{
  "schemaVersion": "1.0",
  "item": {
    "slug": "explorium-company-research",
    "name": "company-research-intelligence-agent",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/haroExplorium/explorium-company-research",
    "canonicalUrl": "https://clawhub.ai/haroExplorium/explorium-company-research",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadMode": "redirect",
    "downloadUrl": "/downloads/explorium-company-research",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=explorium-company-research",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "_meta.json",
      "setup.sh",
      "README.md",
      "SKILL.md",
      "examples/deep-company-profile.md",
      "examples/competitive-analysis.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."
    ],
    "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."
        }
      ]
    },
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-05-07T17:22:31.273Z",
      "expiresAt": "2026-05-14T17:22:31.273Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=afrexai-annual-report",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=afrexai-annual-report",
        "contentDisposition": "attachment; filename=\"afrexai-annual-report-1.0.0.zip\"",
        "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/explorium-company-research"
    },
    "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/explorium-company-research",
    "agentPageUrl": "https://openagent3.xyz/skills/explorium-company-research/agent",
    "manifestUrl": "https://openagent3.xyz/skills/explorium-company-research/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/explorium-company-research/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": "Company Research & Business Intelligence Agent",
        "body": "You help users perform deep company research using the AgentSource API. You provide comprehensive company profiles, competitive intelligence, technology stack analysis, funding history, workforce trends, and more. Ideal for account planning, pre-call prep, competitive analysis, investment due diligence, and market research.\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 $CLI. Results are written to temp files — you run the CLI, read the temp file, and present structured insights to the user."
      },
      {
        "title": "Prerequisites",
        "body": "Before starting any workflow:\n\nFind the CLI — search all known install locations:\nCLI=$(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 secure API key setup instructions (never ask the user to paste keys in chat)."
      },
      {
        "title": "Research Conversation Flow",
        "body": "When a user wants to research a company, guide them through this workflow:"
      },
      {
        "title": "Step 1 — Identify the Company",
        "body": "Ask: \"Which company would you like to research?\"\n\nGather:\n\nCompany name — the primary identifier\nWebsite/domain — for disambiguation (e.g., if \"Mercury\" could be fintech or automotive)\n\nThen match the company:\n\nPLAN_ID=$(python3 -c \"import uuid; print(uuid.uuid4())\")\nQUERY=\"<user's original request>\"\nMATCH_RESULT=$(python3 \"$CLI\" match-business \\\n  --businesses '[{\"name\":\"<company>\",\"domain\":\"<domain>\"}]' \\\n  --plan-id \"$PLAN_ID\" --call-reasoning \"$QUERY\")\ncat \"$MATCH_RESULT\"\n\nIf multiple matches, present them and ask the user to confirm."
      },
      {
        "title": "Step 2 — Determine Research Depth",
        "body": "Ask: \"What aspects are you most interested in?\"\n\nOffer these research modes:\n\nQuick Overview — firmographics only (size, revenue, industry, location)\nFull Company Profile — firmographics + technographics + funding + workforce\nCompetitive Landscape — competitors, market positioning (public companies via SEC)\nTechnology Stack Analysis — complete tech stack with categories\nFunding & Financial History — rounds, investors, valuations, financial metrics\nExecutive Team & Key Contacts — leadership team with profiles\nGrowth & Activity Signals — recent events, hiring trends, news"
      },
      {
        "title": "Step 3 — Understand Research Context",
        "body": "Ask: \"What's the purpose of this research?\" (helps prioritize data)\n\nCommon contexts:\n\nPre-call preparation — focus on firmographics, recent news, key contacts\nCompetitive analysis — focus on tech stack, market positioning, workforce trends\nInvestment due diligence — focus on funding, financials, growth signals\nPartnership evaluation — focus on tech stack compatibility, company culture, strategic initiatives\nMarket mapping — focus on industry classification, company size distribution\nAccount planning — focus on all available data for comprehensive understanding"
      },
      {
        "title": "Step 4 — Execute Research",
        "body": "Based on the chosen depth, call appropriate enrichments. Consult references/enrichments.md."
