Financial Report Analyzer Skill

Core Workflow

1. Data Extraction and Structuring:
   • Use the

     execute_skill_script_file

     tool to run the

     scripts/extract_financials.py

     script, passing in the financial report file path (the

     file_path

     parameter), to automatically extract core values such as revenue, net profit, assets, liabilities, etc.
   • The script supports PDF files (parsed via pdfplumber) and plain text files, returning structured data in JSON format.
2. Financial Ratio Calculation:
   • Use

     execute_skill_script_file

     to run

     scripts/calculate_ratios.py

     , passing in the JSON data from Step 1.
   • Automatically calculate key indicators such as gross profit margin, net profit margin, ROE, asset-liability ratio, etc., outputting 30 template placeholder key-value pairs.
   • Refer to

     references/financial_metrics.md

     to ensure the accuracy of indicator definitions.
   • The system will automatically save the returned JSON result (

     react_state["ratio_data"]

     ), which will be automatically merged by the html_interpreter later.
3. Chart Generation:
   • Use

     execute_skill_script_file

     to run

     scripts/generate_charts.py

     , passing in the JSON data from Step 1.
   • Automatically generate 3 visual charts:

     • financial_overview.png

       : Bar chart comparing core financial indicators

     • profitability.png

       : Horizontal bar chart of profitability indicators

     • asset_structure.png

       : Donut chart of asset structure
   • The system will automatically copy the images to the static directory and record the URL mapping (

     react_state["image_url_map"]

     ), which will be automatically merged by the html_interpreter later.
4. In-depth Analysis:
   • Follow the framework provided in

     references/analysis_framework.md

     to conduct in-depth analysis from four dimensions: profit quality, solvency risk, operational efficiency and cash flow.
   • Combine the "Management Discussion and Analysis" section to explain the core driving factors of performance changes.
   • Write the following 7 sections of analysis text:

     • PROFITABILITY_ANALYSIS

       : Profitability Analysis

     • SOLVENCY_ANALYSIS

       : Solvency and Risk Analysis

     • EFFICIENCY_ANALYSIS

       : Operational Efficiency Analysis

     • CASHFLOW_ANALYSIS

       : Cash Flow and Profit Quality Analysis

     • ADVANTAGES_LIST

       : List of Core Advantages (in HTML

       <li>

       format)

     • RISKS_LIST

       : List of Main Risks (in HTML

       <li>

       format)

     • OVERALL_ASSESSMENT

       : Comprehensive Assessment
5. Report Rendering:
   • Call

     html_interpreter

     using the

     template_path

     mode:
     json

     {
       "template_path": "financial-report-analyzer/templates/report_template.html",
       "data": {
         "PROFITABILITY_ANALYSIS": "Profitability analysis written by LLM...",
         "SOLVENCY_ANALYSIS": "Solvency analysis written by LLM...",
         "EFFICIENCY_ANALYSIS": "Operational efficiency analysis written by LLM...",
         "CASHFLOW_ANALYSIS": "Cash flow analysis written by LLM...",
         "ADVANTAGES_LIST": "<li>Advantage 1</li><li>Advantage 2</li>",
         "RISKS_LIST": "<li>Risk 1</li><li>Risk 2</li>",
         "OVERALL_ASSESSMENT": "Comprehensive assessment written by LLM..."
       },
       "title": "XX Company 2023 Annual Financial Report Analysis"
     }

   • Important: Only pass the 7 sections of analysis text in the

     data

     dictionary! The backend will automatically merge:
     • 30 data indicators from Step 2 (COMPANY_NAME, REVENUE, NET_PROFIT, etc.)
     • Chart URLs from Step 3 (CHART_FINANCIAL_OVERVIEW, CHART_PROFITABILITY, CHART_ASSET_STRUCTURE)
   • Never include data indicators or chart paths in

     data

     , otherwise the JSON will be too large and cause truncation.
6. Completion:
   • Call

     terminate

     to return a short summary of 1-2 sentences.
   • The report will be displayed as a card in the left panel, and users can click the card to view the full report in the right panel.

Complete Workflow Example

Step 1: execute_skill_script_file(skill_name="financial-report-analyzer", script_file_name="extract_financials.py", args={"file_path": "/path/to/report.pdf"})
  → Returns JSON: {"revenue": 10500000000, "net_profit": 1200000000, ...}  (recorded as raw_data)

Step 2: execute_skill_script_file(skill_name="financial-report-analyzer", script_file_name="calculate_ratios.py", args=<raw_data>)
  → Returns 30 template key-value pairs, which are automatically recorded to react_state["ratio_data"] by the system

Step 3: execute_skill_script_file(skill_name="financial-report-analyzer", script_file_name="generate_charts.py", args=<raw_data>)
  → Generates charts, the system automatically copies them to /images/ and records the URL mapping

Step 4: (LLM writes 7 sections of in-depth analysis text on its own)

Step 5: html_interpreter(template_path="financial-report-analyzer/templates/report_template.html", data={contains only 7 sections of analysis text}, title="Report Title")
  → Backend automatically merges data indicators + chart URLs + analysis text to render the complete report

Step 6: terminate(result="Short summary")

Resource Usage Instructions

• Scripts (all executed via

  execute_skill_script_file

  ):

  • scripts/extract_financials.py

    : Accepts the

    file_path

    parameter, reads financial report files (supports PDF and text formats), and extracts core financial data.

  • scripts/calculate_ratios.py

    : Calculates financial ratios and outputs 30 template placeholder key-value pairs. The system automatically records the results.

  • scripts/generate_charts.py

    : Generates 3 visual charts (using matplotlib), and the system automatically handles image copying.

  • scripts/fill_template.py

    : (Backup) Accepts three parameters

    ratio_data

    ,

    chart_paths

    ,

    analysis

    , reads the HTML template and replaces all placeholders. Normally, this script does not need to be used because the template_path mode of html_interpreter will automatically complete template filling.
• References:

  • references/financial_metrics.md

    : Contains formula definitions.

  • references/analysis_framework.md

    : Contains analysis logic.
• Templates:

  • templates/report_template.html

    : HTML template for the final delivered report (must be strictly followed, do not delete sections or modify table structures). It is automatically read and filled by the template_path parameter of html_interpreter.

  • templates/report_template.md

    : Markdown version, for structural reference only.

Notes

• Must use

  execute_skill_script_file

  to run scripts (do not use shell_interpreter), because

  execute_skill_script_file

  will automatically handle image copying and data recording.
• Script extraction may be affected by typesetting, so it is recommended to manually verify the extracted key values before calculation.
• Always pay attention to "non-recurring gains and losses" to evaluate the real profitability of the company's core business.
• Compare at least three years of historical data to identify trends.

• generate_charts.py

  depends on matplotlib, please ensure that this library is installed in the environment.