defeatbeta-analyst

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Comprehensive financial analysis using 60+ data endpoints. Analyze company fundamentals, financial statements, valuation metrics, profitability ratios, growth trends, and industry comparisons. Use for: (1) fundamental analysis and DCF modeling, (2) financial statement analysis, (3) valuation and ratio analysis, (4) growth and profitability assessment, (5) industry benchmarking, or any deep financial research tasks.

Install

mkdir -p .claude/skills/defeatbeta-analyst && curl -L -o skill.zip "https://mcp.directory/api/skills/download/5684" && unzip -o skill.zip -d .claude/skills/defeatbeta-analyst && rm skill.zip

Installs to .claude/skills/defeatbeta-analyst

About this skill

Financial Analyst

Professional-grade financial analysis using historical market data and comprehensive financial metrics from the defeatbeta dataset.

Defaults

Unless the user specifies otherwise:

  • Always call get_latest_data_update_date first — this is "today" for all relative time queries
  • Default analysis: When given only a ticker (e.g., /defeatbeta-analyst AAPL), run Template 1: Quick Investment Screening
  • ROIC and Equity Multiplier: Not applicable to banks/financial institutions — check sector in profile first
  • Date format: "YYYY-MM-DD"
  • Data limits: Price/valuation APIs return max 1000 rows — use date ranges for large datasets

Template Selection

Choose the template that best matches the user's request. Read analysis-templates.md for the full workflow of any template.

User requestTemplate
Quick check / "should I look at this stock?"T1: Quick Investment Screening
Full company deep-diveT2: Full Fundamental Analysis
Overvalued / undervalued / P/E / P/B / DCFT3: Valuation-Focused or T10: DCF Valuation
Revenue growth / earnings quality / ROICT4: Growth Quality Assessment
ROE decomposition / DuPontT5: DuPont Analysis
Margin trends / vs peersT6: Margin Analysis & Peer Comparison
Accruals / FCF quality / working capitalT7: Earnings Quality Assessment
Industry positioningT8: Industry Positioning Analysis
Latest earnings release numbersT9: Quarterly Earnings Analysis
"What did management report this quarter?"T11: Extract Key Financial Data from Earnings Call
"What changed vs last quarter/year?"T12: Financial Metric Changes from Earnings Call
"What is management's guidance/outlook?"T13: Financial Metric Forecasts from Earnings Call
"What does this company do?" / business modelT14: Business Understanding
Revenue segments / geography breakdownT15: Revenue Breakdown
Industry trends / tailwinds / headwindsT16: Industry Context
Competitors / moat / pricing powerT17: Competitive Landscape
Balance sheet strength / debt / FCF qualityT18: Financial Quality
Risks / downside / what could go wrongT19: Risks and Downside
Management track record / capital allocationT20: Management and Execution
Bull case / bear case / scenariosT21: Bull and Bear Scenarios
How to value / valuation assumptionsT22: Valuation Framework
Long-term thesis / why invest / must go rightT23: Long-Term Investment Thesis

API Gotchas

REQUIRED: Before calling any API, read the relevant section in defeatbeta-api-reference.md to confirm the correct parameters and response schema.

  1. Fiscal periods: Earnings transcripts use fiscal periods (may differ from calendar) — specify both fiscal_year and fiscal_quarter
  2. SEC filing access: Must use sec_user_agent field value as User-Agent header when accessing SEC URLs (SEC blocks without it)

Rendering Financial Statements

When displaying results from get_stock_*_income_statement, get_stock_*_balance_sheet, or get_stock_*_cash_flow, you MUST follow these rules. The response contains a statement array where each row has label, indent, is_section, and values fields.

Rules:

  1. Preserve row order — never reorder, skip, or merge rows
  2. Indent — prefix each label with indent × 2 spaces (indent=0 → no prefix, indent=1 → 2 spaces, indent=2 → 4 spaces, etc.)
  3. is_section=true — render the label in bold; this row is a section header and the rows immediately below it (with indent = this.indent + 1) are its children
  4. is_section=false — render the label in normal weight
  5. values[i] corresponds to periods[i]; null means data not available
  6. Do NOT add calculated rows (e.g. margin %) that are not present in the data

Example — given these rows:

labelindentis_section
Total Revenue0true
Operating Revenue1false
Cost of Revenue0false
Operating Expense0true
SG&A1false
R&D1false

Correct rendered output:

Item2025Q42025Q3
Total Revenue10,2709,246
  Operating Revenue10,2709,246
Cost of Revenue4,6934,466
Operating Expense3,8253,510
  SG&A1,1981,069
  R&D2,3302,139

Reference Documentation

Detailed step-by-step workflows (T1–T23)analysis-templates.md

API parameters, response schemas, examples (60+ APIs)defeatbeta-api-reference.md

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