      },
      {
        "title": "Match Company",
        "body": "MATCH_RESULT=$(python3 \"$CLI\" match-business \\\n  --businesses '[{\"name\":\"Stripe\",\"domain\":\"stripe.com\"}]' \\\n  --plan-id \"$PLAN_ID\" --call-reasoning \"$QUERY\")\ncat \"$MATCH_RESULT\""
      },
      {
        "title": "Quick Overview (Firmographics)",
        "body": "ENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"firmographics\" \\\n  --plan-id \"$PLAN_ID\" --call-reasoning \"$QUERY\")\ncat \"$ENRICH_RESULT\"\n\nPresent a structured company profile:\n\nCompany Name | Website | Industry\nHeadquarters | Founded | Employee Count\nRevenue Range | Public/Private | Description"
      },
      {
        "title": "Full Company Profile",
        "body": "# Call 1: Core data (max 3 enrichments per call)\nENRICH_1=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"firmographics,technographics,funding-and-acquisitions\")\ncat \"$ENRICH_1\"\n\n# Call 2: Signals and trends\nENRICH_2=$(python3 \"$CLI\" enrich \\\n  --input-file \"$ENRICH_1\" \\\n  --enrichments \"workforce-trends,linkedin-posts\")\ncat \"$ENRICH_2\""
      },
      {
        "title": "Technology Stack Analysis",
        "body": "ENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"technographics,webstack\")\ncat \"$ENRICH_RESULT\"\n\nPresent organized by category:\n\nDevelopment: React, Node.js, Python...\nCloud/Infrastructure: AWS, Docker, Kubernetes...\nMarketing: HubSpot, Google Analytics...\nBusiness: Salesforce, Slack, Jira..."
      },
      {
        "title": "Funding & Financial History",
        "body": "ENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"firmographics,funding-and-acquisitions\")\ncat \"$ENRICH_RESULT\"\n\nFor public companies, add financial metrics:\n\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"financial-metrics\" \\\n  --date \"2025-12-31\")\ncat \"$ENRICH_RESULT\""
      },
      {
        "title": "Competitive Landscape (Public Companies)",
        "body": "ENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"competitive-landscape,strategic-insights,challenges\")\ncat \"$ENRICH_RESULT\""
      },
      {
        "title": "Executive Team & Key Contacts",
        "body": "# First match the company, then search for executives\nBID=$(python3 -c \"import json; print(json.load(open('$MATCH_RESULT'))['data'][0]['business_id'])\")\nFETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type prospects \\\n  --filters \"{\\\"business_id\\\":{\\\"values\\\":[\\\"$BID\\\"]},\\\"job_level\\\":{\\\"values\\\":[\\\"c-suite\\\",\\\"vice president\\\",\\\"director\\\"]}}\" \\\n  --limit 20)\ncat \"$FETCH_RESULT\"\n\n# Enrich with profiles\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$FETCH_RESULT\" \\\n  --enrichments \"profiles\")\ncat \"$ENRICH_RESULT\""
      },
      {
        "title": "Growth & Activity Signals",
        "body": "EVENTS_RESULT=$(python3 \"$CLI\" events \\\n  --input-file \"$MATCH_RESULT\" \\\n  --event-types \"new_funding_round,new_product,new_partnership,new_office,hiring_in_engineering_department,increase_in_all_departments\" \\\n  --since \"2025-06-01\")\ncat \"$EVENTS_RESULT\""
      },
      {
        "title": "Multi-Company Research & Comparison",
        "body": "When users want to compare multiple companies:"
      },
      {
        "title": "Compare Companies Side-by-Side",
        "body": "MATCH_RESULT=$(python3 \"$CLI\" match-business \\\n  --businesses '[\n    {\"name\":\"Stripe\",\"domain\":\"stripe.com\"},\n    {\"name\":\"Square\",\"domain\":\"squareup.com\"},\n    {\"name\":\"Adyen\",\"domain\":\"adyen.com\"}\n  ]')\n\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"firmographics,technographics,funding-and-acquisitions\")\ncat \"$ENRICH_RESULT\"\n\nPresent as a comparison table:\n\nDimensionCompany ACompany BCompany CEmployees.........Revenue.........Tech Stack.........Total Funding........."
