{
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  "item": {
    "slug": "afrexai-lead-hunter",
    "name": "AfrexAI Lead Hunter Pro",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/1kalin/afrexai-lead-hunter",
    "canonicalUrl": "https://clawhub.ai/1kalin/afrexai-lead-hunter",
    "targetPlatform": "OpenClaw"
  },
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    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=afrexai-lead-hunter",
    "sourcePlatform": "tencent",
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    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
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      "README.md",
      "SKILL.md"
    ],
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      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
    ],
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      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
      "steps": [
        "Download the package from Yavira.",
        "Extract it into a folder your agent can access.",
        "Paste one of the prompts below and point your agent at the extracted folder."
      ],
      "prompts": [
        {
          "label": "New install",
          "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete."
        },
        {
          "label": "Upgrade existing",
          "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
        }
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      "expiresAt": "2026-04-30T16:43:11.935Z",
      "httpStatus": 200,
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        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/afrexai-lead-hunter"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    },
    "downloadPageUrl": "https://openagent3.xyz/downloads/afrexai-lead-hunter",
    "agentPageUrl": "https://openagent3.xyz/skills/afrexai-lead-hunter/agent",
    "manifestUrl": "https://openagent3.xyz/skills/afrexai-lead-hunter/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/afrexai-lead-hunter/agent.md"
  },
  "agentAssist": {
    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "Download the package from Yavira.",
      "Extract it into a folder your agent can access.",
      "Paste one of the prompts below and point your agent at the extracted folder."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
      }
    ]
  },
  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "AfrexAI Lead Hunter Pro",
        "body": "Turn your AI agent into a full B2B sales development machine. Discovery → Enrichment → Scoring → Outreach → CRM. Zero manual work."
      },
      {
        "title": "Architecture",
        "body": "DEFINE ICP ──▶ DISCOVER ──▶ ENRICH ──▶ SCORE ──▶ SEGMENT ──▶ OUTREACH ──▶ CRM\n    │              │            │          │          │            │          │\n    ▼              ▼            ▼          ▼          ▼            ▼          ▼\n Persona      Multi-source  Email+Phone  ICP fit   Tier A/B/C  Sequences  Pipeline\n Builder      Web Research  Company Data  Intent    Campaigns   Templates  Tracking"
      },
      {
        "title": "Phase 1: Define Your Ideal Customer Profile (ICP)",
        "body": "Before hunting, know WHO you're hunting. Answer these:"
      },
      {
        "title": "Company-Level ICP",
        "body": "# Copy and customize this ICP template\ncompany:\n  industries: [SaaS, fintech, legal-tech, prop-tech]\n  employee_range: [50, 500]        # sweet spot for AI adoption\n  revenue_range: [$5M, $100M]      # can afford $120K+ contracts\n  funding_stage: [Series A, Series B, Series C]\n  tech_signals:                     # tools that indicate AI readiness\n    positive: [Salesforce, HubSpot, Snowflake, AWS, Python]\n    negative: [no-website, wordpress-only]\n  geography: [US, UK, Canada, Australia]\n  pain_signals:                     # problems they're likely facing\n    - \"manual data entry\"\n    - \"compliance overhead\"\n    - \"scaling operations\"\n    - \"document processing\""
      },
      {
        "title": "Buyer Persona",
        "body": "persona:\n  titles: [CEO, CTO, COO, VP Operations, Head of Innovation, Director of IT]\n  seniority: [C-Suite, VP, Director]\n  decision_authority: true          # can sign $50K+ without board approval\n  linkedin_activity:                # signals they're actively looking\n    - posts about AI/automation\n    - comments on digital transformation content\n    - recently changed roles (first 90 days = buying window)\n  anti-signals:                     # skip these\n    - \"consultant\" in title (not buyers)\n    - company < 10 employees (no budget)\n    - already has AI vendor (check for competitors in their stack)"
      },
      {
        "title": "Scoring Weights",
        "body": "scoring:\n  icp_company_match: 30             # how well company matches\n  icp_persona_match: 20             # right title + seniority\n  intent_signals: 25                # actively looking for solutions\n  engagement_recency: 15            # recent activity online\n  timing_bonus: 10                  # new role, funding round, hiring\n  \n  thresholds:\n    tier_a: 80                      # hot — outreach immediately\n    tier_b: 60                      # warm — nurture sequence\n    tier_c: 40                      # cool — add to newsletter\n    disqualify: below 40            # don't waste time"
