industry-research

When the user wants to conduct industry research, keyword research for a campaign, search demand analysis, intent mapping, audience research, or understand what people are searching for. Also use when the user mentions 'industry research,' 'keyword clusters,' 'search intent,' 'what are people looking for,' 'audience questions,' 'content gaps,' 'competitor keywords,' 'SERP analysis,' or 'research before campaign.' This skill orchestrates multi-tool deep research using Ahrefs, Firecrawl, and Exa to produce a comprehensive intelligence brief. For raw web scraping, see firecrawl-cli; for competitor analysis, see competitive-intelligence; for market sizing, see market-research.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "industry-research" with this command: npx skills add mariokarras/industry-research

Industry Research

You conduct deep, intent-driven industry research. The core question is "what are people looking for?" -- not "what are competitors doing?" Keyword intent, search demand, and real audience language are the primary signals. Competitor analysis serves the intent research by finding gaps in what's being served.

Before Starting

Check for product marketing context first: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Then determine:

  1. Client name -- Which client to research for
  2. Industry/market -- The market category and key services/products
  3. Seed keywords -- 5-8 starting keyword phrases reflecting core services
  4. Competitor URLs -- 3-5 known competitor websites to analyze
  5. Geographic focus -- Target region for keyword data (default: US)

If dispatched via cron or orchestrator with a specific client name, use the product-marketing-context for that client to derive seed keywords and competitors automatically.


Workflow

Step 1: Keyword Research (Ahrefs)

Use Ahrefs to gather keyword data. Try the Ahrefs MCP server first (if available via mcporter or MCP tools list). If MCP is not available, fall back to the Ahrefs REST API at https://api.ahrefs.com/v3 with Authorization: Bearer $AHREFS_API_KEY.

Regardless of access method, gather data from these endpoints/capabilities:

Keywords Explorer overview -- seed keywords (batch up to 10 per request) for volume, difficulty, traffic potential:

POST /keywords-explorer/overview
Body: { "keywords": ["seed1", "seed2", ...], "country": "us" }

Keywords Explorer matching terms -- for each seed keyword, find related keywords (limit: 100 results per seed):

POST /keywords-explorer/matching-terms
Body: { "keyword": "seed keyword", "country": "us", "limit": 100 }

Keywords Explorer related terms -- semantically similar keywords:

POST /keywords-explorer/related-terms
Body: { "keyword": "seed keyword", "country": "us", "limit": 100 }

Cluster results by topic (group keywords sharing the same parent topic or SERP overlap).

Classify each keyword's intent:

  • Informational -- how/what/why questions, guides, educational content
  • Transactional -- near me, cost, buy, hire, service, pricing queries

Rate limit: Max 60 requests/min. Budget cap: 15 API calls per research run.

If neither Ahrefs MCP nor AHREFS_API_KEY is available, skip this step and note "Ahrefs data unavailable -- no MCP server or API key configured" in the artifact. Continue with Firecrawl+Exa only.

Step 2: Audience Research (Firecrawl + Exa)

Use exa.js search to find Reddit threads, forum posts, Quora answers about the industry/problem space:

exa.js search "[industry] questions problems reddit" --num-results 10
exa.js search "[industry] advice forum" --num-results 10
exa.js search "site:reddit.com [service] experience" --num-results 10

Use firecrawl.js scrape to extract content from top 5 most relevant results:

firecrawl.js scrape --url "https://reddit.com/r/relevant-thread"

Extract:

  • Exact questions people ask
  • Pain points in their own words
  • Emotional language
  • Common objections

Cross-reference with Google's People Also Ask (search for each seed keyword via Exa and extract PAA-style questions):

exa.js search "[seed keyword] questions people also ask" --num-results 5

Step 3: Content Gap Analysis

For each top keyword cluster, use exa.js search to find what currently ranks:

exa.js search "[keyword]" --num-results 10

Use firecrawl.js scrape on top 3 ranking pages per cluster to analyze content depth:

firecrawl.js scrape --url "https://top-ranking-page.com/article"

Identify gaps:

  • Topics with search demand but weak/missing/outdated content from competitors
  • Flag underserved angles -- queries where top results are generic directories (Yelp, WebMD) rather than authoritative guides
  • Note city-specific opportunities if geographic focus applies

Step 4: Competitor Landscape

Use firecrawl.js map on each competitor URL to discover their site structure:

firecrawl.js map --url "https://competitor.com"

Use firecrawl.js scrape on their key pages (homepage, services, blog, pricing) -- max 5 pages per competitor:

firecrawl.js scrape --url "https://competitor.com/services"

Analyze:

  • Positioning/messaging
  • Content strategy (blog frequency, topics)
  • SEO approach (city pages, programmatic content)

If Ahrefs is available (MCP or API), use Site Explorer organic-keywords to see what keywords competitors rank for:

GET /site-explorer/organic-keywords?target=competitor.com&limit=50

Identify messaging patterns and gaps -- what positioning angles are unclaimed.

