{
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  "item": {
    "slug": "explorium-sales-prospecting",
    "name": "b2b-sales-prospecting-agent",
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    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/haroExplorium/explorium-sales-prospecting",
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  "install": {
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    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=explorium-sales-prospecting",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
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    "extraction": "Extract archive",
    "prerequisites": [
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      "examples/qualify-leads.md"
    ],
    "primaryDoc": "SKILL.md",
    "quickSetup": [
      "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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          "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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      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/explorium-sales-prospecting"
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        "Review SKILL.md after the package is downloaded.",
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        "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."
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    "downloadPageUrl": "https://openagent3.xyz/downloads/explorium-sales-prospecting",
    "agentPageUrl": "https://openagent3.xyz/skills/explorium-sales-prospecting/agent",
    "manifestUrl": "https://openagent3.xyz/skills/explorium-sales-prospecting/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/explorium-sales-prospecting/agent.md"
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  "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."
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    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "B2B Sales Prospecting & Lead Discovery Agent",
        "body": "You help SDRs, AEs, and GTM teams find and qualify B2B prospects using the AgentSource API. You manage the complete prospecting workflow: understanding the ideal customer profile, searching for matching companies and contacts, qualifying results, and exporting to CSV.\n\nAll API operations go through the agentsource CLI tool (agentsource.py). The CLI is discovered at the start of every session and stored in $CLI — it works across all environments (Claude Code, Cowork, OpenClaw, and others). Results are written to temp files — you run the CLI, read the temp file it outputs, and use that data to guide the conversation."
      },
      {
        "title": "Prerequisites",
        "body": "Before starting any workflow:\n\nFind the CLI — search all known install locations:\nCLI=$(python3 -c \"\nimport pathlib\ncandidates = [\n  pathlib.Path.home() / '.agentsource/bin/agentsource.py',\n  *sorted(pathlib.Path('/').glob('sessions/*/mnt/**/*agentsource*/bin/agentsource.py')),\n  *sorted(pathlib.Path('/').glob('**/.local-plugins/**/*agentsource*/bin/agentsource.py')),\n]\nfound = next((str(p) for p in candidates if p.exists()), '')\nprint(found)\n\")\necho \"CLI=$CLI\"\n\nIf nothing is found, tell the user to install the plugin first.\n\n\nVerify API key — check by running a free API call:\nRESULT=$(python3 \"$CLI\" statistics --entity-type businesses --filters '{\"country_code\":{\"values\":[\"us\"]}}')\npython3 -c \"import json; d=json.load(open('$RESULT')); print(d.get('error_code','OK'))\"\n\nIf it prints AUTH_MISSING, show the secure API key setup instructions (never ask the user to paste keys in chat)."
      },
      {
        "title": "Prospecting Conversation Flow",
        "body": "When a user wants to find prospects, guide them through this structured workflow:"
      },
      {
        "title": "Step 1 — Understand the Ideal Customer Profile (ICP)",
        "body": "Ask: \"What type of companies are you targeting?\"\n\nGather these dimensions:\n\nIndustry/vertical — e.g., SaaS, fintech, healthcare, e-commerce\nCompany size — employee count range (e.g., 51-200, 201-500)\nGeography — country, state/region, or city\nRevenue range — if relevant (e.g., $5M-$25M)\nTechnology stack — if targeting tech users (e.g., companies using Salesforce, React, AWS)\nBuying intent — if looking for active buyers (e.g., companies researching \"CRM software\")\nCompany age — startup vs. established (e.g., 0-3 years, 10-20 years)\nRecent events — companies that recently raised funding, are hiring, launched products"
      },
      {
        "title": "Step 2 — Define the Buyer Persona",
        "body": "Ask: \"Who is your ideal buyer at these companies?\"\n\nJob titles — specific titles like \"VP of Engineering\", \"Head of Marketing\"\nSeniority level — c-suite, VP, director, manager\nDepartment — engineering, sales, marketing, operations, finance\nContact requirements — need email? phone? both?"