      },
      {
        "title": "Source Priority Matrix",
        "body": "SourceBest ForHow To SearchData QualityCostWeb SearchAny industry\"[industry] companies\" site:linkedin.com/companyHighFreeGitHubDev tools, tech companiesSearch repos, org pages, contributor profilesHighFreeProduct HuntStartups, SaaSBrowse launches, upvoters (they're buyers too)MediumFreeIndustry ListsTargeted verticals\"Top 50 [industry] companies 2026\", Clutch, G2HighFreeJob BoardsHiring = growing = buying\"AI\" OR \"automation\" site:lever.co OR site:greenhouse.ioHighFreeCrunchbaseFunded startupsRecently funded companies in target verticalsHighFreemiumConference SpeakersActive industry leadersSpeaker lists from industry eventsVery HighFreePodcast GuestsThought leaders with budgetSearch \"[industry] podcast\" transcriptsHighFree"
      },
      {
        "title": "Discovery Search Templates",
        "body": "Find companies by pain signal:\n\n\"[industry]\" \"manual process\" OR \"time-consuming\" OR \"looking for solutions\" site:linkedin.com\n\nFind companies by hiring signal (they're growing = they're buying):\n\n\"[company type]\" \"hiring\" \"AI\" OR \"automation\" OR \"data\" site:linkedin.com/jobs\n\nFind recently funded companies (flush with cash):\n\n\"[industry]\" \"raises\" OR \"Series A\" OR \"funding\" OR \"investment\" 2026\n\nFind companies using competitor tools (ripe for switching):\n\n\"[competitor tool]\" \"alternative\" OR \"switching from\" OR \"replaced\"\n\nFind decision makers directly:\n\n\"[title]\" \"[industry]\" \"[city/region]\" site:linkedin.com/in"
      },
      {
        "title": "Discovery Workflow",
        "body": "FOR each search query:\n  1. Run web_search with the query\n  2. Extract company names + URLs from results\n  3. Deduplicate against existing leads\n  4. For each NEW company:\n     a. Visit company website → extract: industry, size estimate, tech signals\n     b. Search \"[company name] CEO\" OR \"[company name] founder\" → get decision maker\n     c. Search \"[company name] funding\" → get financial signals\n     d. Create lead record (see schema below)\n  5. Rate limit: 2-3 second delay between searches"
      },
      {
        "title": "Phase 3: Enrichment Engine",
        "body": "For each discovered lead, enrich with verified data:"
      },
      {
        "title": "Company Enrichment Checklist",
        "body": "Website — Load homepage, extract value prop, tech stack (check <meta> tags, JS frameworks)\n Employee Count — LinkedIn company page, Crunchbase, or website \"About\" page\n Revenue Estimate — Funding amount × 3-5x multiplier, or industry benchmarks\n Tech Stack — Check BuiltWith, Wappalyzer data, or job postings for tech mentions\n Recent News — Last 90 days: funding, launches, executive changes, partnerships\n Pain Indicators — Job postings mentioning problems you solve, blog posts about challenges\n Competitor Usage — Do they use a competitor? Which one? (Check G2 reviews, case studies)"
      },
      {
        "title": "Contact Enrichment Checklist",
        "body": "Full Name — First + Last from LinkedIn or company page\n Title — Current role (verify it matches your buyer persona)\n Email Pattern — Determine company pattern: first@, first.last@, firstlast@, f.last@\n Email Verification — Test pattern with known format, check MX records\n LinkedIn URL — Direct profile link\n Recent Activity — What have they posted/shared in last 30 days?\n Mutual Connections — Anyone in your network connected to them?\n Content Interests — What topics do they engage with? (Use for personalization)"
      },
      {
        "title": "Email Pattern Detection",
        "body": "Common patterns (test in order of likelihood):\n1. first.last@company.com     (most common, ~40%)\n2. first@company.com          (startups, ~25%)\n3. firstlast@company.com      (~15%)\n4. flast@company.com           (~10%)\n5. first_last@company.com     (~5%)\n6. last.first@company.com     (~3%)\n7. first.l@company.com        (~2%)\n\nVerification approach:\n- Check if company has public team page with email format\n- Look for email in GitHub commits from company domain\n- Check email format on Hunter.io or similar (if available)\n- Search \"[person name] email [company]\" \n- Check their personal website/blog for contact"
      },
      {
        "title": "Phase 4: Lead Scoring Algorithm",
        "body": "Score each lead 0-100 using this rubric:"
      },
      {
        "title": "Company Score (0-30 points)",
        "body": "SignalPointsHow to CheckIndustry matches ICP exactly+10Compare to ICP configEmployee count in sweet spot+5LinkedIn/websiteRevenue in target range+5Crunchbase/estimateLocated in target geography+3Website/LinkedInUses compatible tech stack+4Job posts, BuiltWithNo competitor currently+3Research, case studies"
