「structure」の検索結果

Create and structure Claude Code agent skills. Use when the user wants to create a new skill, write an agent skill, make a claude skill, or asks about SKILL.md files.

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Create, use, and manage Agent Skills for Claude. Use when working with Skills, creating custom capabilities, or understanding how Skills extend Claude's functionality. Covers Skill architecture, file structure, and best practices.

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。

Test agent delegation patterns to verify hierarchy and escalation paths. Use after modifying agent structure.

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。

Systematically deconstruct written content into verifiable claims, validate each using search/documentation, and facilitate informed discussion through structured interviewing.

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。

Write effective system prompts for TD AI agents. Covers role definition, constraint specification, output formatting, tool usage instructions, and prompt structure patterns.

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 in designing, orchestrating, and managing multi-agent systems (MAS). Specializes in agent collaboration patterns, hierarchical structures, and swarm intelligence. Use when building agent teams, designing agent communication, or orchestrating autonomous workflows.

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。

Evaluate a codebase for agent-friendliness based on autonomous agent best practices. Use when asked to "evaluate for agents", "check agent readiness", "audit for autonomous execution", "assess agent-friendliness", or when reviewing infrastructure for unattended agent operation. Also use when asked about making a codebase more suitable for AI agents or autonomous workflows.

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。

Analyze the codebase to create a concise, LLM-optimized structured overview in .agent/map.md.

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。

Create well-structured prompts for AI agents using proven architecture patterns. Use when users ask to write agent prompts, system prompts, or agent instructions, or want to improve existing prompts that aren't working.

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。

Ready-to-use prompt templates for specialized agents. Use when building n8n workflows, AI integrations, or sales materials. Contains structured prompts for automation-architect, llm-engineer, and sales-automator agents.

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。

Visual context analyzer for AI agents. Provides screenshots, accessibility scans, DOM snapshots, and element descriptions for web pages. Use when you need to see what a web page looks like, analyze accessibility issues, inspect DOM structure, or get detailed element information. Triggers on requests like "take a screenshot", "check accessibility", "what does this page look like", "analyze the UI", "inspect this element", or any visual/UI analysis 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。

Evaluate agent performance using a structured scoring rubric

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Structured cross-review protocol between specialized agents. Ensures scope alignment, priority calibration, and domain-aware feedback. Use when one agent reviews another's work, during handoffs, or when validating cross-cutting concerns.

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。

Standardized reference documentation section structure for agents - project guidance, conventions, related agents, and Skills. Use when implementing or updating agent documentation.

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This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

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Comprehensive documentation of Claude's capabilities for visual regression testing, CI/CD integration, and quality assurance automation. Use when setting up testing infrastructure, implementing visual regression, or understanding agent testing capabilities. (project)

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Add Qdrant embedding support to v3 WordPress components for RAG chatbot. Implements component-level content chunking for searchable, structured embeddings. Use when adding embedding to new or existing v3 components.

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。

Create a new skill for this repository following the agentskills.io specification with proper structure and packaging

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Validate AgentConfig definitions for the Agent Framework. Use when creating or modifying agent configurations to ensure correct structure, valid tool references, and proper sub-agent composition. Validates TypeScript interfaces and Python Pydantic models.

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。

Create a structured session handoff when context is running low or work is pausing. Deep context mining, self-validation, multi-file splitting. Captures everything the next session needs.

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。

Structured code review through the shared OpenClaw agent-skills installation.

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Market intelligence: strategy screener, popularity rankings, top movers with news correlation, quote anomalies, index/ETF constituent stocks, morning briefings, catalyst monitoring for watchlist, event-driven strategies, ETF fund flows, sector rotation, market microstructure, supply chain analysis, industry overviews, and ARK-style disruptive innovation analysis. Triggers: "筛选", "策略筛选", "排行", "热度", "异动", "成分股", "晨报", "早报", "催化剂", "事件驱动", "ETF资金流", "板块轮动", "产业链", "行业概览", "颠覆式创新", "ARK", "篩選", "排行", "異動", "成分股", "晨報", "ETF資金流", "板塊輪動", "產業鏈", "screener", "rank", "anomaly", "constituent", "morning brief", "catalyst", "event strategy", "ETF flow", "ETF资金流", "ETF申赎", "ETF資金流", "etf flow", "资金申赎", "etf 资金", "sector rotation", "supply chain", "ARK", "disruptive innovation", "板块筛选", "行业筛选", "板塊篩選", "強勢板塊", "弱勢板塊", "top sectors", "催化劑", "事件驅動", "行業概覽", "顛覆式創新", "策略篩選", "熱度"

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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。

Draws out a founder's or expert's point of view: what they believe about their market that others don't, the hot takes they'd defend, the stories behind them, and their taste. Generates interview questions, works from answers, a live call or existing content, and ends with ranked One Big Idea candidates for thought leadership and positioning. Triggers: "expert POV", "founder POV", "one big idea", "OBI", "contrarian beliefs", "what makes our founder different", "thought leadership foundation", "founder interview questions". Feeds /positioning and /tov-guidelines. Not for writing posts or articles, and not for brand voice rules (use /tov-guidelines).

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。