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Domain Keyword Intelligence - Find the Registration Trends

by @abtdomain

Discover domain investment opportunities from emerging keyword spikes. Filters junk signals from real multi-party market activity using registration profilin...

Versionv1.0.3
Downloads1,926
Stars⭐ 1
TERMINAL
clawhub install domain-keyword-intelligence

πŸ“– About This Skill


name: domain-keyword-intelligence description: Discover domain investment opportunities from emerging keyword spikes. Filters junk signals from real multi-party market activity using registration profiling, catalyst research, and NRDS position analysis. Powered by DomainKits MCP. homepage: https://domainkits.com/mcp metadata: {"openclaw":{"emoji":"πŸ“ˆ","primaryEnv":"DOMAINKITS_API_KEY"}}


Domain Keyword Intelligence

Spot domain market trends before they peak. This skill transforms raw keyword spike data into actionable investment signals by separating real multi-party demand from single-operator noise.

Why This Skill?

Raw keywords_trends(emerging) data typically returns 50-100 keywords β€” most are junk. This skill's value is extracting signal from noise:

  • Profile every spike β€” Is it "one person" bulk-registering, or a genuine multi-party market?
  • Research the catalyst β€” What news, product launch, or domain sale is driving registrations?
  • Analyze positioning β€” How are registrants combining this keyword? Where are the gaps?
  • Setup

    Prerequisites

    This skill requires the DomainKits MCP connection and access to web_search.

  • DomainKits MCP: Provides keywords_trends, nrds, and other domain intelligence tools
  • web_search: Platform built-in tool, used for mandatory catalyst research
  • No additional API keys or environment variables are needed beyond the DomainKits connection.

    Option 1: Claude.ai / OpenClaw

    Connect DomainKits via Settings β†’ Connectors. The platform handles authentication automatically.

    Option 2: Claude Code / MCP Config

    Add to your MCP config:

    {
      "mcpServers": {
        "domainkits": {
          "baseUrl": "https://api.domainkits.com/v1/mcp"
        }
      }
    }
    

    With API key (for higher limits):

    {
      "mcpServers": {
        "domainkits": {
          "baseUrl": "https://api.domainkits.com/v1/mcp",
          "headers": {
            "X-API-Key": "$env:DOMAINKITS_API_KEY"
          }
        }
      }
    }
    

    Get your API key at https://domainkits.com

    Tools Used

    This skill orchestrates the following tools:

  • keywords_trends β€” Fetch emerging keyword spikes (DomainKits MCP)
  • nrds β€” Search newly registered domains by keyword and position (DomainKits MCP)
  • web_search β€” Investigate catalysts behind registration spikes (platform built-in)
  • Optional follow-up tools (user-driven):

  • deleted β€” Recently dropped domains
  • expired β€” Backorderable domains
  • aged β€” Domains listed for sale
  • keyword_intel β€” Deep keyword analysis
  • domain_generator β€” Creative name ideas
  • Instructions

    Step 1: Fetch Emerging Keyword Data

    Call keywords_trends(type="emerging") to get keywords with registration volume spikes in the last 7-14 days. The tool returns per-keyword data including registration volume (w3/w4), com_ratio, forsale_pct, might_use_count, top_registrar, and other dimensions needed for Step 2 analysis.

    Step 2: Multi-Dimensional Profile Analysis (Core Logic)

    #### How the domain market works

    The domain market is a multi-party ecosystem. After registering a domain, a person can only do one of three things with it:

    1. Sell it β€” list on aftermarket platforms and wait for buyers. This is investor behavior. Their presence shows up in forsale_pct.

    2. Use it (maybe) β€” point it to infrastructure (Cloudflare, AWS, Vercel). Their presence shows up in might_use_count β€” but this only indicates the domain was configured beyond default parking, not that it is genuinely in use. It could be a real project or a site farm. Only meaningful when registrar distribution is diverse.

    3. Unknown β€” the domain sits on default NS, neither listed for sale nor pointed to any infrastructure. The registrant's intent is unclear. This is the remainder after subtracting forsale and might_use from total registrations.