      },
      {
        "title": "Persona Score (0-20 points)",
        "body": "SignalPointsHow to CheckTitle matches buyer persona+8LinkedInC-Suite or VP level+5LinkedInHas decision authority+4Title + company sizeActive on LinkedIn (posts monthly)+3LinkedIn activity"
      },
      {
        "title": "Intent Score (0-25 points)",
        "body": "SignalPointsHow to CheckRecently posted about relevant pain+8LinkedIn/TwitterCompany hiring for roles you'd replace+7Job boardsAttended relevant industry event+5Conference listsDownloaded competitor content+3Hard to verify, skip if unknownSearched for solution keywords+2Hard to verify, skip if unknown"
      },
      {
        "title": "Timing Score (0-15 points)",
        "body": "SignalPointsHow to CheckNew in role (< 90 days)+5LinkedIn start dateCompany just raised funding+4Crunchbase/newsEnd of quarter (budget flush)+3CalendarCompany growing fast (hiring surge)+3Job postings count"
      },
      {
        "title": "Engagement Score (0-10 points)",
        "body": "SignalPointsHow to CheckOpened previous email+4Email trackingVisited your website+3AnalyticsConnected on LinkedIn+2LinkedInReferred by someone+1CRM notes"
      },
      {
        "title": "Tier A (Score 80-100) — HOT LEADS",
        "body": "Action: Immediate personalized outreach\nSequence: 5-touch hyper-personalized campaign\nTimeline: Contact within 24 hours\nChannel: Email → LinkedIn → Phone (if available)\nTemplate: \"CEO-to-CEO\" or \"Specific Pain\" (see below)"
      },
      {
        "title": "Tier B (Score 60-79) — WARM LEADS",
        "body": "Action: Nurture sequence\nSequence: 7-touch value-first campaign  \nTimeline: Start within 48 hours\nChannel: Email → LinkedIn\nTemplate: \"Value Insight\" or \"Case Study\" (see below)"
      },
      {
        "title": "Tier C (Score 40-59) — COOL LEADS",
        "body": "Action: Add to newsletter + long-term nurture\nSequence: Monthly value content\nTimeline: Bi-weekly touchpoints\nChannel: Email only\nTemplate: \"Industry Report\" or \"Educational\" (see below)"
      },
      {
        "title": "Template 1: The Specific Pain (Tier A)",
        "body": "Email 1 — Day 0 (The Hook)\n\nSubject: [specific pain point] at [Company]?\n\nHi [First Name],\n\nNoticed [Company] is [specific observation — hiring for X role / posted about Y challenge / using Z tool].\n\nThat usually means [pain point they're likely feeling].\n\nWe built [solution] that [specific result with number]. [Client name] cut their [metric] by [X%] in [timeframe].\n\nWorth a 15-min call to see if it fits [Company]?\n\n[Your name]\n\nEmail 2 — Day 3 (The Proof)\n\nSubject: Re: [original subject]\n\n[First Name] — quick follow-up.\n\nHere's exactly what we did for [similar company]: [1-sentence case study with specific numbers].\n\n[Link to case study or calculator]\n\nHappy to walk through how this maps to [Company].\n\n[Your name]\n\nEmail 3 — Day 7 (The Angle)\n\nSubject: [industry trend] + [Company]\n\n[First Name],\n\n[Industry trend or stat that's relevant]. Companies like [Company] are [what smart companies are doing about it].\n\nWe help [type of company] [specific outcome]. Takes about [timeframe] to see results.\n\nOpen to a quick chat this week?\n\n[Your name]\n\nEmail 4 — Day 14 (The Breakup)\n\nSubject: Should I close your file?\n\n[First Name],\n\nI've reached out a few times — totally understand if the timing isn't right.\n\nIf [pain point] becomes a priority, here's a [free resource] that might help: [link]\n\nEither way, I'll stop filling your inbox. Just reply \"yes\" if you'd like to chat sometime.\n\n[Your name]"
      },
      {
        "title": "Template 2: The Value-First (Tier B)",
        "body": "Email 1 — Lead with insight, not a pitch\n\nSubject: [number] [industry] companies are doing [thing] wrong\n\nHi [First Name],\n\nWe analyzed [X] companies in [industry] and found that [surprising insight].\n\nThe ones getting it right are [what top performers do differently].\n\nPut together a quick breakdown: [link to free resource/calculator]\n\nThought it'd be useful given what [Company] is building.\n\n[Your name]"
      },
      {
        "title": "Template 3: The LinkedIn Warm-Up",
        "body": "Step 1: View their profile (creates notification)\nStep 2 (Day 2): Like/comment on their recent post (genuine, not generic)\nStep 3 (Day 4): Send connection request with note:\n\nHi [Name] — been following [Company]'s work in [space]. \nParticularly liked your take on [specific post topic]. \nWould love to connect.\n\nStep 4 (Day 7, after accepted): Send value message (NOT a pitch):\n\n[Name] — saw you mentioned [challenge] in your recent post. \nWe put together [free resource] that addresses exactly that. \nThought you might find it useful: [link]"
      },
      {
        "title": "Lead Record Schema",
