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Financial Health Scores

  • 241 installs
  • 129 repo stars
  • Updated June 5, 2026
  • octagonai/skills

Compute composite financial-health scores from leverage, liquidity, profitability, and cash-flow stability metrics to rank credits and equity survivors in a shortlist.

About

Financial-health-scores skill synthesizes leverage, liquidity, profitability, and cash-generation indicators into comparable health grades for validate-stage screening of equities and credits under stress scenarios.

  • Blends leverage and liquidity ratios
  • Scores cash-flow consistency
  • Highlights distress and covenant risk
  • Ranks peers on health tiers
  • Outputs pass-watch-reject summaries

Financial Health Scores by the numbers

  • 241 all-time installs (skills.sh)
  • +5 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #374 of 1,106 Finance & Trading skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/octagonai/skills --skill financial-health-scores

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Listed on Skillselion
Installs241
repo stars129
Last updatedJune 5, 2026
Repositoryoctagonai/skills

What it does

Compute composite financial-health scores from leverage, liquidity, profitability, and cash-flow stability metrics to rank credits and equity survivors in a shortlist.

Files

SKILL.mdMarkdownGitHub ↗

Financial Health Scores

Retrieve financial health scores including Altman Z-Score and Piotroski Score for public companies using Octagon MCP.

Prerequisites

Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.

Query Format

Retrieve financial health scores for <TICKER>, including the Altman Z-Score and Piotroski Score.

MCP Call:

{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Retrieve financial health scores for TSLA, including the Altman Z-Score and Piotroski Score"
  }
}

Output Format

The agent returns health scores with supporting metrics:

Altman Z-Score: 16.84 (calculated using working capital, total assets, retained earnings, EBIT, and market cap). A score above 3.0 indicates low bankruptcy risk.

Piotroski Score: 6 (out of a maximum 9). This score assesses profitability, leverage, liquidity, and operating efficiency.

Supporting Financial Metrics:

MetricValue (USD)
Working Capital36,928,000,000
Total Assets137,806,000,000
Retained Earnings39,003,000,000
EBIT5,616,000,000
Market Cap1,400,635,834,800
Total Liabilities54,941,000,000
Revenue94,827,000,000

Data Source: octagon-financials-agent

Altman Z-Score Interpretation

The Altman Z-Score predicts bankruptcy probability:

Z-Score RangeInterpretation
> 3.0Safe Zone - Low bankruptcy risk
1.8 - 3.0Grey Zone - Moderate risk, needs monitoring
< 1.8Distress Zone - High bankruptcy risk

Z-Score Formula

Z = 1.2(WC/TA) + 1.4(RE/TA) + 3.3(EBIT/TA) + 0.6(MC/TL) + 1.0(Rev/TA)

Where:

  • WC = Working Capital
  • TA = Total Assets
  • RE = Retained Earnings
  • EBIT = Earnings Before Interest and Taxes
  • MC = Market Cap
  • TL = Total Liabilities
  • Rev = Revenue

Piotroski Score Interpretation

The Piotroski F-Score (0-9) assesses financial strength:

Score RangeInterpretation
8-9Strong - High quality value stock
5-7Moderate - Average financial health
0-4Weak - Poor financial health

Piotroski Components (9 criteria)

Profitability (4 points): 1. Positive Net Income 2. Positive Operating Cash Flow 3. Return on Assets improvement 4. OCF > Net Income (accruals quality)

Leverage/Liquidity (3 points): 5. Lower long-term debt ratio 6. Higher current ratio 7. No new share issuance

Operating Efficiency (2 points): 8. Higher gross margin 9. Higher asset turnover

Analysis Tips

Combined Assessment

Use both scores together:

  • High Z-Score + High Piotroski = Financially healthy
  • High Z-Score + Low Piotroski = Watch operating trends
  • Low Z-Score + High Piotroski = Leverage concern
  • Low Z-Score + Low Piotroski = Avoid or deep value

Value Investing Application

Piotroski Score designed for:

  • Screening high book-to-market stocks
  • Identifying quality within value
  • Avoiding value traps

Credit Analysis

Z-Score useful for:

  • Bond investment decisions
  • Supplier credit assessment
  • Counterparty risk evaluation

Sector Considerations

Scores work best for:

  • Manufacturing companies (Z-Score original use)
  • Mature businesses with stable operations
  • Less reliable for: financials, early-stage, asset-light

Follow-up Queries

Based on results, suggest deeper analysis:

  • "What factors contributed to [COMPANY]'s Piotroski Score versus industry peers?"
  • "How does [COMPANY]'s Altman Z-Score compare to its historical averages?"
  • "Break down the individual components of [COMPANY]'s Piotroski Score"
  • "Compare [COMPANY]'s financial health scores to [PEER1] and [PEER2]"

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