    These three states account for every registered domain. Like any financial market, a healthy keyword market requires liquidity β€” active trading, not just ownership.

    forsale_pct is the market's trading volume. If forsale is very low, market participation is low β€” this is not a healthy market signal. A keyword with high com_ratio, dispersed registrars, and high might_use_count but near-zero forsale has registrations but no market.

    Two hard rules:

  • If forsale is below 3%, discard. Do not explain it away with "end-user driven" or "terminal demand" β€” low forsale means low market participation, period.
  • Never make recommendations or judgments without data. Labels like "NFL-related", "Chinese pinyin demand", "gaming keyword" are speculation unless confirmed by web_search. If you have not searched, do not guess. Output data only, not narratives. Potential healthy keywords must be verified through NRDS registration analysis (Step 3) before being presented as opportunities.
  • Two cross-cutting dimensions apply to all three participant types:

  • com_ratio β€” the "blue chip ratio." High com_ratio means participants are investing in .com β€” the most expensive TLD. Low com_ratio means activity is concentrated on cheap TLDs.
  • top_registrar.pct β€” the "exchange concentration." Registrars are channels, not identity labels. High concentration (e.g., above 80%) on a single registrar reduces confidence that many independent parties are involved. A real multi-party market almost always shows distributed registrar usage.
  • The core question for every keyword is: Is this data from "one person" or "a market"?

    When analyzing a keyword, check whether each participant type is present. When a type is absent, ask why β€” the answer tells you what's really happening. When a type overwhelmingly dominates, ask whether that makes sense for a real market or whether it points to a single operator.

    #### Filtering Process

    1. Calculate w4/w3 growth rate for each keyword 2. Profile each keyword across all dimensions β€” check whether all three participant types are present and whether the two cross-cutting dimensions are reasonable 3. Classify as junk (single operator or missing participant roles) or healthy (genuine multi-party market) 4. Sort healthy keywords by w4/w3 growth rate 5. Take Top 5-8 for deep analysis

    #### Output Format

    Summarize filtering results concisely:

  • N total emerging keywords
  • Excluded X junk signals β€” each in under 10 words (e.g., "ethereum: single registrar, all forsale, no .com")
  • Identified Z healthy market signals
  • List healthy keywords with key profile data:

    llm β€” W3: 794 β†’ W4: 979 (↑23%)
      com_ratio: 82.6% | forsale: 36.8% | might_use: 63 | top_registrar: Unstoppable Domains 29.7%
      Profile: Multi-party participation, .com dominant, mix of investment and usage. Healthy signal.
    

    Step 2.5: Catalyst Research (web_search MANDATORY)

    For each healthy keyword identified in Step 2, use web_search to investigate what is driving the registration spike. Domain registration spikes are predominantly driven by technology and internet industry events β€” product launches, AI model releases, platform announcements, viral open-source projects, regulatory changes, major acquisitions, or high-profile domain sales.

    Profile analysis tells you WHETHER a signal is healthy. Catalyst research tells you WHY β€” and "why" determines whether the opportunity is worth pursuing.

    For each healthy keyword, search with a technology lens. Prioritize the last 3 days β€” emerging spikes are almost always driven by very recent events. If nothing is found within 3 days, extend to 10 days maximum: 1. {keyword} news β€” look for product launches, funding rounds, open-source projects, platform announcements, regulatory changes 2. {keyword} domain sold price β€” a high-value domain sale is the single strongest catalyst for registration spikes

    #### Output: Catalyst Verification Table

    Present catalyst findings as this table. The Source column must contain a real URL from web_search results. No URL = keyword does not appear in the table. Do not substitute with training data.

    | Keyword | W4 | forsale% | Catalyst | Source |
    |---------|-----|---------|----------|--------|
    | molt    | 576 | 17.2%   | OpenClaw/Moltbot AI agent project | CNBC |
    | nemo    | 374 | 29.7%   | Nvidia NeMo/NemoClaw, GTC 2026 | TradingView |
    | llm     | 768 | 28.6%   | PrivateLLM.com sold $250K | DomainInvesting |
    

    Rules:

  • Source = actual URL from web_search. Not training data.
  • No catalyst found AND no URL β†’ keyword excluded from table. Note "no catalyst identified" in the filtering summary and move on.
  • forsale < 3% β†’ never reaches this table (killed at Step 2).
  • Only keywords in this table proceed to Step 3.
  • Step 3: NRDS Registration Position Analysis

    This step bridges "macro trend" to "micro execution."