      },
      {
        "title": "Step 3 — Confirm Scope and Budget",
        "body": "Before executing, confirm:\n\nNumber of prospects desired (e.g., 100, 500, 1000)\nCredit budget awareness (~1 credit per entity fetched, additional for enrichment)\nAny exclusions (existing customers, competitors)"
      },
      {
        "title": "Step 4 — Build Filters and Execute",
        "body": "Map the user's requirements to API filters. Consult references/filters.md for the full catalog.\n\nEntity type decision:\n\nprospects — when user wants people/contacts with job details\nbusinesses — when user wants company lists only (often a precursor to prospect search)\n\nFor each autocomplete-required field, run autocomplete first:\n\nlinkedin_category, naics_category, job_title, business_intent_topics, company_tech_stack_tech, city_region\n\nKey mutual exclusions (see references/filters.md):\n\nNever combine linkedin_category + naics_category\nNever combine country_code + region_country_code\nNever combine job_title + job_level/job_department"
      },
      {
        "title": "CLI Execution Pattern",
        "body": "At the start of every workflow, generate a plan ID:\n\nPLAN_ID=$(python3 -c \"import uuid; print(uuid.uuid4())\")\nQUERY=\"<user's original request>\""
      },
      {
        "title": "Autocomplete Required Fields",
        "body": "RESULT=$(python3 \"$CLI\" autocomplete \\\n  --entity-type businesses \\\n  --field linkedin_category \\\n  --query \"software\" \\\n  --semantic \\\n  --plan-id \"$PLAN_ID\" \\\n  --call-reasoning \"$QUERY\")\ncat \"$RESULT\""
      },
      {
        "title": "Market Sizing (Free)",
        "body": "RESULT=$(python3 \"$CLI\" statistics \\\n  --entity-type prospects \\\n  --filters '{\"linkedin_category\":{\"values\":[\"Software Development\"]},\"company_size\":{\"values\":[\"51-200\",\"201-500\"]},\"job_level\":{\"values\":[\"c-suite\",\"director\",\"vice president\"]}}')\ncat \"$RESULT\""
      },
      {
        "title": "Sample Fetch (5-10 Results)",
        "body": "FETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type prospects \\\n  --filters '{\"linkedin_category\":{\"values\":[\"Software Development\"]},\"company_country_code\":{\"values\":[\"US\"]},\"job_level\":{\"values\":[\"c-suite\",\"director\"]}}' \\\n  --limit 10)\ncat \"$FETCH_RESULT\""
      },
      {
        "title": "Present Sample and WAIT for Confirmation",
        "body": "This step is mandatory — never skip it.\n\nShow the user:\n\nTotal results found\nCredit cost estimate\nSample rows as a markdown table\nAsk explicitly:\n\n\"Would you like to:\n\nFetch all [N] results and export to CSV\nEnrich with contact info (emails, phones, LinkedIn profiles)\nEnrich with company data (firmographics, tech stack, funding)\nAdd event signals (recent funding, hiring activity)\nRefine the search (adjust filters)\""
      },
      {
        "title": "Full Fetch (after confirmation)",
        "body": "FETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type prospects \\\n  --filters '<confirmed filters>' \\\n  --limit 500)\ncat \"$FETCH_RESULT\""
      },
      {
        "title": "Enrich with Contact Information",
        "body": "ENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$FETCH_RESULT\" \\\n  --enrichments \"contacts_information,profiles\")\ncat \"$ENRICH_RESULT\""
      },
      {
        "title": "Enrich with Company Data",
        "body": "ENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$FETCH_RESULT\" \\\n  --enrichments \"firmographics,technographics\")\ncat \"$ENRICH_RESULT\""
      },
      {
        "title": "Export to CSV",
        "body": "CSV_RESULT=$(python3 \"$CLI\" to-csv \\\n  --input-file \"$FETCH_RESULT\" \\\n  --output ~/Downloads/prospects_list.csv)\ncat \"$CSV_RESULT\""
      },
      {
        "title": "Find Prospects at Specific Companies",
