本文へ移動
cccskills
無料GitHub で公開

design-deep-research

Perform comprehensive, multi-source research on any topic using AI-powered web search and analysis. Covers deep_research for broad discovery and semantic_content_search for site-specific knowledge retrieval. Use when you need to research brands, markets, competitors, or trends with citations — before creating content, planning campaigns, or making strategic decisions.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md9.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Deep Research

Use this skill when the task requires thorough, multi-source research with citations — more depth than a quick web search.

Available Tools

ToolPurposeDepth
deep_researchMulti-step web search + AI analysis with citationsComprehensive — generates full reports
semantic_content_searchSearch site content via vector embeddingsFinds related content already on your WordPress site
search_contentHybrid keyword + semantic search of site contentUse search_type: "hybrid" for best results across your content

WP-CLI Commands

Key mcp-ai WP-CLI commands for research workflows. Run via terminal:

CommandUse for
wp mcp-ai harnessSemantic search across stored content
wp mcp-ai healthCheck search/tool connectivity
wp mcp-ai memoryReview stored research context

When to use this skill

Trigger when ANY of the following is true:

  • The task asks to "research", "investigate", or "do a deep dive" on a topic.
  • Building a brand or company profile for marketing purposes.
  • Researching a market, industry trend, or competitive landscape.
  • The task requires citations, sources, and substantiated findings.
  • "Find out everything about X" — breadth + depth matters.
  • Preparing a research report that will inform a campaign, content piece, or strategy.
  • The task mentions "deep research", "comprehensive research", or "multi-source".

deep_research — Comprehensive Topic Research

Use for broad, multi-source investigation. Performs multi-step web searches, AI analysis, and generates a structured report with citations.

Parameters

topic          — The research topic or question (required)
depth          — "basic" | "standard" | "comprehensive" (default: "standard")
focus_areas    — Optional specific aspects: ["technical", "historical", "pricing", "competitors"]
include_sources — Include source citations (default: true)
run_mode       — "immediate" (synchronous) | "background" (WordPress cron)
include_site_content — Search WordPress + Vector Store alongside web (default: true)
memory_agent_id — Recall prior research from agent memory before starting
store_to_memory — Auto-store report in agent memory (requires memory_agent_id)

Depth Selection

DepthWhenExample
basicQuick overview, fact-checking, simple questions"What are the top fragrance brands in Sri Lanka?"
standardMarketing research, brand profiles, campaign prep"Research Conatural — history, products, target market, competitors"
comprehensiveCompetitive analysis, market reports, strategic planning"Full analysis of Sri Lanka's luxury fragrance e-commerce market"

Focus Areas

Guide the research by specifying aspects:

For a brand:    ["history", "product range", "pricing", "target audience", "competitors"]
For a market:   ["market size", "trends", "key players", "consumer behavior", "growth forecast"]
For a trend:    ["origins", "current state", "adoption", "future outlook", "Sri Lanka context"]
For a competitor: ["products", "pricing", "marketing channels", "USPs", "weaknesses"]

Run Modes

ModeWhenTime
immediateInteractive tasks where you need results now30s–2min
backgroundLong research, non-urgent, large scopeMinutes to hours

Use immediate for most Sophie tasks. Use background for comprehensive market reports or when researching 10+ entities.

Output

Returns:

  • Report — structured findings with sections
  • Sources — URLs with type labels (manufacturer, retailer, news, etc.)
  • Product data (if applicable) — specs, pricing, images, attributes
  • SEO keywords — extracted from research for content optimization

Example

deep_research {
  topic: "Conatural skincare brand — history, product range, target market,
          certifications, competitors in Sri Lanka"
  depth: "standard"
  focus_areas: ["brand history", "product categories", "certifications",
                "pricing strategy", "Sri Lanka market position"]
  include_sources: true
  run_mode: "immediate"
}

semantic_content_search — Site Knowledge Retrieval

Search your own WordPress content (posts, pages, products) by meaning, not just keywords. Uses vector embeddings for semantic matching.

