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credit-analysis

Calculate default probabilities and credit risk for bonds and issuers.

15|2|Updated May 1, 2026
Search Tags:#finance#risk#rating#default#credit#bond
One-click install
npx skills add https://github.com/OpenSucker/OpenSucker --skill credit-analysis-opensucker
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: credit-analysis
Source: https://github.com/OpenSucker/OpenSucker/tree/main/skills/vibe_skills/credit-analysis
Command: npx skills add https://github.com/OpenSucker/OpenSucker --skill credit-analysis-opensucker

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps users analyze and evaluate the creditworthiness of bonds and issuers, enabling informed investment decisions.

Core Features & Use Cases

  • Credit Risk Assessment: Evaluate corporate and government bond ratings, default probabilities, and credit spreads.
  • Financial Modeling: Apply Altman Z-Score, Merton, and KMV models to forecast potential defaults and financial distress.
  • Use Case: An investor wants to assess the default risk of a municipal bond; this Skill provides the necessary models and calculations for a comprehensive analysis.

Quick Start

Use the credit-analysis skill to compute the default probability of a company with given financial data.

Frequently Asked Questions about credit-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate bond default probability for corporate and municipal issuers?▼

Altman Z-Score and Merton models are used for financial modeling to forecast potential defaults and financial distress. You apply these models to corporate and government bond issuers to evaluate their creditworthiness and default probability.

What is the best way to assess corporate bond credit risk and credit spreads?▼

Assessing credit risk involves evaluating corporate and government bond ratings, default probabilities, and credit spreads. This comprehensive analysis supports informed investment decisions and ongoing risk management for bond portfolios.

Can I use the KMV model to forecast financial distress for municipal bonds?▼

Yes, you can use the KMV model to forecast financial distress for municipal bonds. The analysis applies financial modeling to evaluate issuer creditworthiness, requiring applicable models and financial data inputs for accurate assessment.

Do I need historical financial data inputs to evaluate bond ratings?▼

Yes, you need financial data inputs to evaluate bond ratings accurately. The credit risk assessment process requires applicable models and financial data inputs to compute default probabilities and perform comprehensive issuer analysis.

What are the limitations of using the Merton model for credit risk analysis?▼

The primary limitation is that accurate assessment requires specific financial data inputs and applicable models. Without complete financial data, the Merton model and other credit risk evaluations may not accurately forecast default probabilities.

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