{
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    "slug": "plusefin-analysis",
    "name": "PlusE Financial Analysis",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
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      "SKILL.md",
      "plusefin.py"
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      "Extract the archive and review SKILL.md first.",
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        {
          "label": "Upgrade existing",
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      "primaryActionHref": "/downloads/plusefin-analysis"
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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. 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. Summarize what changed and any follow-up checks I should run."
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "PlusE Financial Analysis",
        "body": "AI-ready financial data research skill with structured research methodology."
      },
      {
        "title": "Setup",
        "body": "export PLUSEFIN_API_KEY=your_api_key"
      },
      {
        "title": "1. Research Setup",
        "body": "Define target (ticker) and time range (6mo / 1y / 2y)\nSet research objective: valuation analysis / technical outlook / event-driven"
      },
      {
        "title": "2. Data Collection",
        "body": "Company Fundamentals: ticker - overview, valuation, ratings\nMarket Sentiment: sentiment / sentiment-history\nOptions Data: options / options-analyze (IV, Greeks, OI)\nInstitutional Holdings: holders - major holders changes\nFinancial Statements: statements (income/balance/cash)\nEarnings & Insider: earnings / insiders\nPrice History: price-history"
      },
      {
        "title": "3. Hypothesis Formation",
        "body": "Based on data, formulate hypotheses:\n\nDirection: Bullish / Bearish / Neutral\nDrivers: Valuation reversion, earnings growth, event catalyst, sentiment reversal"
      },
      {
        "title": "4. Evidence Validation",
        "body": "Use search capabilities to gather research reports, news, announcements\nCross-validate multi-source data timeline consistency\nSeek evidence supporting or refuting hypotheses"
      },
      {
        "title": "5. Valuation Scenarios",
        "body": "Bull Case: Valuation assuming upside catalysts materialize\nBase Case: Valuation based on current market expectations\nBear Case: Valuation assuming downside risks materialize"
      },
      {
        "title": "6. Risk Assessment",
        "body": "Downside risks\nKey assumption risks\nPotential catalysts and triggers"
      },
      {
        "title": "7. Report Output",
        "body": "Structured output:\n\nCore thesis\nEvidence summary\nValuation scenario comparison\nRisk warnings\nActionable recommendations (if applicable)\n\nEach key conclusion must include source citations."
      },
      {
        "title": "Usage",
        "body": "# Set API key\nexport PLUSEFIN_API_KEY=your_api_key\n\n# Run commands\npython plusefin.py <command> [args]"
      },
      {
        "title": "Commands",
        "body": "CommandUsageDescriptiontickerpython plusefin.py ticker <symbol>Company overview, valuation, ratingsprice-historypython plusefin.py price-history <ticker> [period]Historical prices (6mo/1y/2y)sentimentpython plusefin.py sentimentMarket sentiment (Fear & Greed)sentiment-historypython plusefin.py sentiment-history [days]Historical sentimentoptionspython plusefin.py options <symbol> [num]Options chainoptions-analyzepython plusefin.py options-analyze <symbol>Options analysisholderspython plusefin.py holders <symbol>Institutional holdingsstatementspython plusefin.py statements <symbol> [type]Financial statements (income/balance/cash)earningspython plusefin.py earnings <symbol>Earnings historyinsiderspython plusefin.py insiders <symbol>Insider tradingnewspython plusefin.py news <symbol>Stock newsfredpython plusefin.py fred <series_id>Macroeconomic data"
      }
    ],
    "body": "PlusE Financial Analysis\n\nAI-ready financial data research skill with structured research methodology.\n\nSetup\nexport PLUSEFIN_API_KEY=your_api_key\n\nResearch Framework\n1. Research Setup\nDefine target (ticker) and time range (6mo / 1y / 2y)\nSet research objective: valuation analysis / technical outlook / event-driven\n2. Data Collection\nCompany Fundamentals: ticker - overview, valuation, ratings\nMarket Sentiment: sentiment / sentiment-history\nOptions Data: options / options-analyze (IV, Greeks, OI)\nInstitutional Holdings: holders - major holders changes\nFinancial Statements: statements (income/balance/cash)\nEarnings & Insider: earnings / insiders\nPrice History: price-history\n3. Hypothesis Formation\n\nBased on data, formulate hypotheses:\n\nDirection: Bullish / Bearish / Neutral\nDrivers: Valuation reversion, earnings growth, event catalyst, sentiment reversal\n4. Evidence Validation\nUse search capabilities to gather research reports, news, announcements\nCross-validate multi-source data timeline consistency\nSeek evidence supporting or refuting hypotheses\n5. Valuation Scenarios\nBull Case: Valuation assuming upside catalysts materialize\nBase Case: Valuation based on current market expectations\nBear Case: Valuation assuming downside risks materialize\n6. Risk Assessment\nDownside risks\nKey assumption risks\nPotential catalysts and triggers\n7. Report Output\n\nStructured output:\n\nCore thesis\nEvidence summary\nValuation scenario comparison\nRisk warnings\nActionable recommendations (if applicable)\n\nEach key conclusion must include source citations.\n\nUsage\n# Set API key\nexport PLUSEFIN_API_KEY=your_api_key\n\n# Run commands\npython plusefin.py <command> [args]\n\nCommands\nCommand\tUsage\tDescription\nticker\tpython plusefin.py ticker <symbol>\tCompany overview, valuation, ratings\nprice-history\tpython plusefin.py price-history <ticker> [period]\tHistorical prices (6mo/1y/2y)\nsentiment\tpython plusefin.py sentiment\tMarket sentiment (Fear & Greed)\nsentiment-history\tpython plusefin.py sentiment-history [days]\tHistorical sentiment\noptions\tpython plusefin.py options <symbol> [num]\tOptions chain\noptions-analyze\tpython plusefin.py options-analyze <symbol>\tOptions analysis\nholders\tpython plusefin.py holders <symbol>\tInstitutional holdings\nstatements\tpython plusefin.py statements <symbol> [type]\tFinancial statements (income/balance/cash)\nearnings\tpython plusefin.py earnings <symbol>\tEarnings history\ninsiders\tpython plusefin.py insiders <symbol>\tInsider trading\nnews\tpython plusefin.py news <symbol>\tStock news\nfred\tpython plusefin.py fred <series_id>\tMacroeconomic data"
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    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/wanghsinche/plusefin-analysis",
    "publisherUrl": "https://clawhub.ai/wanghsinche/plusefin-analysis",
    "owner": "wanghsinche",
    "version": "1.0.9",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
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