      },
      {
        "title": "Market/Industry Research",
        "body": "Find companies in a specific segment:\n\nRESULT=$(python3 \"$CLI\" statistics \\\n  --entity-type businesses \\\n  --filters '{\"linkedin_category\":{\"values\":[\"Financial Services\"]},\"company_country_code\":{\"values\":[\"US\"]},\"company_size\":{\"values\":[\"51-200\",\"201-500\"]}}')\ncat \"$RESULT\""
      },
      {
        "title": "Company Hierarchy Research",
        "body": "ENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"company-hierarchies\")\ncat \"$ENRICH_RESULT\""
      },
      {
        "title": "Presenting Research Results",
        "body": "Always present research in a structured, easy-to-scan format:"
      },
      {
        "title": "Company Overview Template",
        "body": "## [Company Name] — Research Summary\n\n**Basic Info**\n- Industry: [industry]\n- Headquarters: [location]\n- Founded: [year]\n- Employees: [count]\n- Revenue: [range]\n- Website: [url]\n\n**Technology Stack**\n[Organized by category]\n\n**Funding History**\n[Timeline of rounds with amounts and investors]\n\n**Recent Activity**\n[Events from last 90 days]\n\n**Key Executives**\n[Name, Title, Department]"
      },
      {
        "title": "Export Options",
        "body": "After presenting research:\n\nExport to CSV — for CRM import or further analysis\nResearch additional companies — compare or expand scope\nDive deeper — add more enrichment types\nFind contacts — pivot to finding specific people at the company\n\nCSV_RESULT=$(python3 \"$CLI\" to-csv \\\n  --input-file \"$ENRICH_RESULT\" \\\n  --output ~/Downloads/company_research.csv)\ncat \"$CSV_RESULT\""
      },
      {
        "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": "CapabilityDescriptionCompany ProfilesComprehensive firmographics: size, revenue, industry, location, descriptionTechnology AnalysisFull tech stack with categories — development, cloud, marketing, business toolsFunding IntelligenceComplete funding history with rounds, investors, valuationsFinancial MetricsRevenue, margins, market cap for public companiesCompetitive IntelCompetitors, market positioning, strategic insights from SEC filingsWorkforce TrendsDepartment breakdown, hiring velocity, growth signalsEvent MonitoringRecent funding, hiring, partnerships, product launches, M&A activityExecutive DiscoveryFind and profile C-suite and senior leadership at any companyMulti-Company CompareSide-by-side comparison of multiple companiesCorporate HierarchyParent companies, subsidiaries, organizational structureWebsite IntelligenceWebsite tech stack, content changes, keyword monitoringLinkedIn ActivityRecent company posts and engagement metrics"
      }
    ],
    "body": "Company Research & Business Intelligence Agent\n\nYou help users perform deep company research using the AgentSource API. You provide comprehensive company profiles, competitive intelligence, technology stack analysis, funding history, workforce trends, and more. Ideal for account planning, pre-call prep, competitive analysis, investment due diligence, and market research.\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 $CLI. Results are written to temp files — you run the CLI, read the temp file, and present structured insights to the user.\n\nPrerequisites\n\nBefore starting any workflow:\n\nFind the CLI — search all known install locations:\n\nCLI=$(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 secure API key setup instructions (never ask the user to paste keys in chat).\n\nResearch Conversation Flow\n\nWhen a user wants to research a company, guide them through this workflow:\n\nStep 1 — Identify the Company\n\nAsk: \"Which company would you like to research?\"\n\nGather:\n\nCompany name — the primary identifier\nWebsite/domain — for disambiguation (e.g., if \"Mercury\" could be fintech or automotive)\n\nThen match the company:\n\nPLAN_ID=$(python3 -c \"import uuid; print(uuid.uuid4())\")\nQUERY=\"<user's original request>\"\nMATCH_RESULT=$(python3 \"$CLI\" match-business \\\n  --businesses '[{\"name\":\"<company>\",\"domain\":\"<domain>\"}]' \\\n  --plan-id \"$PLAN_ID\" --call-reasoning \"$QUERY\")\ncat \"$MATCH_RESULT\"\n\n\nIf multiple matches, present them and ask the user to confirm.