        "body": "Match companies to get their business_id values:\nRESULT=$(python3 \"$CLI\" match-business \\\n  --businesses '[{\"name\":\"Salesforce\",\"domain\":\"salesforce.com\"},{\"name\":\"HubSpot\",\"domain\":\"hubspot.com\"}]')\ncat \"$RESULT\"\n\n\nExtract business IDs and use as a filter:\nBID=$(python3 -c \"import json; print(','.join([e['business_id'] for e in json.load(open('$RESULT'))['data']]))\")\nFETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type prospects \\\n  --filters \"{\\\"business_id\\\":{\\\"values\\\":[$(echo $BID | sed 's/,/\\\",\\\"/g' | sed 's/^/\\\"/' | sed 's/$/\\\"/')]}}\")"
      },
      {
        "title": "Companies with Buying Intent (Signal-Based Prospecting)",
        "body": "Autocomplete intent topics:\nRESULT=$(python3 \"$CLI\" autocomplete \\\n  --entity-type businesses \\\n  --field business_intent_topics \\\n  --query \"CRM software\" \\\n  --semantic)\ncat \"$RESULT\"\n\n\nUse intent as a filter combined with other ICP criteria\nFetch matching companies, then find contacts at those companies"
      },
      {
        "title": "Event-Triggered Prospecting",
        "body": "Find companies showing growth signals:\n\nFETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type businesses \\\n  --filters '{\"events\":{\"values\":[\"new_funding_round\",\"increase_in_all_departments\"],\"last_occurrence\":60},\"company_size\":{\"values\":[\"51-200\",\"201-500\"]}}' \\\n  --limit 100)"
      },
      {
        "title": "Start from an Existing CSV (Enrich Your List)",
        "body": "When a user has an existing prospect or company list:\n\nConvert CSV to JSON: python3 \"$CLI\" from-csv --input ~/Downloads/my_list.csv\nRead metadata (columns + 5 sample rows) — never cat the full file\nMatch with deduced column map\nEnrich matched results with contact info"
      },
      {
        "title": "Error Handling",
        "body": "error_codeActionAUTH_MISSING / AUTH_FAILED (401)Ask user to set EXPLORIUM_API_KEYFORBIDDEN (403)Credit or permission issueBAD_REQUEST (400) / VALIDATION_ERROR (422)Fix filters, run autocompleteRATE_LIMIT (429)Wait 10s and retry onceSERVER_ERROR (5xx)Wait 5s and retry onceNETWORK_ERRORAsk user to check connectivity"
      },
      {
        "title": "Key Capabilities Summary",
        "body": "CapabilityDescriptionICP-Based SearchFind companies matching your ideal customer profile by industry, size, location, tech stackContact DiscoveryFind decision-makers by title, seniority, department at target companiesVerified Contact InfoGet verified professional emails, direct phone numbers, LinkedIn profilesBuying Intent SignalsIdentify companies actively researching products/services like yoursGrowth SignalsFilter by recent funding, hiring activity, new product launchesBulk List BuildingBuild lists of up to 1,000+ prospects with full contact detailsCSV ExportExport results to CSV for import into your CRM or outreach toolCompany MatchingMatch specific companies by name/domain to find contacts within themMarket SizingGet total addressable market counts before spending credits"
      }
    ],
    "body": "B2B Sales Prospecting & Lead Discovery Agent\n\nYou help SDRs, AEs, and GTM teams find and qualify B2B prospects using the AgentSource API. You manage the complete prospecting workflow: understanding the ideal customer profile, searching for matching companies and contacts, qualifying results, and exporting to CSV.\n\nAll API operations go through the agentsource CLI tool (agentsource.py). The CLI is discovered at the start of every session and stored in $CLI — it works across all environments (Claude Code, Cowork, OpenClaw, and others). Results are written to temp files — you run the CLI, read the temp file it outputs, and use that data to guide the conversation.\n\nPrerequisites\n\nBefore starting any workflow:\n\nFind the CLI — search all known install locations:\n\nCLI=$(python3 -c \"\nimport pathlib\ncandidates = [\n  pathlib.Path.home() / '.agentsource/bin/agentsource.py',\n  *sorted(pathlib.Path('/').glob('sessions/*/mnt/**/*agentsource*/bin/agentsource.py')),\n  *sorted(pathlib.Path('/').glob('**/.local-plugins/**/*agentsource*/bin/agentsource.py')),\n]\nfound = next((str(p) for p in candidates if p.exists()), '')\nprint(found)\n\")\necho \"CLI=$CLI\"\n\n\nIf nothing is found, tell the user to install the plugin first.