resolve-design-errors

Detect and root-cause design errors in Simulink models using SLDV Design Error Detection.

1.0k|98|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/matlab/simulink-agentic-toolkit --skill resolve-design-errors
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: resolve-design-errors
Source: https://github.com/matlab/simulink-agentic-toolkit/tree/main/skills-catalog/verification-validation-and-test/resolve-design-errors
Command: npx skills add https://github.com/matlab/simulink-agentic-toolkit --skill resolve-design-errors

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Simulink models can contain hidden design errors such as division-by-zero, integer overflow, dead logic, and out-of-bounds array access that are hard to find manually. This Skill runs Simulink Design Verifier's Design Error Detection, performs root cause analysis on every finding, and guides a safe clone-fix-verify workflow.

Core Features & Use Cases

  • Automated defect detection: Runs SLDV Design Error Detection via sldv_run_defect_checker, with automatic caching of prior analysis results.
  • Root cause analysis: Uses sldv_find_de_root_cause to produce backward slices, counterexamples, locality (blast-radius) scores, and shared-root cascade annotations for each finding.
  • Dead logic classification: Classifies dead logic as intentional (defensive logic, negation guards) versus design error using a built-in pattern catalog, then proposes ranked fix options.
  • Use Case: An engineer suspects unreachable logic in a controller model. The Skill runs DED, traces each defect to its root cause block, classifies findings against known patterns, and proposes fixes that are applied only to a cloned model after explicit user approval.

Quick Start

Ask the agent to run design error detection on your Simulink model and explain the root cause of any findings.

Frequently Asked Questions about resolve-design-errors

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

FAQPage Schema
How do I find design errors in a Simulink model?

Run Design Error Detection with Simulink Design Verifier, which scans for division-by-zero, integer overflow, dead logic, and out-of-bounds array access. This Skill automates the scan via sldv_run_defect_checker and reports each finding with its block path and defect type.

How do I find the root cause of dead logic in Simulink?

Use sldv_find_de_root_cause on a failed DED result to get backward slices, counterexample input values, and locality scores for each finding. Trace the counterexample through the slice blocks to identify which block produces the defect-triggering value.

What products are required for Simulink Design Error Detection?

You need MATLAB R2023b or later with Simulink, Simulink Design Verifier, and Simulink Check (Model Slicer). The Skill runs through the MATLAB MCP Server tools such as evaluate_matlab_code and model_read.

Does a passing Design Error Detection result mean my model is error-free?

No. DED is a quick scan for a fixed set of defect classes, not an exhaustive proof. A pass means no defects of the checked types were found; it does not cover requirement violations, functional bugs, or Inf/NaN issues.

Is dead logic in Simulink always a bug?

No. Dead logic can be intentional, such as defensive conditions in library blocks or mutually exclusive Stateflow guards. The Skill classifies each finding against a pattern catalog as intentional, design_error, or unclassified before proposing any fix.

Will the Skill modify my original Simulink model when fixing defects?

No. Fixes are never applied to the original model. The workflow clones the model first, presents root cause findings and ranked fix options, and only applies changes after explicit user approval, followed by re-running DED to verify.