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Use when the user asks to: research keywords, analyze search volume\u002FCPC\u002Fcompetition, find keyword suggestions, check keyword difficulty, analyze competitors, get trending topics, do YouTube SEO research, or optimize landing page keywords. Requires a DataForSEO API account and credentials in .env file.","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fadamkristopher\u002Fseo-dataforseo\u002FSKILL.md",[17,22,25,28],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000019","营销推广",{"categoryNo":26,"categoryName":27,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":29,"categoryName":30,"taxonomyType":31,"taxonomyTypeDesc":32},"01JBSEEDCAT000000000000035","市场营销","PROFESSION","适用职业",[34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53],"seo","seo dataforseo","check","serp analysis","keyword research","competitor analysis","optimize","do","youtube","use","landing","research","find","page","analyze","api","credentials","analysis","file","search","2026-11-10 10:12:30",false,"---\nname: seo-dataforseo\ndescription: \"SEO keyword research using the DataForSEO API. Perform keyword analysis, YouTube keyword research, competitor analysis, SERP analysis, and trend tracking. Use when the user asks to: research keywords, analyze search volume\u002FCPC\u002Fcompetition, find keyword suggestions, check keyword difficulty, analyze competitors, get trending topics, do YouTube SEO research, or optimize landing page keywords. Requires a DataForSEO API account and credentials in .env file.\"\n---\n\n# SEO Keyword Research (DataForSEO)\n\n## Setup\n\nInstall dependencies:\n\n```bash\npip install -r scripts\u002Frequirements.txt\n```\n\nConfigure credentials by creating a `.env` file in the project root:\n\n```\nDATAFORSEO_LOGIN=your_email@example.com\nDATAFORSEO_PASSWORD=your_api_password\n```\n\nGet credentials from: https:\u002F\u002Fapp.dataforseo.com\u002Fapi-access\n\n## Quick Start\n\n| User says | Function to call |\n|-----------|-----------------|\n| \"Research keywords for [topic]\" | `keyword_research(\"topic\")` |\n| \"YouTube keyword data for [idea]\" | `youtube_keyword_research(\"idea\")` |\n| \"Analyze competitor [domain.com]\" | `competitor_analysis(\"domain.com\")` |\n| \"What's trending?\" | `trending_topics()` |\n| \"Keyword analysis for [list]\" | `full_keyword_analysis([\"kw1\", \"kw2\"])` |\n| \"Landing page keywords for [topic]\" | `landing_page_keyword_research([\"kw1\"], \"competitor.com\")` |\n\nExecute functions by importing from `scripts\u002Fmain.py`:\n\n```python\nimport sys\nfrom pathlib import Path\nsys.path.insert(0, str(Path(\"scripts\")))\nfrom main import *\n\nresult = keyword_research(\"AI website builders\")\n```\n\n## Workflow Pattern\n\nEvery research task follows three phases:\n\n### 1. Research\nRun API functions. Each function call hits the DataForSEO API and returns structured data.\n\n### 2. Auto-Save\nAll results automatically save as timestamped JSON files to `results\u002F{category}\u002F`. File naming pattern: `YYYYMMDD_HHMMSS__operation__keyword__extra_info.json`\n\n### 3. Summarize\nAfter research, read the saved JSON files and create a markdown summary in `results\u002Fsummary\u002F` with data tables, ranked opportunities, and strategic recommendations.\n\n## High-Level Functions\n\nThese are the primary functions in `scripts\u002Fmain.py`. Each orchestrates multiple API calls for a complete research workflow.\n\n| Function | Purpose | What it gathers |\n|----------|---------|----------------|\n| `keyword_research(keyword)` | Single keyword deep-dive | Overview, suggestions, related keywords, difficulty |\n| `youtube_keyword_research(keyword)` | YouTube content research | Overview, suggestions, YouTube SERP rankings, YouTube trends |\n| `landing_page_keyword_research(keywords, competitor_domain)` | Landing page SEO | Overview, intent, difficulty, SERP analysis, competitor keywords |\n| `full_keyword_analysis(keywords)` | Strategic content planning | Overview, difficulty, intent, keyword ideas, historical volume, Google Trends |\n| `competitor_analysis(domain, keywords)` | Competitor intelligence | Domain keywords, Google Ads keywords, competitor domains |\n| `trending_topics(location_name)` | Current trends | Currently trending searches |\n\n### Parameters\n\nAll functions accept an optional `location_name` parameter (default: \"United States\"). Most functions also have boolean flags to skip specific sub-analyses (e.g., `include_suggestions=False`).\n\n### Individual API Functions\n\nFor granular control, import specific functions from the API modules. See [references\u002Fapi-reference.md](references\u002Fapi-reference.md) for the complete list of 25 API functions with parameters, limits, and examples.