        "body": "{\n  \"id\": \"lead-001\",\n  \"created\": \"2026-02-13\",\n  \"source\": \"web-search\",\n  \n  \"company\": {\n    \"name\": \"Acme Corp\",\n    \"website\": \"https://acme.com\",\n    \"industry\": \"SaaS\",\n    \"employees\": 150,\n    \"revenue_est\": \"$20M\",\n    \"funding\": \"Series B — $15M (2025)\",\n    \"tech_stack\": [\"Salesforce\", \"AWS\", \"React\"],\n    \"location\": \"San Francisco, CA\"\n  },\n  \n  \"contact\": {\n    \"first_name\": \"Jane\",\n    \"last_name\": \"Smith\",\n    \"title\": \"VP of Operations\",\n    \"email\": \"jane.smith@acme.com\",\n    \"email_verified\": false,\n    \"linkedin\": \"https://linkedin.com/in/janesmith\",\n    \"phone\": null\n  },\n  \n  \"scoring\": {\n    \"company_score\": 25,\n    \"persona_score\": 18,\n    \"intent_score\": 15,\n    \"timing_score\": 8,\n    \"engagement_score\": 0,\n    \"total\": 66,\n    \"tier\": \"B\"\n  },\n  \n  \"enrichment\": {\n    \"pain_signals\": [\"hiring 3 data analysts\", \"blog about manual reporting\"],\n    \"recent_news\": [\"Raised Series B in Jan 2026\"],\n    \"competitor_usage\": \"None detected\",\n    \"content_interests\": [\"data automation\", \"operational efficiency\"]\n  },\n  \n  \"outreach\": {\n    \"status\": \"not_started\",\n    \"sequence\": \"value-first\",\n    \"emails_sent\": 0,\n    \"last_contacted\": null,\n    \"next_action\": \"2026-02-14\",\n    \"replies\": [],\n    \"notes\": \"\"\n  },\n  \n  \"pipeline\": {\n    \"stage\": \"prospect\",\n    \"deal_value\": null,\n    \"probability\": 0,\n    \"next_step\": \"Initial outreach\"\n  }\n}"
      },
      {
        "title": "Pipeline Stages",
        "body": "PROSPECT → CONTACTED → REPLIED → MEETING_BOOKED → QUALIFIED → PROPOSAL → NEGOTIATION → CLOSED_WON / CLOSED_LOST"
      },
      {
        "title": "Tracking Metrics",
        "body": "Track these weekly to optimize your machine:\n\nDiscovery rate: leads found per search session\nEnrichment completeness: % of fields filled per lead\nScore distribution: what % are Tier A vs B vs C?\nResponse rate: replies / emails sent (target: 5-15%)\nMeeting rate: meetings / replies (target: 30-50%)\nConversion rate: deals / meetings (target: 20-30%)\nPipeline velocity: days from discovery → closed deal"
      },
      {
        "title": "Daily Autopilot Routine",
        "body": "MORNING (agent runs autonomously):\n  1. Run 3-5 discovery searches (rotate queries)\n  2. Enrich any un-enriched leads from yesterday\n  3. Score new leads\n  4. Send Day-N emails for active sequences\n  5. Check for replies → flag for human review\n  6. Update pipeline stages\n  7. Report: \"Found X leads, sent Y emails, Z replies\"\n\nWEEKLY:\n  1. Review Tier C leads — any moved to B/A?\n  2. Clean dead leads (no response after full sequence)\n  3. Analyze response rates by template — A/B test\n  4. Refresh ICP based on closed deals\n  5. Add new search queries based on wins"
      },
      {
        "title": "Agent Integration",
        "body": "# In your agent's heartbeat or cron:\n1. Load ICP config\n2. Run discovery for 1 search query\n3. Enrich top 5 new leads\n4. Score all unscored leads\n5. Queue outreach for Tier A leads\n6. Log results to daily brief"
      },
      {
        "title": "CSV Export",
        "body": "company,contact,title,email,linkedin,score,tier,industry,employees,pain_signal\nAcme Corp,Jane Smith,VP Ops,jane@acme.com,linkedin.com/in/jane,66,B,SaaS,150,hiring analysts"
      },
      {
        "title": "Weekly Report Template",
        "body": "# Lead Hunter Weekly Report — Week of [DATE]\n\n## Pipeline Summary\n- Total leads in system: [N]\n- New leads this week: [N]  \n- Tier A: [N] | Tier B: [N] | Tier C: [N]\n\n## Outreach Performance\n- Emails sent: [N]\n- Reply rate: [X%]\n- Meetings booked: [N]\n- Pipeline value added: $[X]\n\n## Top Leads This Week\n1. [Company] — [Contact] — Score: [X] — [Why they're hot]\n2. [Company] — [Contact] — Score: [X] — [Why they're hot]\n3. [Company] — [Contact] — Score: [X] — [Why they're hot]\n\n## Insights\n- Best performing search query: [query]\n- Best performing email template: [template]\n- Recommendation: [action to take]"
      },
      {
        "title": "Pro Tips",
        "body": "The 90-Day Window: New executives are 10x more likely to buy in their first 90 days. Prioritize \"new role\" signals.\nHiring = Buying: If a company is hiring for the role your product replaces, they have budget AND pain. These are your hottest leads.\nCompetitor's Customers: Search for reviews/complaints about competitors. Unhappy customers switch fastest.\nConference Lists: Speaker and attendee lists from industry events are gold. These people are actively engaged in the space.\nThe \"Reply to Anything\" Rule: Any reply (even \"not interested\") is valuable. It confirms the email works and the person exists. Log it.\nPersonalization > Volume: 20 hyper-personalized emails outperform 200 generic ones. Always reference something specific about the prospect.\nMulti-Thread: Don't rely on one contact per company. Find 2-3 decision-makers and approach from different angles.\nTiming Matters: Tuesday-Thursday, 8-10 AM local time gets the best open rates. Avoid Mondays and Fridays.\n\nBuilt by AfrexAI — AI agents that actually sell."
