Financial Health Scores

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](references/mcp-setup.md) for installation instructions.

Query Format

Retrieve financial health scores for , 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:

| Metric | Value (USD) | |--------|-------------| | Working Capital | 36,928,000,000 | | Total Assets | 137,806,000,000 | | Retained Earnings | 39,003,000,000 | | EBIT | 5,616,000,000 | | Market Cap | 1,400,635,834,800 | | Total Liabilities | 54,941,000,000 | | Revenue | 94,827,000,000 |

Data Source: octagon-financials-agent

Altman Z-Score Interpretation

The Altman Z-Score predicts bankruptcy probability:

| Z-Score Range | Interpretation | |---------------|----------------| | > 3.0 | Safe Zone - Low bankruptcy risk | | 1.8 - 3.0 | Grey Zone - Moderate risk, needs monitoring | | Net Income (accruals quality)

Leverage/Liquidity (3 points):

1. Lower long-term debt ratio
2. Higher current ratio
3. No new share issuance

Operating Efficiency (2 points):

1. Higher gross margin
2. 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]"

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: OctagonAI
• Source: OctagonAI/skills
• License: MIT
• Homepage: https://octagonai.co

Install and usage instructions live in the source repository linked above.