\n\n## Results Storage\n\nResults auto-save to `results\u002F` with this structure:\n\n```\nresults\u002F\n├── keywords_data\u002F    # Search volume, CPC, competition\n├── labs\u002F             # Suggestions, difficulty, intent\n├── serp\u002F             # Google\u002FYouTube rankings\n├── trends\u002F           # Google Trends data\n└── summary\u002F          # Human-readable markdown summaries\n```\n\n### Managing Results\n\n```python\nfrom core.storage import list_results, load_result, get_latest_result\n\n# List recent results\nfiles = list_results(category=\"labs\", limit=10)\n\n# Load a specific result\ndata = load_result(files[0])\n\n# Get most recent result for an operation\nlatest = get_latest_result(category=\"labs\", operation=\"keyword_suggestions\")\n```\n\n### Utility Functions\n\n```python\nfrom main import get_recent_results, load_latest\n\n# List recent files across all categories\nfiles = get_recent_results(limit=10)\n\n# Load latest result for a category\ndata = load_latest(\"labs\", \"keyword_suggestions\")\n```\n\n## Creating Summaries\n\nAfter running research, create a markdown summary document in `results\u002Fsummary\u002F`. Include:\n\n- **Data tables** with volumes, CPC, competition, difficulty\n- **Ranked lists** of opportunities (sorted by volume or opportunity score)\n- **SERP analysis** showing what currently ranks\n- **Recommendations** for content strategy, titles, tags\n\nName the summary file descriptively (e.g., `results\u002Fsummary\u002Fai-tools-keyword-research.md`).\n\n## Tips\n\n1. **Be specific** — \"Get keyword suggestions for 'AI website builders'\" works better than \"research AI stuff\"\n2. **Request summaries** — Always create a summary document after research, named specifically\n3. **Batch related keywords** — Pass multiple related keywords at once for comparison\n4. **Specify the goal** — \"for a YouTube video\" vs \"for a landing page\" changes which data matters most\n5. **Ask for competition analysis** — \"Show me what videos are ranking\" helps identify content gaps\n\n## Defaults\n\n- **Location**: United States (code 2840)\n- **Language**: English\n- **API Limits**: 700 keywords for volume\u002Foverview, 1000 for difficulty\u002Fintent, 5 for trends, 200 for keyword ideas\n","# SEO Keyword Research (DataForSEO)\n\n## Setup\n\nInstall dependencies:\n\n```bash\npip install -r scripts\u002Frequirements.txt\n```\n\nConfigure credentials by creating a `.env` file in the project root:\n\n```\nDATAFORSEO_LOGIN=your_email@example.com\nDATAFORSEO_PASSWORD=your_api_password\n```\n\nGet credentials from: https:\u002F\u002Fapp.dataforseo.com\u002Fapi-access\n\n## Quick Start\n\n| User says | Function to call |\n|-----------|-----------------|\n| \"Research keywords for [topic]\" | `keyword_research(\"topic\")` |\n| \"YouTube keyword data for [idea]\" | `youtube_keyword_research(\"idea\")` |\n| \"Analyze competitor [domain.com]\" | `competitor_analysis(\"domain.com\")` |\n| \"What's trending?\" | `trending_topics()` |\n| \"Keyword analysis for [list]\" | `full_keyword_analysis([\"kw1\", \"kw2\"])` |\n| \"Landing page keywords for [topic]\" | `landing_page_keyword_research([\"kw1\"], \"competitor.com\")` |\n\nExecute functions by importing from `scripts\u002Fmain.py`:\n\n```python\nimport sys\nfrom pathlib import Path\nsys.path.insert(0, str(Path(\"scripts\")))\nfrom main import *\n\nresult = keyword_research(\"AI website builders\")\n```\n\n## Workflow Pattern\n\nEvery research task follows three phases:\n\n### 1. Research\nRun API functions. Each function call hits the DataForSEO API and returns structured data.\n\n### 2. Auto-Save\nAll results automatically save as timestamped JSON files to `results\u002F{category}\u002F`. File naming pattern: `YYYYMMDD_HHMMSS__operation__keyword__extra_info.json`\n\n### 3. Summarize\nAfter research, read the saved JSON files and create a markdown summary in `results\u002Fsummary\u002F` with data tables, ranked opportunities, and strategic recommendations.\n\n## High-Level Functions\n\nThese are the primary functions in `scripts\u002Fmain.py`. Each orchestrates multiple API calls for a complete research workflow.\n\n| Function | Purpose | What it gathers |\n|----------|---------|----------------|\n| `keyword_research(keyword)` | Single keyword deep-dive | Overview, suggestions, related keywords, difficulty |\n| `youtube_keyword_research(keyword)` | YouTube content research | Overview, suggestions, YouTube SERP rankings, YouTube trends |\n| `landing_page_keyword_research(keywords, competitor_domain)` | Landing page SEO | Overview, intent, difficulty, SERP analysis, competitor keywords |\n| `full_keyword_analysis(keywords)` | Strategic content planning | Overview, difficulty, intent, keyword ideas, historical volume, Google Trends |\n| `competitor_analysis(domain, keywords)` | Competitor intelligence | Domain keywords, Google Ads keywords, competitor domains |\n| `trending_topics(location_name)` | Current trends | Currently trending searches |\n\n### Parameters\n\nAll functions accept an optional `location_name` parameter (default: \"United States\"). Most functions also have boolean flags to skip specific sub-analyses (e.g., `include_suggestions=False`).