Parameters

query          — Natural language search query
post_types     — Post types to search (default: ["post", "page"])
limit          — Max results (default: 10, max: 100)
threshold      — Minimum similarity score 0–1 (default: 0.7)
vector_store_id — Optional OpenAI vector store ID
include_meta   — Include post metadata (default: false)

When to use

  • "Have we written about this before?" — check for existing content
  • "What products are related to X?" — find semantically similar products
  • "Find all content about Sri Lankan luxury market" — thematic search
  • Before creating new content — avoid duplication

Example

semantic_content_search {
  query: "luxury fragrance gifting ideas for Sri Lankan customers"
  post_types: ["post", "product"]
  threshold: 0.75
  limit: 10
}

Research Workflow

For a typical research task, follow this sequence:

1. SITE CHECK (optional)
   semantic_content_search → "Do we already have content on this?"

2. DEEP RESEARCH
   deep_research {
     topic: "..."
     depth: "standard"
     include_sources: true
   }

3. EXTRACT INSIGHTS
   From the report, pull:
   ● Key facts (for content)
   ● Competitor intel (for positioning)
   ● Market gaps (for campaign angles)
   ● Sources (for citations and further reading)

4. ACT ON IT
   → Feed findings into campaign orchestration
   → Create a WordPress post via create_post_from_research
   → Save to Paper Store for future reference

Paper Store Integration (on request)

When explicitly asked to persist research:

paper_store_write {
  collection: "research-reports"
  id: "topic-slug"
  title: "Research: [Topic]"
  connection_id: "conn_8srcad8zylhe"
  tags: ["deep-research", "topic-tag", "brand-tag"]
  body: {
    topic: "..."
    report: "..."
    key_findings: [...]
    sources: [...]
    researched_at: "YYYY-MM-DD"
  }
}

Critical Rules

  • Match depth to need — a brand overview doesn't need comprehensive. Save that for competitive analysis.
  • Always include sources — citations make research actionable and credible.
  • Use focus areas — they dramatically improve report quality by guiding the AI.
  • Check site content first — semantic_content_search prevents duplicating work already done.
  • Feed research into action — research without application is wasted. Every report should inform a decision, campaign, or piece of content.
  • Store when asked — persist to Paper Store only when the user requests it.

Common Mistakes

WRONG:
  ● Using deep_research for "What's 2+2?" (use web_search for quick facts)
  ● Running comprehensive depth for a 2-minute task
  ● Not specifying focus_areas (generic report, misses what you need)
  ● Researching without a purpose — no link to campaign, content, or decision
  ● Saving every research to Paper Store automatically

RIGHT:
  ✅ deep_research for multi-source, cited, structured reports
  ✅ web_search for quick fact checks
  ✅ standard depth for most marketing research tasks
  ✅ Specific focus_areas tied to what you'll do with the results
  ✅ Research → insight → action chain
  ✅ Paper Store only when explicitly requested

What This Skill Does NOT Cover

  • Quick fact-checking — use design-web-research for fast lookups via web_search or brave_web_search.
  • Product-specific research — use design-product-research for structured SKU/catalog investigations via research_product.
  • Content writing — use design-content-research to convert research into WordPress draft posts via create_post_from_research.
  • Campaign planning — use design-campaign-orchestration to apply research insights to campaign themes and calendars.
  • SEO implementation — use design-seo-content to apply research keywords to product/category pages.
  • Image or visual research — use analyze_image or design-image-generation for visual reference gathering.

Cross-references

  • Run design-web-research for quick web searches — use web_search or brave_web_search instead of deep_research.
  • Run design-product-research for structured product-specific research — use research_product.
  • Run design-content-research to convert research into WordPress drafts — use create_post_from_research.
  • Run design-campaign-orchestration to apply research insights to campaign planning.
  • Run design-seo-content to use research keywords in product and category pages.
  • Use paper_store_* with connection_id to persist research reports to specific sites.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

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。

nvdigitalsolutions/mcp-ai-wpoos72026年10月13日 更新

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

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。

nvdigitalsolutions/mcp-ai-wpoos72026年10月13日 更新

Control a headless browser to navigate URLs, click elements, fill forms, extract content from JavaScript-rendered pages, take screenshots, and automate end-to-end web 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。

nvdigitalsolutions/mcp-ai-wpoos72026年10月13日 更新

Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

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。

nvdigitalsolutions/mcp-ai-wpoos72026年10月13日 更新

Review code for quality, simplicity, and maintainability. Identifies unnecessary abstractions, duplicated logic, oversized functions, missing error handling, and naming issues — then fixes them automatically before presenting the result.

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。

nvdigitalsolutions/mcp-ai-wpoos72026年10月13日 更新

WooCommerce store operations through NV oOS Pro — product research, catalog cross-referencing, inventory lookups, and Shopify or Flowhub comparisons where integrations are configured.

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。

nvdigitalsolutions/mcp-ai-wpoos72026年10月13日 更新

nvdigitalsolutions のスキルをすべて見る

このスキルの問題を報告する