AI Runtime Error Solver
Diagnose and resolve runtime errors instantly
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Why did code that compiled, passed review and ran fine all week throw at half past two this morning? Nothing changed, did it?
Runtime errors are the ones the compiler cannot catch, because they depend on values rather than syntax. A field is null that never was before. A list is empty. A response arrives in a shape nobody documented. The AI Runtime Error Solver reads the failure and the code together and works out which value broke the assumption.
Short answer: The AI Runtime Error Solver is a free AIToolsay tool that diagnoses errors that only appear when code runs. Paste the code and the error, and it identifies the root cause, returns corrected code, suggests how to prevent it and can write a test that reproduces the failure.
What is AI Runtime Error Solver?
Runtime errors are failures of assumption. Something in the code expected a value to exist, to be a certain type, to be within a range, and it was not.
The prompt box asks you to paste the code and the error or behaviour you are seeing. Unlike a syntax problem, the error message here rarely points at the real fault. The line that threw is where the bad value arrived, not where it came from.
That is the gap this tool works in. It reads the failing line, then reasons backwards through the code you pasted to find where the assumption was actually broken.
Why Use AI Runtime Error Solver?
The instinct with a runtime error is to add a check at the line that threw. That stops the error and leaves the bug, which now fails silently somewhere further along.
Working out whether the value should have existed is the real question, and it is a question about intent rather than syntax. Turning Explain Root Cause on gives you the reasoning, which is what lets you decide between guarding the value and fixing where it came from.
| Error | The quick fix | The question worth asking |
|---|---|---|
| Null reference | Add a null check | Why is it null here when it never was before? |
| Index out of range | Check the length first | Why is the list shorter than the code assumed? |
| Type error on a response field | Cast it | Did the upstream contract change? |
| Division by zero | Guard the denominator | Is zero a legitimate value or a data problem? |
Note Include the input that caused the failure if you have it. A runtime error is a function of the data, and the value that broke it is the single most useful thing you can paste.
How Does AI Runtime Error Solver Work?
Prompt box. Paste the code and the error or behaviour you are seeing, plus the input if you can get it.
Model selector. Choose the engine up front, from MSB AI, OpenAI ChatGPT, Google Gemini, Anthropic Claude AI, xAI Grok AI, DeepSeek, Qwen, Meta AI, NVIDIA AI, OpenRouter AI and MiniMax.
Advanced options accordion. Ten controls in total: Language, Issue Type, Analysis Depth and Output as dropdowns, four toggles, a Thoroughness slider and a free text field.
Generate button. Code, error, model and settings run through the prompt engineering layer written for debugging, which is the instruction set that makes it trace a value backwards rather than restate the message.
Output card. The diagnosis and fix appear under the button with a live word count, plus copy, listen, reuse, download and open in full view.
Export row. DOC, TXT and HTML on every result. DOC when the explanation is going into a ticket, TXT when you want the corrected code.
Activity history. Session generations stay listed under the result, so a first diagnosis and a second pass with more context sit side by side.
Step-by-Step Guide
- Capture the error message and the line it points at.
- Copy the failing function and anything that produces the value it received.
- Open the AI Runtime Error Solver and paste both, error first.
- Add the input value that triggered it, redacted if it contains anything sensitive.
- Set Issue Type to Runtime Error and Language to your language.
- Set Output to Root Cause and leave Provide Fixed Code off for the first run.
- Read the cause and decide whether the value should exist at all.
- Turn Provide Fixed Code and Show Test to Reproduce on, then generate the version you will actually use.
Key Features
Backwards reasoning
Finds where the bad value came from rather than stopping at the line that threw.
Guard or fix
The explanation gives you enough to choose between defending the line and correcting the source.
A reproducing test
Show Test to Reproduce turns an intermittent production error into something that fails on demand.
Prevention advice
Suggest Prevention covers the class of error, not only this instance of it.
Advanced Options Guide
| Option | What it controls | When to change it | Suggested start |
|---|---|---|---|
| Language | Auto Detect, Python, JavaScript, TypeScript, Java, C#, C++, Go, PHP or Ruby | Set it, since null and type behaviour differ sharply between languages | Your language |
| Issue Type | Auto Detect, Syntax Error, Runtime Error, Logic Bug, Performance, Memory Leak, Exception or Crash | Runtime Error is the setting for this tool's core case | Runtime Error |
| Analysis Depth | Quick, Standard or Deep | Deep when the value passes through several functions before failing | Standard, then Deep if the cause is not obvious |
| Output | Fix + Explanation, Corrected Code, Root Cause or Step by Step Debug | Step by Step Debug when the failure is intermittent and you need a plan | Root Cause first |
| Explain Root Cause | Adds the reasoning connecting the bad value to its origin | Leave on. Without it you get a patch, not a diagnosis | On |
| Provide Fixed Code | Returns the corrected implementation | Turn off until you agree with the cause | Off first, on second |
| Suggest Prevention | Suggests type hints, validation or contracts that would stop the class of error | Leave on for anything that reached production | On |
| Show Test to Reproduce | Writes a test that triggers the same error | Turn on for intermittent failures. Reproducibility is most of the work | On |
| Thoroughness | Slider from 1 to 100 setting how far back through the code it reasons | Raise it when the value crosses a boundary such as a queue or an API | 65 |
| Custom Instructions | Free text up to 1000 characters over the settings | Use it for the conditions the code cannot show | "Only fails under load, roughly one request in a thousand" |
Caution Adding a null check because a null appeared is not a fix, it is a silence. Ask whether that value should ever have been null. If the answer is no, the bug is upstream and the check will hide it until something worse happens.
