundary.

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。

thiientv/godmode972026年8月26日 更新

shift

無料

Orchestrating migrations, upgrades, and modernization across frameworks, libraries, APIs, databases, and dependencies. Generates codemods, applies Strangler Fig, verifies equivalence, plans rollback.

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。

simota/agent-skills922026年10月12日 更新

Tags harness-decomposed curriculum items (KUDs, LTs, criteria) with a school's developmental band metadata while preserving source voice and labels. Supply the band schema; the skill derives mapping rules from it.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Use Nexscope (Search Intelligence Framework) data to analyze ASIN traffic source composition and exposure distribution, covering current period/previous period/newly entered/exited period comparisons. Trigger when the user mentions ASIN traffic sources, traffic structure analysis, organic traffic vs paid traffic share, exposure score breakdown, period comparison, new/exited traffic keywords, competitor traffic analysis, SP ad keyword count, brand ad exposure, Amazon's Choice exposure, editorial recommendation exposure, Top Rated exposure, video ad exposure, organic search exposure ratio, PPC traffic sources, promotional deal traffic sources, recommendation slot structure breakdown, ASIN traffic analysis, traffic sources, organic traffic share, ad traffic share, exposure analysis, traffic structure, period-over-period comparison, keyword churn, Nexscope. Even if the user does not explicitly mention "Nexscope", if their need involves analyzing an ASIN's traffic sources, exposure channel distribution, cross-period comparison, or competitor traffic structure comparison, this skill should also be triggered.

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。

nexscope-ai/nexscope-ecommerce-skills892026年10月9日 更新

Use when reviewing Spring Boot 4 / Java 17+ code with concrete files or diffs — pull requests, modules, or pasted Java/Spring sources — for migration risks, architecture boundary leaks, JSpecify null-safety gaps, security flaws, performance regressions, or Spring Data pitfalls. Not for Kotlin-only code, non-Spring frameworks, or generic review advice without code context.

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。

a-pavithraa/springboot-skills-marketplace792026年8月26日 更新

EU Compliance Officer for MiFID II investment firms and IDD insurance distributors. Implements compliance frameworks, ensures National Competent Authority reporting, conducts product governance oversight, manages suitability and appropriateness testing, reviews marketing and inducements, coordinates cross-border passporting compliance, implements GDPR data protection, conducts AML (5AMLD/6AMLD) monitoring, and prepares for NCA inspections. Use for compliance manual development, MiFID II/IDD implementation, or ESMA guideline interpretation.

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Produce a complete metrics definition doc — metric name, formula, data source, segmentation, SQL or event tracking spec, and what good/bad looks like. Given a product area, outputs the full metrics spec. Use when asked to "define KPIs", "metrics framework", "what should we measure", "north star metric", or "instrument this feature".

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。

tonone-ai/tonone762026年10月5日 更新

Generates Entity Framework Core configurations using Fluent API. Maps domain entities to database tables with proper relationships, constraints, and conventions.

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。

ronnythedev/dotnet-clean-architecture-skills752026年7月14日 更新

Advanced Zephyr RTOS kernel services. Covers inter-thread communication using Zbus (pub/sub), behavioral management with the State Machine Framework (SMF), background processing via work queues, and persistent configuration with the Settings subsystem. Trigger when building modular application architectures, complex state-driven logic, or requiring persistent data storage.

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。

beriberikix/zephyr-agent-skills692026年5月19日 更新

Audit a MaaFramework/Maa-series project's Git history to learn how Pipeline JSON, interface options, Python AgentServer CustomAction code, and related data tables evolved. Use when asked to review a Maa project from initial commit through a target commit, map `action: Custom` pipeline nodes to `@AgentServer.custom_action(...)` implementations, find pipeline/custom/option patterns or breakages, and produce a report plus skill-improvement 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。

KhazixW2/MaaGumballs672026年10月2日 更新

Add runtime UI options (select/checkbox/switch/input) to MaaFramework option surfaces such as `assets/interface.json` or `assets/resource/tasks/**/*.json`. Use when adding a user-facing toggle, selector, checkbox, or input; wiring options to `pipeline_override`; aligning option paths with Python `context.get_node_data()` or CustomAction params; or reviewing option behavior across Pipeline JSON and Python.

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。

KhazixW2/MaaGumballs672026年10月2日 更新

biomni

無料

Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical 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。

plurigrid/asi672026年7月10日 更新

Python web and API development enforcing strict route/domain/data layer separation, Pydantic v2 strict request-response models, edge-resolved auth, and async-safe HTTP clients. Use when working with FastAPI, Starlette, Django, Flask, HTTP endpoints, request models, authentication flows, async handlers, or any Python web framework task.