      }
    ],
    "body": "AfrexAI Lead Hunter Pro\n\nTurn your AI agent into a full B2B sales development machine. Discovery → Enrichment → Scoring → Outreach → CRM. Zero manual work.\n\nArchitecture\nDEFINE ICP ──▶ DISCOVER ──▶ ENRICH ──▶ SCORE ──▶ SEGMENT ──▶ OUTREACH ──▶ CRM\n    │              │            │          │          │            │          │\n    ▼              ▼            ▼          ▼          ▼            ▼          ▼\n Persona      Multi-source  Email+Phone  ICP fit   Tier A/B/C  Sequences  Pipeline\n Builder      Web Research  Company Data  Intent    Campaigns   Templates  Tracking\n\nPhase 1: Define Your Ideal Customer Profile (ICP)\n\nBefore hunting, know WHO you're hunting. Answer these:\n\nCompany-Level ICP\n# Copy and customize this ICP template\ncompany:\n  industries: [SaaS, fintech, legal-tech, prop-tech]\n  employee_range: [50, 500]        # sweet spot for AI adoption\n  revenue_range: [$5M, $100M]      # can afford $120K+ contracts\n  funding_stage: [Series A, Series B, Series C]\n  tech_signals:                     # tools that indicate AI readiness\n    positive: [Salesforce, HubSpot, Snowflake, AWS, Python]\n    negative: [no-website, wordpress-only]\n  geography: [US, UK, Canada, Australia]\n  pain_signals:                     # problems they're likely facing\n    - \"manual data entry\"\n    - \"compliance overhead\"\n    - \"scaling operations\"\n    - \"document processing\"\n\nBuyer Persona\npersona:\n  titles: [CEO, CTO, COO, VP Operations, Head of Innovation, Director of IT]\n  seniority: [C-Suite, VP, Director]\n  decision_authority: true          # can sign $50K+ without board approval\n  linkedin_activity:                # signals they're actively looking\n    - posts about AI/automation\n    - comments on digital transformation content\n    - recently changed roles (first 90 days = buying window)\n  anti-signals:                     # skip these\n    - \"consultant\" in title (not buyers)\n    - company < 10 employees (no budget)\n    - already has AI vendor (check for competitors in their stack)\n\nScoring Weights\nscoring:\n  icp_company_match: 30             # how well company matches\n  icp_persona_match: 20             # right title + seniority\n  intent_signals: 25                # actively looking for solutions\n  engagement_recency: 15            # recent activity online\n  timing_bonus: 10                  # new role, funding round, hiring\n  \n  thresholds:\n    tier_a: 80                      # hot — outreach immediately\n    tier_b: 60                      # warm — nurture sequence\n    tier_c: 40                      # cool — add to newsletter\n    disqualify: below 40            # don't waste time\n\nPhase 2: Multi-Source Discovery\nSource Priority Matrix\nSource\tBest For\tHow To Search\tData Quality\tCost\nWeb Search\tAny industry\t\"[industry] companies\" site:linkedin.com/company\tHigh\tFree\nGitHub\tDev tools, tech companies\tSearch repos, org pages, contributor profiles\tHigh\tFree\nProduct Hunt\tStartups, SaaS\tBrowse launches, upvoters (they're buyers too)\tMedium\tFree\nIndustry Lists\tTargeted verticals\t\"Top 50 [industry] companies 2026\", Clutch, G2\tHigh\tFree\nJob Boards\tHiring = growing = buying\t\"AI\" OR \"automation\" site:lever.co OR site:greenhouse.io\tHigh\tFree\nCrunchbase\tFunded startups\tRecently funded companies in target verticals\tHigh\tFreemium\nConference Speakers\tActive industry leaders\tSpeaker lists from industry events\tVery High\tFree\nPodcast Guests\tThought leaders with budget\tSearch \"[industry] podcast\" transcripts\tHigh\tFree\nDiscovery Search Templates\n\nFind companies by pain signal:\n\n\"[industry]\" \"manual process\" OR \"time-consuming\" OR \"looking for solutions\" site:linkedin.com\n\n\nFind companies by hiring signal (they're growing = they're buying):\n\n\"[company type]\" \"hiring\" \"AI\" OR \"automation\" OR \"data\" site:linkedin.com/jobs\n\n\nFind recently funded companies (flush with cash):\n\n\"[industry]\" \"raises\" OR \"Series A\" OR \"funding\" OR \"investment\" 2026\n\n\nFind companies using competitor tools (ripe for switching):\n\n\"[competitor tool]\" \"alternative\" OR \"switching from\" OR \"replaced\"\n\n\nFind decision makers directly:\n\n\"[title]\" \"[industry]\" \"[city/region]\" site:linkedin.com/in\n\nDiscovery Workflow\nFOR each search query:\n  1. Run web_search with the query\n  2. Extract company names + URLs from results\n  3. Deduplicate against existing leads\n  4. For each NEW company:\n     a. Visit company website → extract: industry, size estimate, tech signals\n     b. Search \"[company name] CEO\" OR \"[company name] founder\" → get decision maker\n     c. Search \"[company name] funding\" → get financial signals\n     d. Create lead record (see schema below)\n  5. Rate limit: 2-3 second delay between searches\n\nPhase 3: Enrichment Engine\n\nFor each discovered lead, enrich with verified data:\n\nCompany Enrichment Checklist\n Website — Load homepage, extract value prop, tech stack (check <meta> tags, JS frameworks)\n Employee Count — LinkedIn company page, Crunchbase, or website \"About\" page\n Revenue Estimate — Funding amount × 3-5x multiplier, or industry benchmarks\n Tech Stack — Check BuiltWith, Wappalyzer data, or job postings for tech mentions\n Recent News — Last 90 days: funding, launches, executive changes, partnerships\n Pain Indicators — Job postings mentioning problems you solve, blog posts about challenges\n Competitor Usage — Do they use a competitor? Which one? (Check G2 reviews, case studies)\nContact Enrichment Checklist\n Full Name — First + Last from LinkedIn or company page\n Title — Current role (verify it matches your buyer persona)\n Email Pattern — Determine company pattern: first@, first.last@, firstlast@, f.last@\n Email Verification — Test pattern with known format, check MX records\n LinkedIn URL — Direct profile link\n Recent Activity — What have they posted/shared in last 30 days?\n Mutual Connections — Anyone in your network connected to them?\n Content Interests — What topics do they engage with? (Use for personalization)\nEmail Pattern Detection\nCommon patterns (test in order of likelihood):\n1. first.last@company.com     (most common, ~40%)\n2. first@company.com          (startups, ~25%)\n3. firstlast@company.com      (~15%)\n4. flast@company.com           (~10%)\n5. first_last@company.com     (~5%)\n6. last.first@company.com     (~3%)\n7. first.l@company.com        (~2%)\n\nVerification approach:\n- Check if company has public team page with email format\n- Look for email in GitHub commits from company domain\n- Check email format on Hunter.io or similar (if available)\n- Search \"[person name] email [company]\" \n- Check their personal website/blog for contact\n\nPhase 4: Lead Scoring Algorithm\n\nScore each lead 0-100 using this rubric:\n\nCompany Score (0-30 points)\nSignal\tPoints\tHow to Check\nIndustry matches ICP exactly\t+10\tCompare to ICP config\nEmployee count in sweet spot\t+5\tLinkedIn/website\nRevenue in target range\t+5\tCrunchbase/estimate\nLocated in target geography\t+3\tWebsite/LinkedIn\nUses compatible tech stack\t+4\tJob posts, BuiltWith\nNo competitor currently\t+3\tResearch, case studies\nPersona Score (0-20 points)\nSignal\tPoints\tHow to Check\nTitle matches buyer persona\t+8\tLinkedIn\nC-Suite or VP level\t+5\tLinkedIn\nHas decision authority\t+4\tTitle + company size\nActive on LinkedIn (posts monthly)\t+3\tLinkedIn activity\nIntent Score (0-25 points)\nSignal\tPoints\tHow to Check\nRecently posted about relevant pain\t+8\tLinkedIn/Twitter\nCompany hiring for roles you'd replace\t+7\tJob boards\nAttended relevant industry event\t+5\tConference lists\nDownloaded competitor content\t+3\tHard to verify, skip if unknown\nSearched for solution keywords\t+2\tHard to verify, skip if unknown\nTiming Score (0-15 points)\nSignal\tPoints\tHow to Check\nNew in role (< 90 days)\t+5\tLinkedIn start date\nCompany just raised funding\t+4\tCrunchbase/news\nEnd of quarter (budget flush)\t+3\tCalendar\nCompany growing fast (hiring surge)\t+3\tJob postings count\nEngagement Score (0-10 points)\nSignal\tPoints\tHow to Check\nOpened previous email\t+4\tEmail tracking\nVisited your website\t+3\tAnalytics\nConnected on LinkedIn\t+2\tLinkedIn\nReferred by someone\t+1\tCRM notes\nPhase 5: Segmentation & Campaign Assignment\nTier A (Score 