Example Outputs
Input: a function that reads a currency amount from an API response and converts it, failing intermittently with a type error.
Settings: Language TypeScript, Issue Type Runtime Error, Analysis Depth Deep, Output Root Cause, Explain Root Cause on, Show Test to Reproduce on, Thoroughness 70, Custom Instructions "fails for roughly one order in two hundred".
ROOT CAUSE
The amount field is a string in most responses and a number
when the value is zero. The conversion assumes a string and
calls a string method on it.
WHY IT IS INTERMITTENT
Only zero valued orders take the numeric branch, which is
why it looks random. It is deterministic on the input.
...The phrase worth noticing is "it is deterministic on the input". Intermittent bugs are almost never random. They are conditional on data you have not been looking at, and naming the condition is what turns the problem from frightening into ordinary.
Once the cause is clear, the AI Error Fixer handles the correction, and the reproducing test is worth expanding with the AI Unit Test Generator so the whole branch is covered.
Comparison Table
| Approach | Best at | Worst at |
|---|---|---|
| Adding log statements | Confirming a hypothesis | Errors you cannot reproduce locally |
| Stepping through a debugger | Local, reproducible failures | Anything intermittent or in production |
| Searching the error message | Well known library errors | Failures specific to your data |
| AI Runtime Error Solver | Explaining why a value broke an assumption | Failures caused by code you did not paste |
Strengths
- Turning intermittent into conditional, which makes it fixable
- Reasoning backwards from the failing line to the source of the value
- Producing a test that makes the failure repeatable
- Distinguishing a data problem from a code problem
Limits
- It only sees the code you paste, so paste the caller too
- Concurrency failures need the concurrency described
- Environment differences must be stated, not assumed
- ✅ Error message and failing line included
- ✅ The function that produced the value pasted as well
- ✅ The triggering input included and redacted
- ✅ Root cause read before any fix applied
- ✅ A reproducing test written before the change
Pro tip Write your own theory into Custom Instructions before generating. "I think the queue is delivering the same message twice" gives the analysis something specific to confirm or reject, and a rejected theory is often more informative than an open ended diagnosis.
AIToolsay is a free AI tools platform where every tool is a dedicated workspace with its own prompt engineering and its own options panel, instead of one general chat box with many labels. All tools are free to run and none of them need an account. You also select the engine, choosing from MSB AI, OpenAI ChatGPT, Google Gemini, Anthropic Claude AI, xAI Grok AI, DeepSeek, Qwen, Meta AI, NVIDIA AI, OpenRouter AI and MiniMax, and when a bug is stubborn a second engine reading the same code is a cheap second opinion. Beyond the tool suite there is an AI directory, an AI models directory, courses, prompts, guides and news. Everything else is reachable from the AIToolsay homepage.
Frequently Asked Questions
Is the AI Runtime Error Solver free?
Yes. It is free to use, nothing is installed, and no account is needed to run a diagnosis.
What should I paste alongside the error?
The failing function, whatever calls it, and the input that triggered the failure. The caller matters as much as the failing line, because that is usually where the bad value came from.
Can it help with errors I cannot reproduce?
That is its best case. Describe the conditions, such as how often it happens and what is different about those requests, and turn Show Test to Reproduce on. Intermittent failures are almost always conditional on data.
Should I just add a null check?
Only after you know whether the value should have been null. If it should never be null, a check hides a real bug and moves the failure somewhere less obvious.
Does it handle concurrency bugs?
Partly. Say explicitly that multiple threads or processes are involved and describe the shared state, because nothing in the code itself tells the tool that two things run at once.
Is it safe to paste production data?
Redact anything identifying first and replace it with placeholders that keep the shape. The structure of the value is what matters, not the actual contents.
What is the difference between this and the exception analyzer?
This focuses on why a value broke an assumption. The exception analyzer focuses on how errors are raised, caught and handled across your code. Different questions, both worth asking.
Runtime errors feel random because the condition that triggers them is invisible. Paste the code and the caller, include the input, read the cause before the fix, and let the AI Runtime Error Solver turn a mysterious two in the morning failure into a rule you can test for.
Thanks for reading, and I hope tonight is quieter. If this earns a place in your debugging routine, join the AIToolsay community, follow along on social media, turn on push notifications for new tools, and subscribe to the newsletter for the occasional round up.
Let AI Speak.
Sabir
Founder of AIToolsay and a passionate AI enthusiast dedicated to building practical, user-friendly AI tools that simplify everyday tasks.
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