本文へ移動
cccskills

「rag」の検索結果

5,141 件 ・ 関連度順

Expert knowledge for Azure Operator Nexus development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and deployment. Use when managing Nexus clusters, fabric ACLs/BGP, isolation domains, near‑edge storage, or upgrade workflows, and other Azure Operator Nexus related development tasks. Not for Azure Operator Insights (use azure-operator-insights), Azure Operator Service Manager (use azure-operator-service-manager), Azure Networking (use azure-networking), Azure Virtual Network Manager (use azure-virtual-network-manager).

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。

MicrosoftDocs/Agent-Skills7872026年10月19日 更新

Expert knowledge for Azure HDInsight development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when working with HDInsight Spark/Hive/Kafka/HBase clusters, Ambari/Oozie pipelines, or Azure-integrated storage/BI, and other Azure HDInsight related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure Stream Analytics (use azure-stream-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。

MicrosoftDocs/Agent-Skills7872026年10月19日 更新

Expert knowledge for Azure Durable Task development including best practices, decision making, architecture & design patterns, limits & quotas, configuration, integrations & coding patterns, and deployment. Use when building Durable orchestrations with Azure Storage/SQL/Netherite, versioning deployments, or using instance APIs, and other Azure Durable Task related development tasks. Not for Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps), Azure App Service (use azure-app-service), Azure Service Fabric (use azure-service-fabric).

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。

MicrosoftDocs/Agent-Skills7872026年10月19日 更新

Expert knowledge for Azure Defender For Cloud development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when securing VMs/containers/storage/SQL, enabling plans, tuning alerts, exporting via APIs/ARG, or integrating SIEM/XDR, and other Azure Defender For Cloud related development tasks. Not for Azure Security (use azure-security), Azure Sentinel (use azure-sentinel), Azure DDoS Protection (use azure-ddos-protection), Azure External Attack Surface Management (use azure-external-attack-surface-management).

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。

MicrosoftDocs/Agent-Skills7872026年10月19日 更新

Expert guidance for designing Azure solutions using Azure Architecture. Covers reference architectures, solution ideas, design patterns, technology choices, architecture styles, best practices, anti-patterns, example workloads, and migration guides. Use when designing RAG/GenAI, AKS, SAP or mainframe migrations, HA/DR topologies, or secure hybrid networks, and other Azure Architecture related development tasks.

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。

MicrosoftDocs/Agent-Skills7872026年10月19日 更新

Expert knowledge for Azure Cloud Shell development including troubleshooting, limits & quotas, and security. Use when handling Cloud Shell storage mounts, session limits, file persistence, private VNet access, or RBAC setup, and other Azure Cloud Shell related development tasks. Not for Azure Portal (use azure-portal), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop), Azure DevOps (use azure-devops).

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。

MicrosoftDocs/Agent-Skills7872026年10月19日 更新

Expert knowledge for Azure Content Understanding in Foundry Tools development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when designing Content Understanding analyzers, RAG document flows, agentic workflows, REST/SDK calls, or Foundry deployments, and other Azure Content Understanding in Foundry Tools related development tasks. Not for Azure Speech in Foundry Tools (use azure-speech), Azure AI Search (use azure-cognitive-search), Azure AI Document Intelligence (use azure-document-intelligence), Azure AI Video Indexer (use azure-video-indexer).

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。

MicrosoftDocs/Agent-Skills7872026年10月19日 更新

Expert knowledge for Azure Copilot development including troubleshooting, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when sizing VMs, generating Bicep/Terraform, configuring Cosmos DB chat storage, or designing Azure networks, and other Azure Copilot related development tasks. Not for Azure Portal (use azure-portal), Azure Machine Learning (use azure-machine-learning), Azure DevOps (use azure-devops), Microsoft Foundry (use microsoft-foundry).

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。

MicrosoftDocs/Agent-Skills7872026年10月19日 更新

Amazon listing builder and optimizer for sellers. Two modes: (A) Create — build keyword-optimized listings from scratch using keyword lists + product characteristics + AI copywriting, (B) Optimize — audit existing listings, find keyword gaps, score across 8 dimensions, and rewrite with missing keywords. Integrates with amazon-keyword-research for keyword input. Works on 12 Amazon marketplaces. No API key required. Use when: (1) creating a new Amazon listing from keywords, (2) auditing an existing listing for SEO and conversion, (3) checking keyword coverage in title/bullets/description, (4) generating listing copy with target keywords and tone, (5) comparing listings against competitors, (6) preparing a listing for launch or relaunch.

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/Amazon-Skills7852026年8月26日 更新

Read your Robinhood Agentic brokerage account via the Robinhood Trading MCP - portfolio, buying power, positions, and order history - and place a single operator-instructed trade. OAuth Connect via the dashboard MCP panel.

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。

aeonfun/aeon7782026年10月20日 更新

Detect suspected manipulation on prediction markets over the past 3 days by cross-referencing price/volume/comment anomalies with multilingual local-press coverage

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。

aeonfun/aeon7782026年10月20日 更新

5 concrete real-life actions, leverage-scored against open loops with specificity and anti-fluff gates

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。

aeonfun/aeon7782026年10月20日 更新

Pre-send quality scorecard for any lead list. Grades duplicate rate, title diversity, bad-title patterns, catch-all domain density, ICP fit, email verification coverage. Outputs a letter grade + action items BEFORE you send. Catches bad lists before they burn inboxes. Run after email enrichment, before Smartlead upload.