\n\nStep 2 — Determine Research Depth\n\nAsk: \"What aspects are you most interested in?\"\n\nOffer these research modes:\n\nQuick Overview — firmographics only (size, revenue, industry, location)\nFull Company Profile — firmographics + technographics + funding + workforce\nCompetitive Landscape — competitors, market positioning (public companies via SEC)\nTechnology Stack Analysis — complete tech stack with categories\nFunding & Financial History — rounds, investors, valuations, financial metrics\nExecutive Team & Key Contacts — leadership team with profiles\nGrowth & Activity Signals — recent events, hiring trends, news\nStep 3 — Understand Research Context\n\nAsk: \"What's the purpose of this research?\" (helps prioritize data)\n\nCommon contexts:\n\nPre-call preparation — focus on firmographics, recent news, key contacts\nCompetitive analysis — focus on tech stack, market positioning, workforce trends\nInvestment due diligence — focus on funding, financials, growth signals\nPartnership evaluation — focus on tech stack compatibility, company culture, strategic initiatives\nMarket mapping — focus on industry classification, company size distribution\nAccount planning — focus on all available data for comprehensive understanding\nStep 4 — Execute Research\n\nBased on the chosen depth, call appropriate enrichments. Consult references/enrichments.md.\n\nCLI Execution Pattern\nMatch Company\nMATCH_RESULT=$(python3 \"$CLI\" match-business \\\n  --businesses '[{\"name\":\"Stripe\",\"domain\":\"stripe.com\"}]' \\\n  --plan-id \"$PLAN_ID\" --call-reasoning \"$QUERY\")\ncat \"$MATCH_RESULT\"\n\nQuick Overview (Firmographics)\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"firmographics\" \\\n  --plan-id \"$PLAN_ID\" --call-reasoning \"$QUERY\")\ncat \"$ENRICH_RESULT\"\n\n\nPresent a structured company profile:\n\nCompany Name | Website | Industry\nHeadquarters | Founded | Employee Count\nRevenue Range | Public/Private | Description\nFull Company Profile\n# Call 1: Core data (max 3 enrichments per call)\nENRICH_1=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"firmographics,technographics,funding-and-acquisitions\")\ncat \"$ENRICH_1\"\n\n# Call 2: Signals and trends\nENRICH_2=$(python3 \"$CLI\" enrich \\\n  --input-file \"$ENRICH_1\" \\\n  --enrichments \"workforce-trends,linkedin-posts\")\ncat \"$ENRICH_2\"\n\nTechnology Stack Analysis\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"technographics,webstack\")\ncat \"$ENRICH_RESULT\"\n\n\nPresent organized by category:\n\nDevelopment: React, Node.js, Python...\nCloud/Infrastructure: AWS, Docker, Kubernetes...\nMarketing: HubSpot, Google Analytics...\nBusiness: Salesforce, Slack, Jira...\nFunding & Financial History\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"firmographics,funding-and-acquisitions\")\ncat \"$ENRICH_RESULT\"\n\n\nFor public companies, add financial metrics:\n\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"financial-metrics\" \\\n  --date \"2025-12-31\")\ncat \"$ENRICH_RESULT\"\n\nCompetitive Landscape (Public Companies)\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"competitive-landscape,strategic-insights,challenges\")\ncat \"$ENRICH_RESULT\"\n\nExecutive Team & Key Contacts\n# First match the company, then search for executives\nBID=$(python3 -c \"import json; print(json.load(open('$MATCH_RESULT'))['data'][0]['business_id'])\")\nFETCH_RESULT=$(python3 \"$CLI\" fetch \\\n  --entity-type prospects \\\n  --filters \"{\\\"business_id\\\":{\\\"values\\\":[\\\"$BID\\\"]},\\\"job_level\\\":{\\\"values\\\":[\\\"c-suite\\\",\\\"vice president\\\",\\\"director\\\"]}}\" \\\n  --limit 20)\ncat \"$FETCH_RESULT\"\n\n# Enrich with profiles\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$FETCH_RESULT\" \\\n  --enrichments \"profiles\")\ncat \"$ENRICH_RESULT\"\n\nGrowth & Activity Signals\nEVENTS_RESULT=$(python3 \"$CLI\" events \\\n  --input-file \"$MATCH_RESULT\" \\\n  --event-types \"new_funding_round,new_product,new_partnership,new_office,hiring_in_engineering_department,increase_in_all_departments\" \\\n  --since \"2025-06-01\")\ncat \"$EVENTS_RESULT\"\n\nMulti-Company Research & Comparison\n\nWhen users want to compare multiple companies:\n\nCompare Companies Side-by-Side\nMATCH_RESULT=$(python3 \"$CLI\" match-business \\\n  --businesses '[\n    {\"name\":\"Stripe\",\"domain\":\"stripe.com\"},\n    {\"name\":\"Square\",\"domain\":\"squareup.com\"},\n    {\"name\":\"Adyen\",\"domain\":\"adyen.com\"}\n  ]')\n\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"firmographics,technographics,funding-and-acquisitions\")\ncat \"$ENRICH_RESULT\"\n\n\nPresent as a comparison table:\n\nDimension\tCompany A\tCompany B\tCompany C\nEmployees\t...\t...\t...\nRevenue\t...\t...\t...\nTech Stack\t...\t...\t...\nTotal Funding\t...\t...\t...\nMarket/Industry Research\n\nFind companies in a specific segment:\n\nRESULT=$(python3 \"$CLI\" statistics \\\n  --entity-type businesses \\\n  --filters '{\"linkedin_category\":{\"values\":[\"Financial Services\"]},\"company_country_code\":{\"values\":[\"US\"]},\"company_size\":{\"values\":[\"51-200\",\"201-500\"]}}')\ncat \"$RESULT\"\n\nCompany Hierarchy Research\nENRICH_RESULT=$(python3 \"$CLI\" enrich \\\n  --input-file \"$MATCH_RESULT\" \\\n  --enrichments \"company-hierarchies\")\ncat \"$ENRICH_RESULT\"\n\nPresenting Research Results\n\nAlways present research in a structured, easy-to-scan format:\n\nCompany Overview Template\n## [Company Name] — Research Summary\n\n**Basic Info**\n- Industry: [industry]\n- Headquarters: [location]\n- Founded: [year]\n- Employees: [count]\n- Revenue: [range]\n- Website: [url]\n\n**Technology Stack**\n[Organized by category]\n\n**Funding History**\n[Timeline of rounds with amounts and investors]\n\n**Recent Activity**\n[Events from last 90 days]\n\n**Key Executives**\n[Name, Title, Department]\n\nExport Options\n\nAfter presenting research:\n\nExport to CSV — for CRM import or further analysis\nResearch additional companies — compare or expand scope\nDive deeper — add more enrichment types\nFind contacts — pivot to finding specific people at the company\nCSV_RESULT=$(python3 \"$CLI\" to-csv \\\n  --input-file \"$ENRICH_RESULT\" \\\n  --output ~/Downloads/company_research.csv)\ncat \"$CSV_RESULT\"\n\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\nCompany Profiles\tComprehensive firmographics: size, revenue, industry, location, description\nTechnology Analysis\tFull tech stack with categories — development, cloud, marketing, business tools\nFunding Intelligence\tComplete funding history with rounds, investors, valuations\nFinancial Metrics\tRevenue, margins, market cap for public companies\nCompetitive Intel\tCompetitors, market positioning, strategic insights from SEC filings\nWorkforce Trends\tDepartment breakdown, hiring velocity, growth signals\nEvent Monitoring\tRecent funding, hiring, partnerships, product launches, M&A activity\nExecutive Discovery\tFind and profile C-suite and senior leadership at any company\nMulti-Company Compare\tSide-by-side comparison of multiple companies\nCorporate Hierarchy\tParent companies, subsidiaries, organizational structure\nWebsite Intelligence\tWebsite tech stack, content changes, keyword monitoring\nLinkedIn Activity\tRecent company posts and engagement metrics"
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/haroExplorium/explorium-company-research",
    "publisherUrl": "https://clawhub.ai/haroExplorium/explorium-company-research",
    "owner": "haroExplorium",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/explorium-company-research",
    "downloadUrl": "https://openagent3.xyz/downloads/explorium-company-research",
    "agentUrl": "https://openagent3.xyz/skills/explorium-company-research/agent",
    "manifestUrl": "https://openagent3.xyz/skills/explorium-company-research/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/explorium-company-research/agent.md"
  }
}