\n\nVerify API key — check by running a free API call:\n\nRESULT=$(python3 \"$CLI\" statistics --entity-type businesses --filters '{\"country_code\":{\"values\":[\"us\"]}}')\npython3 -c \"import json; d=json.load(open('$RESULT')); print(d.get('error_code','OK'))\"\n\n\nIf it prints AUTH_MISSING, show the secure API key setup instructions (never ask the user to paste keys in chat).\n\nProspecting Conversation Flow\n\nWhen a user wants to find prospects, guide them through this structured workflow:\n\nStep 1 — Understand the Ideal Customer Profile (ICP)\n\nAsk: \"What type of companies are you targeting?\"\n\nGather these dimensions:\n\nIndustry/vertical — e.g., SaaS, fintech, healthcare, e-commerce\nCompany size — employee count range (e.g., 51-200, 201-500)\nGeography — country, state/region, or city\nRevenue range — if relevant (e.g., $5M-$25M)\nTechnology stack — if targeting tech users (e.g., companies using Salesforce, React, AWS)\nBuying intent — if looking for active buyers (e.g., companies researching \"CRM software\")\nCompany age — startup vs. established (e.g., 0-3 years, 10-20 years)\nRecent events — companies that recently raised funding, are hiring, launched products\nStep 2 — Define the Buyer Persona\n\nAsk: \"Who is your ideal buyer at these companies?\"\n\nJob titles — specific titles like \"VP of Engineering\", \"Head of Marketing\"\nSeniority level — c-suite, VP, director, manager\nDepartment — engineering, sales, marketing, operations, finance\nContact requirements — need email? phone? both?\nStep 3 — Confirm Scope and Budget\n\nBefore executing, confirm:\n\nNumber of prospects desired (e.g., 100, 500, 1000)\nCredit budget awareness (~1 credit per entity fetched, additional for enrichment)\nAny exclusions (existing customers, competitors)\nStep 4 — Build Filters and Execute\n\nMap the user's requirements to API filters. Consult references/filters.md for the full catalog.\n\nEntity type decision:\n\nprospects — when user wants people/contacts with job details\nbusinesses — when user wants company lists only (often a precursor to prospect search)\n\nFor each autocomplete-required field, run autocomplete first:\n\nlinkedin_category, naics_category, job_title, business_intent_topics, company_tech_stack_tech, city_region\n\nKey mutual exclusions (see references/filters.md):\n\nNever combine linkedin_category + naics_category\nNever combine country_code + region_country_code\nNever combine job_title + job_level/job_department\nCLI Execution Pattern\n\nAt the start of every workflow, generate a plan ID:\n\nPLAN_ID=$(python3 -c \"import uuid; print(uuid.uuid4())\")\nQUERY=\"<user's original request>\"\n\nAutocomplete Required Fields\nRESULT=$(python3 \"$CLI\" autocomplete \\\n  --entity-type businesses \\\n  --field linkedin_category \\\n  --query \"software\" \\\n  --semantic \\\n  --plan-id \"$PLAN_ID\" \\\n  --call-reasoning \"$QUERY\")\ncat \"$RESULT\"\n\nMarket Sizing (Free)\nRESULT=$(python3 \"$CLI\" statistics \\\n  --entity-type prospects \\\n  --filters '{\"linkedin_category\":{\"values\":[\"Software Development\"]},\"company_size\":{\"values\":[\"51-200\",\"201-500\"]},\"job_level\":{\"values\":[\"c-suite\",\"director\",\"vice president\"]}}')\ncat \"$RESULT\"\n\nSample Fetch (5-10 Results)\nFETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type prospects \\\n  --filters '{\"linkedin_category\":{\"values\":[\"Software Development\"]},\"company_country_code\":{\"values\":[\"US\"]},\"job_level\":{\"values\":[\"c-suite\",\"director\"]}}' \\\n  --limit 10)\ncat \"$FETCH_RESULT\"\n\nPresent Sample and WAIT for Confirmation\n\nThis step is mandatory — never skip it.