    For each healthy keyword, call nrds to examine actual registration patterns:

    nrds(keyword="", position="start", tld="com", no_hyphen="true", sort="reg_date_desc", days_range="0-10")
    nrds(keyword="", position="end", tld="com", no_hyphen="true", sort="reg_date_desc", days_range="0-10")
    

    #### Analysis Points

    1. Position distribution: - position=start (e.g., llmtools.com, llmagent.ai) β†’ keyword as category anchor - position=end (e.g., myllm.com, bestllm.io) β†’ keyword as modifier - Comparing volumes reveals how the market positions this keyword

    2. Popular combinations: Extract high-frequency combination words from registrations. E.g., llm + agent, llm + chat, llm + tools. These represent the market's view on the keyword's most valuable applications

    3. Registration quality: - Length distribution (short names taken = fierce competition; short names available = window open) - period (registration term): 6+ years = serious project, 1 year = speculative trial - prefix_tld_count: high = prefix registered across many TLDs = strong recognition

    4. Investor vs end-user behavior: - NS: afternic.com / sedo.com / thisdomain.forsale = investor listing - NS: cloudflare / aws / vercel = domain configured for use (could be real project or site farm β€” check if naming patterns are diverse or template-like) - Ratio reveals speculation phase vs adoption phase

    #### Output Format

    llm β€” NRDS Registration Analysis
      position=start: 287 domains (llmtools, llmagent, llmchat, llmcode...)
      position=end: 143 domains (myllm, bestllm, openllm, smartllm...)
      Popular combos: agent (42), tools (28), chat (23), code (19), hub (15)
      Market direction: Heavy llm+agent combinations suggest bullish sentiment on LLM Agent space
      Quality: Short domains (<10 char) largely taken, 10-15 char range still has room
    

    Step 4: Next Steps

    After presenting the trend analysis and NRDS findings, let the user know they can use DomainKits' other tools to explore domain opportunities for any keyword that interests them β€” such as deleted for recently dropped domains, expired for backorderable domains, aged for domains listed for sale, keyword_intel for deep keyword analysis, or domain_generator for creative name ideas. Let the user choose which keywords and directions to pursue.

    Output Rules

  • Language: Follow user's language
  • Concise: Profile judgments in one sentence. Skip junk quickly, expand on healthy signals
  • Data-driven: Every judgment cites specific numbers
  • Honest: No catalyst found β†’ say "cause unidentified" β€” never fabricate
  • Quota-aware: Step 3 consumes many tool calls. Show Step 2 results first and let user pick 2-3 keywords before continuing
  • Access Tiers

    Guest users can use this skill with limited daily search quota. Register a free account at https://domainkits.com to unlock higher search limits and access to all tools.

    Privacy

  • Works without API key (guest tier)
  • No user data stored by this skill
  • DomainKits: GDPR compliant, memory OFF by default
  • Links

  • DomainKits: https://domainkits.com/mcp
  • GitHub: https://github.com/ABTdomain/domainkits-mcp
  • Contact: info@domainkits.com
  • Developed by: https://abtdomain.com
  • βš™οΈ Configuration

    Prerequisites

    This skill requires the DomainKits MCP connection and access to web_search.

  • DomainKits MCP: Provides keywords_trends, nrds, and other domain intelligence tools
  • web_search: Platform built-in tool, used for mandatory catalyst research
  • No additional API keys or environment variables are needed beyond the DomainKits connection.

    Option 1: Claude.ai / OpenClaw

    Connect DomainKits via Settings β†’ Connectors. The platform handles authentication automatically.

    Option 2: Claude Code / MCP Config

    Add to your MCP config:

    {
      "mcpServers": {
        "domainkits": {
          "baseUrl": "https://api.domainkits.com/v1/mcp"
        }
      }
    }
    

    With API key (for higher limits):

    {
      "mcpServers": {
        "domainkits": {
          "baseUrl": "https://api.domainkits.com/v1/mcp",
          "headers": {
            "X-API-Key": "$env:DOMAINKITS_API_KEY"
          }
        }
      }
    }
    

    Get your API key at https://domainkits.com