80-100) — HOT LEADS\nAction: Immediate personalized outreach\nSequence: 5-touch hyper-personalized campaign\nTimeline: Contact within 24 hours\nChannel: Email → LinkedIn → Phone (if available)\nTemplate: \"CEO-to-CEO\" or \"Specific Pain\" (see below)\n\nTier B (Score 60-79) — WARM LEADS\nAction: Nurture sequence\nSequence: 7-touch value-first campaign  \nTimeline: Start within 48 hours\nChannel: Email → LinkedIn\nTemplate: \"Value Insight\" or \"Case Study\" (see below)\n\nTier C (Score 40-59) — COOL LEADS\nAction: Add to newsletter + long-term nurture\nSequence: Monthly value content\nTimeline: Bi-weekly touchpoints\nChannel: Email only\nTemplate: \"Industry Report\" or \"Educational\" (see below)\n\nPhase 6: Outreach Sequence Templates\nTemplate 1: The Specific Pain (Tier A)\n\nEmail 1 — Day 0 (The Hook)\n\nSubject: [specific pain point] at [Company]?\n\nHi [First Name],\n\nNoticed [Company] is [specific observation — hiring for X role / posted about Y challenge / using Z tool].\n\nThat usually means [pain point they're likely feeling].\n\nWe built [solution] that [specific result with number]. [Client name] cut their [metric] by [X%] in [timeframe].\n\nWorth a 15-min call to see if it fits [Company]?\n\n[Your name]\n\n\nEmail 2 — Day 3 (The Proof)\n\nSubject: Re: [original subject]\n\n[First Name] — quick follow-up.\n\nHere's exactly what we did for [similar company]: [1-sentence case study with specific numbers].\n\n[Link to case study or calculator]\n\nHappy to walk through how this maps to [Company].\n\n[Your name]\n\n\nEmail 3 — Day 7 (The Angle)\n\nSubject: [industry trend] + [Company]\n\n[First Name],\n\n[Industry trend or stat that's relevant]. Companies like [Company] are [what smart companies are doing about it].\n\nWe help [type of company] [specific outcome]. Takes about [timeframe] to see results.\n\nOpen to a quick chat this week?\n\n[Your name]\n\n\nEmail 4 — Day 14 (The Breakup)\n\nSubject: Should I close your file?\n\n[First Name],\n\nI've reached out a few times — totally understand if the timing isn't right.\n\nIf [pain point] becomes a priority, here's a [free resource] that might help: [link]\n\nEither way, I'll stop filling your inbox. Just reply \"yes\" if you'd like to chat sometime.\n\n[Your name]\n\nTemplate 2: The Value-First (Tier B)\n\nEmail 1 — Lead with insight, not a pitch\n\nSubject: [number] [industry] companies are doing [thing] wrong\n\nHi [First Name],\n\nWe analyzed [X] companies in [industry] and found that [surprising insight].\n\nThe ones getting it right are [what top performers do differently].\n\nPut together a quick breakdown: [link to free resource/calculator]\n\nThought it'd be useful given what [Company] is building.\n\n[Your name]\n\nTemplate 3: The LinkedIn Warm-Up\n\nStep 1: View their profile (creates notification) Step 2 (Day 2): Like/comment on their recent post (genuine, not generic) Step 3 (Day 4): Send connection request with note:\n\nHi [Name] — been following [Company]'s work in [space]. \nParticularly liked your take on [specific post topic]. \nWould love to connect.\n\n\nStep 4 (Day 7, after accepted): Send value message (NOT a pitch):\n\n[Name] — saw you mentioned [challenge] in your recent post. \nWe put together [free resource] that addresses exactly that. \nThought you might find it useful: [link]\n\nPhase 7: CRM & Pipeline Management\nLead Record Schema\n{\n  \"id\": \"lead-001\",\n  \"created\": \"2026-02-13\",\n  \"source\": \"web-search\",\n  \n  \"company\": {\n    \"name\": \"Acme Corp\",\n    \"website\": \"https://acme.com\",\n    \"industry\": \"SaaS\",\n    \"employees\": 150,\n    \"revenue_est\": \"$20M\",\n    \"funding\": \"Series B — $15M (2025)\",\n    \"tech_stack\": [\"Salesforce\", \"AWS\", \"React\"],\n    \"location\": \"San Francisco, CA\"\n  },\n  \n  \"contact\": {\n    \"first_name\": \"Jane\",\n    \"last_name\": \"Smith\",\n    \"title\": \"VP of Operations\",\n    \"email\": \"jane.smith@acme.com\",\n    \"email_verified\": false,\n    \"linkedin\": \"https://linkedin.com/in/janesmith\",\n    \"phone\": null\n  },\n  \n  \"scoring\": {\n    \"company_score\": 25,\n    \"persona_score\": 18,\n    \"intent_score\": 15,\n    \"timing_score\": 