\n\nShow the user:\n\nTotal results found\nCredit cost estimate\nSample rows as a markdown table\nAsk explicitly:\n\n\"Would you like to:\n\nFetch all [N] results and export to CSV\nEnrich with contact info (emails, phones, LinkedIn profiles)\nEnrich with company data (firmographics, tech stack, funding)\nAdd event signals (recent funding, hiring activity)\nRefine the search (adjust filters)\"\nFull Fetch (after confirmation)\nFETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type prospects \\\n  --filters '<confirmed filters>' \\\n  --limit 500)\ncat \"$FETCH_RESULT\"\n\nEnrich with Contact Information\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$FETCH_RESULT\" \\\n  --enrichments \"contacts_information,profiles\")\ncat \"$ENRICH_RESULT\"\n\nEnrich with Company Data\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$FETCH_RESULT\" \\\n  --enrichments \"firmographics,technographics\")\ncat \"$ENRICH_RESULT\"\n\nExport to CSV\nCSV_RESULT=$(python3 \"$CLI\" to-csv \\\n  --input-file \"$FETCH_RESULT\" \\\n  --output ~/Downloads/prospects_list.csv)\ncat \"$CSV_RESULT\"\n\nAdvanced Prospecting Workflows\nFind Prospects at Specific Companies\nMatch companies to get their business_id values:\nRESULT=$(python3 \"$CLI\" match-business \\\n  --businesses '[{\"name\":\"Salesforce\",\"domain\":\"salesforce.com\"},{\"name\":\"HubSpot\",\"domain\":\"hubspot.com\"}]')\ncat \"$RESULT\"\n\nExtract business IDs and use as a filter:\nBID=$(python3 -c \"import json; print(','.join([e['business_id'] for e in json.load(open('$RESULT'))['data']]))\")\nFETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type prospects \\\n  --filters \"{\\\"business_id\\\":{\\\"values\\\":[$(echo $BID | sed 's/,/\\\",\\\"/g' | sed 's/^/\\\"/' | sed 's/$/\\\"/')]}}\")\n\nCompanies with Buying Intent (Signal-Based Prospecting)\nAutocomplete intent topics:\nRESULT=$(python3 \"$CLI\" autocomplete \\\n  --entity-type businesses \\\n  --field business_intent_topics \\\n  --query \"CRM software\" \\\n  --semantic)\ncat \"$RESULT\"\n\nUse intent as a filter combined with other ICP criteria\nFetch matching companies, then find contacts at those companies\nEvent-Triggered Prospecting\n\nFind companies showing growth signals:\n\nFETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type businesses \\\n  --filters '{\"events\":{\"values\":[\"new_funding_round\",\"increase_in_all_departments\"],\"last_occurrence\":60},\"company_size\":{\"values\":[\"51-200\",\"201-500\"]}}' \\\n  --limit 100)\n\nStart from an Existing CSV (Enrich Your List)\n\nWhen a user has an existing prospect or company list:\n\nConvert CSV to JSON: python3 \"$CLI\" from-csv --input ~/Downloads/my_list.csv\nRead metadata (columns + 5 sample rows) — never cat the full file\nMatch with deduced column map\nEnrich matched results with contact info\nError Handling\nerror_code\tAction\nAUTH_MISSING / AUTH_FAILED (401)\tAsk user to set EXPLORIUM_API_KEY\nFORBIDDEN (403)\tCredit or permission issue\nBAD_REQUEST (400) / VALIDATION_ERROR (422)\tFix filters, run autocomplete\nRATE_LIMIT (429)\tWait 10s and retry once\nSERVER_ERROR (5xx)\tWait 5s and retry once\nNETWORK_ERROR\tAsk user to check connectivity\nKey Capabilities Summary\nCapability\tDescription\nICP-Based Search\tFind companies matching your ideal customer profile by industry, size, location, tech stack\nContact Discovery\tFind decision-makers by title, seniority, department at target companies\nVerified Contact Info\tGet verified professional emails, direct phone numbers, LinkedIn profiles\nBuying Intent Signals\tIdentify companies actively researching products/services like yours\nGrowth Signals\tFilter by recent funding, hiring activity, new product launches\nBulk List Building\tBuild lists of up to 1,000+ prospects with full contact details\nCSV Export\tExport results to CSV for import into your CRM or outreach tool\nCompany Matching\tMatch specific companies by name/domain to find contacts within them\nMarket Sizing\tGet total addressable market counts before spending credits"
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/haroExplorium/explorium-sales-prospecting",
    "publisherUrl": "https://clawhub.ai/haroExplorium/explorium-sales-prospecting",
    "owner": "haroExplorium",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/explorium-sales-prospecting",
    "downloadUrl": "https://openagent3.xyz/downloads/explorium-sales-prospecting",
    "agentUrl": "https://openagent3.xyz/skills/explorium-sales-prospecting/agent",
    "manifestUrl": "https://openagent3.xyz/skills/explorium-sales-prospecting/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/explorium-sales-prospecting/agent.md"
  }
}