financial-reporting

Purpose

This skill enables the generation and analysis of financial reports by aggregating data, creating visualizations, and ensuring compliance with standards like GAAP or IFRS. It processes financial datasets to produce actionable insights for reporting tasks.

When to Use

Use this skill for quarterly financial summaries, annual audits, compliance checks, or ad-hoc analyses of income statements and balance sheets. Apply it when integrating with accounting software or when visualizing trends in financial metrics.

Key Capabilities

• Data aggregation: Pulls data from sources via API endpoint /api/v1/aggregate?start_date=2023-01-01&end_date=2023-12-31, supporting filters for accounts and currencies.
• Visualization: Generates charts using libraries like Matplotlib; e.g., creates a pie chart for expense breakdown with plot_type='pie'&data_source='expenses'.
• Compliance tools: Checks reports against rules, such as validating totals with compliance_check('GAAP', report_data), returning boolean results.
• Analysis functions: Performs ratio analysis, e.g., calculate_ratio('debt_to_equity', balance_sheet_data), outputting a float value.
• Export formats: Supports JSON, CSV, or PDF output; configure with export_format='PDF'&file_path='/reports/q1.pdf'.

Usage Patterns

To use this skill, import the module in Python scripts or call via CLI. Start by authenticating with $FINANCIAL_API_KEY, then aggregate data before analysis. For scripts, wrap calls in try-except blocks for error resilience. Common pattern: Fetch data, process it, visualize, and export. Example workflow: aggregate_data() -> analyze_data() -> generate_report().