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。

Jamie-BitFlight/claude_skills672026年10月13日 更新

Real-time quotes, K-line charts, order book, trade ticks, intraday capital flow, market sentiment temperature, trading session schedule, security lists, exchange rates, and IPO calendar for HK/US/A-share/SG via Longbridge. Also covers ADR premium and FX carry frameworks. Triggers: "股价", "行情", "K线", "走势", "盘口", "资金流", "市场温度", "汇率", "IPO", "打新", "隔夜股", "ADR溢价", "外汇套息", "K線", "盤口", "資金流", "市場溫度", "匯率", "ADR溢價", "外匯套息", "现在多少钱", "多少钱", "stock price", "quote", "kline", "chart", "depth", "orderbook", "capital flow", "market sentiment", "exchange rate", "IPO calendar", "security list", "ADR premium", "fx carry", "market open", "trading hours", "开市", "溢价", "NVDA.US", "700.HK", "600519.SH", "股價", "走勢", "開盤", "今天開市"

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。

longbridge/skills642026年10月12日 更新

Financial statements, business segments, dividends, valuation multiples (PE/PB/PS), industry comparison, operating data, corporate actions, company and executive profiles, cross-stock comparison, and valuation ranking via Longbridge. Also: DCF models, value investing screens (low PE/PB, margin of safety), and behavioral finance analysis frameworks. Triggers: "财报", "三表", "利润表", "资产负债", "现金流", "估值", "PE", "PB", "分红", "公司信息", "高管", "行业估值", "并购", "DCF", "内在价值", "低估值", "安全边际", "行为金融", "小盘成长", "专精特新", "主营业务", "业务构成", "收入结构", "业务分析", "是做什么的", "是干嘛的", "公司画像", "行业排名", "行业龙头", "市场份额", "收入占比", "业务结构", "財報", "估值", "分紅", "內在價值", "安全邊際", "主營業務", "業務構成", "收入結構", "行業排名", "行業龍頭", "financial report", "income statement", "balance sheet", "valuation", "dividend", "company info", "industry valuation", "DCF", "value screen", "behavioral finance", "main business", "business composition", "revenue structure", "what does XX do", "industry ranking", "market share", "利潤表", "資產負債", "現金流", "行業估值", "併購", "行為金融", "小盤成長"

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。

longbridge/skills642026年10月12日 更新

Institution ratings, consensus price targets, EPS/revenue forecasts, finance calendar, shareholder data, fund holders, insider trades (SEC Form 4), short interest, industry rankings, peer group analysis via Longbridge. Frameworks: investment proposals, coverage initiation, stock research, competitive analysis, financial planning, and DeFi/on-chain analysis. Triggers: "机构评级", "目标价", "一致预期", "EPS预测", "内部人交易", "空头", "行业排名", "投资提案", "首次覆盖", "竞争格局", "财务规划", "DeFi收益", "链上数据", "機構評級", "目標價", "一致預期", "內部人交易", "空頭", "投資提案", "首次覆蓋", "競爭格局", "鏈上數據", "analyst rating", "price target", "consensus", "insider trades", "short interest", "coverage initiation", "DeFi yield", "on-chain", "earnings calendar", "finance calendar", "财报日历", "下周谁财报", "下周财报", "下周有哪些财报", "哪些财报", "谁财报", "FOMC", "非农", "股东", "谁持有", "股東", "基金持仓", "基金持倉", "機構評級", "目標價", "財務規劃"

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。

longbridge/skills642026年10月12日 更新

Quantitative strategy frameworks: pairs trading/cointegration, volatility regime strategies, seasonality/calendar effects, multi-factor models (IC/IR), factor research and screening, correlation analysis, statistical methods (ADF/GARCH), strategy optimization, execution modeling, hedging, and ML-based prediction (sklearn). Also provides CLI access to run indicator scripts against K-line data. Triggers: "量化", "因子", "配对交易", "协整", "波动率策略", "季节性", "多因子", "IC", "机器学习", "对冲", "量化策略", "協整", "波動率策略", "季節性", "多因子", "對沖", "quant", "pairs trading", "cointegration", "volatility strategy", "seasonality", "multi-factor", "factor model", "IC IR", "machine learning", "hedging", "walk-forward", "配對交易", "機器學習", "因子選股"

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。

longbridge/skills642026年10月12日 更新

Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration. Use when: the task directly matches context manager responsibilities within plugin agent-orchestration. Do not use when: a more specific framework or task-focused skill is clearly a better match.

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。

diegosouzapw/awesome-omni-skill622026年3月2日 更新

Browser Use is an open source browser automation framework for AI agents that turns websites into controllable interfaces for multi-step tasks. It combines a Python SDK, browser orchestration, and model integrations so agents can navigate, extract data, and complete workflows in real browsers.

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

Expert customer health scoring and analytics guidance. Use when designing health scores, building churn prediction models, analyzing usage metrics, identifying at-risk accounts, creating executive dashboards, or performing cohort analysis. Use for leading indicator development, customer data enrichment, risk escalation frameworks, and retention analytics.

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。

ncklrs/startup-os-skills522026年2月27日 更新