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。

growthenginenowoslawski/coldoutboundskills7722026年10月6日 更新

Expand a hard-to-build niche list from ~10 known-good seed companies into a full qualified TAM. Seed fingerprinting (how do good-fit companies ACTUALLY show up in the company database's filters) → lookalike generation (Prospeo company_lookalike, Exa findSimilar, Parallel.ai entity search) → filter mining with a precision/volume scorecard → wide pull with auto-sharding → cheap-AI qualification → live-website verification → client transparency report. Use when a vertical list feels "too small" (medical groups, hedge funds, Medicare brokerages), when known good-fit companies don't show up in keyword searches, or when someone says "expand this list", "the TAM should be bigger", "find more companies like these".

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。

growthenginenowoslawski/coldoutboundskills7722026年10月6日 更新

Writes the character-performance layer of a video prompt as behavior under pressure, not displayed emotion — objective, obstacle, tactics, beats, subtext, listening, body/status/proxemics, and mandatory eye life. Produces a reusable 150–220-word acting master profile per character plus a per-scene rewrite of it, and a locked voice prompt. Use whenever a prompt needs acting, performance, or emotion direction; whenever characters read wooden, dead-eyed, or 'AI'; whenever a character must stay themselves across many shots; or when the user asks for character behavior, mannerisms, tics, a gait, or how someone reacts. Pairs with higgsfield-facs (muscle-level AU codes) and higgsfield-seedance (the prompt the paragraph goes 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。

OSideMedia/higgsfield-ai-prompt-skill7672026年9月27日 更新

Write high-quality JUnit 5 tests with AssertJ assertions. Use when user says "add tests", "write tests", "improve test coverage", or when reviewing/creating test classes for Java 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。

decebals/claude-code-java7582026年9月7日 更新

Maintain skills wiki health - check links, naming, cross-references, and coverage

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。

obra/superpowers-skills7542025年10月15日 更新

old-coder

無料

Evidence-first development — surround the implementation with an executable spec and a gauntlet of constraints (tests, types, coverage, mutation) so line-by-line review becomes optional. Use when the user explicitly asks for high-assurance or evidence-first work ("reliable", "TDD", "prove it works", "I won't read the code"), or when the change touches high-stakes domains (money, auth, data loss, concurrency, public API). For routine changes where the user just wants normal tests, write good tests directly instead of invoking this loop.

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。

AmazingAng/old-coder7532026年8月18日 更新

LlamaIndex 官方用户文档离线知识库,用于检索并回答 LlamaIndex Python 框架的安装、RAG、数据加载、索引、检索与查询、Agent、Workflow、模型、Embedding、向量库、评估、可观测性、部署、LlamaCloud 和 LlamaParse 等问题,也可生成有文档依据的示例代码与排障建议。当用户提到 LlamaIndex、llama-index、LlamaParse、VectorStoreIndex、QueryEngine、Retriever、AgentWorkflow 或相关集成用法时使用;纯源码贡献、内部实现审查或与 LlamaIndex 无关的通用 AI 问题不使用。

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。

chujianyun/skills7492026年10月16日 更新

用 MinerU 将复杂PDF文档转换为LLM友好的Markdown/JSON格式。适用于:(1) PDF转Markdown/JSON,(2) 提取PDF中的文本、表格、公式、图像,(3) 解析学术论文、技术文档、商业报告,(4) 为RAG应用准备文档数据,(5) 批量处理PDF。触发关键词:"PDF解析"、"PDF转Markdown"、"提取PDF表格/公式"、"MinerU"、"parse PDF"等。不用于:PDF的阅读/填表/签名/拆分合并(用宿主pdf工具)、Word/PPT等非PDF格式解析、只需读几页内容的场景(直接读即可,不必转换)。

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。

staruhub/ClaudeSkills7302026年8月13日 更新

bootstrap

無料

Capify an existing project. Scans the repo for already-installed MCP servers, skills, rules, hooks, sub-agents, and plugins (across .claude, .cursor, .codex, .gemini, etc.), consolidates them into shared top-level directories (skills/, rules/, hooks/), and synthesizes a sound capabilities.yaml from the inventory. Use whenever the user says "bootstrap capa", "capify this project", "onboard capa onto an existing repo", "inventory my agent setup", or asks how to turn an ad-hoc Claude/Cursor/Codex configuration into a capabilities file. Use even when the user only mentions one provider — discovery should still sweep all of them.

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。

infragate/capa7252026年10月20日 更新

Generate an AI Citations Report (GEO) for a domain — which AI-search prompts cite the site across Google AI Overview and ChatGPT, plus organic-traffic context and per-article citation coverage. Use when the user asks for an 'AI citations report', 'GEO citations report', or 'which AI prompts cite <domain>'.

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。

OpenClaudia/openclaudia-skills7182026年10月20日 更新

Audit EVERY Google Search Console property at once — rank all sites by clicks and impressions with period-over-period deltas, then diff keywords per site to surface what is newly ranking, rising, dropping, lost, or ranking well without earning clicks. Built for agencies and multi-site owners. Use when asked to compare all sites, rank properties by traffic, find new keywords across a portfolio, or spot which site is down. Trigger phrases: "audit GSC", "all my sites", "rank my properties", "portfolio search performance", "which sites are down", "what new keywords are we ranking for", "client site performance", "GSC report across accounts". For ONE site's queries, pages, or index coverage, use the search-console skill instead.

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。

OpenClaudia/openclaudia-skills7182026年10月20日 更新

5-dimension scorecard (0-100, grade A/B/C/F) for a scaffolded harness. Dimensions: Repo understanding (25%), Agent usefulness (25%), MCP safety (20%), Test coverage (15%), Publish readiness (15%). Emits a 6-field badges block (score + mcpRisk + 4 booleans) ready for the harness README. Exit 0 A/B, 1 C, 2 F.

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。

ruvnet/metaharness7092026年10月20日 更新