Step 5: Compile Artifact

Write the output to .agents/industry-research-{client}.md where {client} is the lowercase client name (e.g., allcare).

Use this artifact template:

# Industry Research: {Client Name}

*Client: {Client Full Name}*
*Last full refresh: YYYY-MM-DD*

## 1. Keyword Clusters & Intent Map

*Last researched: YYYY-MM-DD*

### Cluster: {Topic Name}
| Keyword | Monthly Volume | Difficulty | Intent | Traffic Potential |
|---------|---------------|------------|--------|-------------------|
| keyword phrase | X,XXX | XX | Informational/Transactional | X,XXX |

**Intent distribution:** X% informational, X% transactional
**Primary opportunities:** Summary of top keyword opportunities

## 2. Questions & Pain Points

*Last researched: YYYY-MM-DD*

### What people ask (from PAA, Reddit, forums)
- "Exact question from audience?" (volume: X,XXX)

### Pain points (exact audience language)
- "Verbatim quote from real person" -- Source (Reddit, forum, etc.)

## 3. Content Gaps & Opportunities

*Last researched: YYYY-MM-DD*

### Underserved angles
- **Gap description:** Why it matters and the opportunity

### What's ranking (and what's weak)
| Query | Top Result | Gap/Opportunity |
|-------|-----------|-----------------|
| search query | Current top result | What's missing or weak |

## 4. Competitor Landscape

*Last researched: YYYY-MM-DD*

### Who ranks for our keywords
| Competitor | Ranks For | Positioning | Content Strategy |
|-----------|-----------|-------------|------------------|
| Competitor name | Key keywords | How they position | Blog, city pages, etc. |

### Messaging patterns
- Competitor: "Their messaging angle" -- framing type
- **Gap:** Unclaimed positioning angle

Target artifact size: 3,000-5,000 words. Synthesize and distill -- do not dump raw scraped content.

Each section has its own Last researched: timestamp so consuming skills can verify recency.


Tips

  • Focus on intent, not just volume -- a 500-volume transactional keyword outperforms a 5,000-volume informational one for conversions
  • Capture exact audience language -- "my mom can barely get to the doctor" is more valuable than "transportation barriers to healthcare access"
  • Budget API calls carefully -- 15 Ahrefs calls per run, scrape selectively (use firecrawl.js map before scrape)
  • Keep the artifact scannable -- downstream skills read specific sections, not the whole document

Related Skills

  • competitive-intelligence -- For detailed competitor analysis (company-level deep dives)
  • market-research -- For market sizing, TAM/SAM/SOM, and industry trends
  • firecrawl-cli -- For raw Firecrawl scraping (detailed tool documentation)
  • exa-company-research -- For raw Exa web search on specific companies
  • product-marketing-context -- For foundational product/service context that feeds into research

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Research

Wikipedia Publisher

Draft, review, de-risk, and publish Wikipedia or Wikidata content with a bias toward policy-safe workflow. Use when creating or editing encyclopedia articles...

Registry SourceRecently Updated
Research

Cg Paper Writing

Academic paper writing skill for 3D vision, computer graphics, CAD, and 3D understanding. Covers NeRF, 3D Gaussian Splatting, multi-view stereo, SLAM, point...

Registry SourceRecently Updated
Research

媒体广告流量分析

查询广告投放流量分布与趋势的数据分析技能。支持按行业、地域、媒体(OTT/移动端)、目标受众等多维度分析广告曝光数据,适用于媒体策略评估、竞品投放监测、行业广告趋势研究等场景。

Registry SourceRecently Updated
256Profile unavailable
Research

职场罗盘-用于面试者提前面试和公司背调,以及模拟面试;Your Guide for Interview Prep, Company Research, and Mock Interviews

职场罗盘 by Barry — 一站式求职辅助 Skill。整合简历解析优化、公司调研(就业向)、同城职位搜索、模拟面试四大模块。输入个人信息/简历,自动生成简历优化方向、公司调研报告、招聘表单,并可进行模拟面试。

Registry SourceRecently Updated
1260Profile unavailable