\n\n### Individual API Functions\n\nFor granular control, import specific functions from the API modules. See [references\u002Fapi-reference.md](references\u002Fapi-reference.md) for the complete list of 25 API functions with parameters, limits, and examples.\n\n## Results Storage\n\nResults auto-save to `results\u002F` with this structure:\n\n```\nresults\u002F\n├── keywords_data\u002F    # Search volume, CPC, competition\n├── labs\u002F             # Suggestions, difficulty, intent\n├── serp\u002F             # Google\u002FYouTube rankings\n├── trends\u002F           # Google Trends data\n└── summary\u002F          # Human-readable markdown summaries\n```\n\n### Managing Results\n\n```python\nfrom core.storage import list_results, load_result, get_latest_result\n\n# List recent results\nfiles = list_results(category=\"labs\", limit=10)\n\n# Load a specific result\ndata = load_result(files[0])\n\n# Get most recent result for an operation\nlatest = get_latest_result(category=\"labs\", operation=\"keyword_suggestions\")\n```\n\n### Utility Functions\n\n```python\nfrom main import get_recent_results, load_latest\n\n# List recent files across all categories\nfiles = get_recent_results(limit=10)\n\n# Load latest result for a category\ndata = load_latest(\"labs\", \"keyword_suggestions\")\n```\n\n## Creating Summaries\n\nAfter running research, create a markdown summary document in `results\u002Fsummary\u002F`. Include:\n\n- **Data tables** with volumes, CPC, competition, difficulty\n- **Ranked lists** of opportunities (sorted by volume or opportunity score)\n- **SERP analysis** showing what currently ranks\n- **Recommendations** for content strategy, titles, tags\n\nName the summary file descriptively (e.g., `results\u002Fsummary\u002Fai-tools-keyword-research.md`).\n\n## Tips\n\n1. **Be specific** — \"Get keyword suggestions for 'AI website builders'\" works better than \"research AI stuff\"\n2. **Request summaries** — Always create a summary document after research, named specifically\n3. **Batch related keywords** — Pass multiple related keywords at once for comparison\n4. **Specify the goal** — \"for a YouTube video\" vs \"for a landing page\" changes which data matters most\n5. **Ask for competition analysis** — \"Show me what videos are ranking\" helps identify content gaps\n\n## Defaults\n\n- **Location**: United States (code 2840)\n- **Language**: English\n- **API Limits**: 700 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Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[195],{"categoryNo":196,"categoryName":197,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[199,49,200,48,201,202,203,204,205,206,207,208,209,210,211,212,213,177,43],"dilemm ai","arena","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking",{"skillNo":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":218,"categories":219,"keywords":221,"publishedAt":54},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, or submitting paper reviews via API at http:\u002F\u002F150.158.152.82:8000.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Fweak-accept\u002FSKILL.md",[220],{"categoryNo":26,"categoryName":27,"taxonomyType":20,"taxonomyTypeDesc":21},[222,223,224,225,226,227,228,173,229,212,43,230,49,231,232],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","fetch","read","http","via",{"skillNo":234,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":235,"categories":236,"keywords":238,"publishedAt":54},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[237],{"categoryNo":26,"categoryName":27,"taxonomyType":20,"taxonomyTypeDesc":21},[225,224,223,222,232,227,228,173,226,212,43,229,230,49,231],{"skillNo":240,"name":241,"nameZh":6,"description":242,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":243,"categories":244,"keywords":245,"publishedAt":54},"01M6G8HM95Y64JNVFC2HN4E2BG","git-summary","Get a quick summary of the current Git repository including status, recent commits, branches, and contributors.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzweack\u002Fgit-summary\u002FSKILL.md",[],[246,247,248,249,250,251,252,253,254,255,256,257,258],"git","summary","git summary","commits","repository","win32","status","linux","contributors","true","quick","get","branches",{"skillNo":260,"name":261,"nameZh":6,"description":262,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":263,"categories":264,"keywords":269,"publishedAt":54},"01M6G8HGEGF05CNEJCGVYFSC4R","agent-constitution","Interact with AgentConstitution governance contracts on Base Sepolia. Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[265,266],{"categoryNo":196,"categoryName":197,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":267,"categoryName":268,"taxonomyType":31,"taxonomyTypeDesc":32},"01JBSEEDCAT000000000000037","律师与法务",[270,271,272,273,173,274,275,59,276,230,36,277,278,279,280,186,281,282,283],"agent constitution","constitution","contracts","tree","query","base","log","Rules","projects","compliance","actions","state","governance","github"]