8,\n    \"engagement_score\": 0,\n    \"total\": 66,\n    \"tier\": \"B\"\n  },\n  \n  \"enrichment\": {\n    \"pain_signals\": [\"hiring 3 data analysts\", \"blog about manual reporting\"],\n    \"recent_news\": [\"Raised Series B in Jan 2026\"],\n    \"competitor_usage\": \"None detected\",\n    \"content_interests\": [\"data automation\", \"operational efficiency\"]\n  },\n  \n  \"outreach\": {\n    \"status\": \"not_started\",\n    \"sequence\": \"value-first\",\n    \"emails_sent\": 0,\n    \"last_contacted\": null,\n    \"next_action\": \"2026-02-14\",\n    \"replies\": [],\n    \"notes\": \"\"\n  },\n  \n  \"pipeline\": {\n    \"stage\": \"prospect\",\n    \"deal_value\": null,\n    \"probability\": 0,\n    \"next_step\": \"Initial outreach\"\n  }\n}\n\nPipeline Stages\nPROSPECT → CONTACTED → REPLIED → MEETING_BOOKED → QUALIFIED → PROPOSAL → NEGOTIATION → CLOSED_WON / CLOSED_LOST\n\nTracking Metrics\n\nTrack these weekly to optimize your machine:\n\nDiscovery rate: leads found per search session\nEnrichment completeness: % of fields filled per lead\nScore distribution: what % are Tier A vs B vs C?\nResponse rate: replies / emails sent (target: 5-15%)\nMeeting rate: meetings / replies (target: 30-50%)\nConversion rate: deals / meetings (target: 20-30%)\nPipeline velocity: days from discovery → closed deal\nPhase 8: Automation & Scheduling\nDaily Autopilot Routine\nMORNING (agent runs autonomously):\n  1. Run 3-5 discovery searches (rotate queries)\n  2. Enrich any un-enriched leads from yesterday\n  3. Score new leads\n  4. Send Day-N emails for active sequences\n  5. Check for replies → flag for human review\n  6. Update pipeline stages\n  7. Report: \"Found X leads, sent Y emails, Z replies\"\n\nWEEKLY:\n  1. Review Tier C leads — any moved to B/A?\n  2. Clean dead leads (no response after full sequence)\n  3. Analyze response rates by template — A/B test\n  4. Refresh ICP based on closed deals\n  5. Add new search queries based on wins\n\nAgent Integration\n# In your agent's heartbeat or cron:\n1. Load ICP config\n2. Run discovery for 1 search query\n3. Enrich top 5 new leads\n4. Score all unscored leads\n5. Queue outreach for Tier A leads\n6. Log results to daily brief\n\nOutput Formats\nCSV Export\ncompany,contact,title,email,linkedin,score,tier,industry,employees,pain_signal\nAcme Corp,Jane Smith,VP Ops,jane@acme.com,linkedin.com/in/jane,66,B,SaaS,150,hiring analysts\n\nWeekly Report Template\n# Lead Hunter Weekly Report — Week of [DATE]\n\n## Pipeline Summary\n- Total leads in system: [N]\n- New leads this week: [N]  \n- Tier A: [N] | Tier B: [N] | Tier C: [N]\n\n## Outreach Performance\n- Emails sent: [N]\n- Reply rate: [X%]\n- Meetings booked: [N]\n- Pipeline value added: $[X]\n\n## Top Leads This Week\n1. [Company] — [Contact] — Score: [X] — [Why they're hot]\n2. [Company] — [Contact] — Score: [X] — [Why they're hot]\n3. [Company] — [Contact] — Score: [X] — [Why they're hot]\n\n## Insights\n- Best performing search query: [query]\n- Best performing email template: [template]\n- Recommendation: [action to take]\n\nPro Tips\nThe 90-Day Window: New executives are 10x more likely to buy in their first 90 days. Prioritize \"new role\" signals.\nHiring = Buying: If a company is hiring for the role your product replaces, they have budget AND pain. These are your hottest leads.\nCompetitor's Customers: Search for reviews/complaints about competitors. Unhappy customers switch fastest.\nConference Lists: Speaker and attendee lists from industry events are gold. These people are actively engaged in the space.\nThe \"Reply to Anything\" Rule: Any reply (even \"not interested\") is valuable. It confirms the email works and the person exists. Log it.\nPersonalization > Volume: 20 hyper-personalized emails outperform 200 generic ones. Always reference something specific about the prospect.\nMulti-Thread: Don't rely on one contact per company. Find 2-3 decision-makers and approach from different angles.\nTiming Matters: Tuesday-Thursday, 8-10 AM local time gets the best open rates. Avoid Mondays and Fridays.\n\nBuilt by AfrexAI — AI agents that actually sell."
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