Find the error: how to compose a precise code debugging task
The 'Find the error' tool analyses supplied code and error message, identifies likely causes and suggests a minimal correction. To get a useful answer, it is important to correctly fill in three fields: code and error message, platform or application, context and requirements. In this article we will explain how to compose a precise request, which details are critical, and which will only confuse. We will not discuss general artificial intelligence questions — only the practice of working with this specific tool. You will learn to formulate requests so that the model faster finds the cause of the failure and offers a realistic solution.
Open tool: Code debugger ↗Why precision in the task matters
The model does not see your project, does not run the code and does not have access to documentation. It relies only on the text you enter. If the 'Code and error message' field contains a fragment without context, the answer will be general or incorrect. The more precisely you describe what is happening and what should happen, the higher the chance of getting a minimal fix rather than a module rewritten from scratch.
Precision matters also because the tool returns a single result in text form. You will not have the opportunity to clarify the request in a dialogue. Everything you want to communicate must fit into three fields. Length limits: the first field up to 8000 characters, the second and third up to 1000 characters each. This is enough to describe a typical error, but not enough for the whole project. So learn to highlight the essence.
Bad: 'Code does not work, help me.' Good: 'Python 3.11, script reads CSV and crashes on line 12 with KeyError: date. I expect the date to be taken from the Date column. Here is the code and the traceback'.
Field 'Code and error message': what to include
Insert a minimal reproducible fragment into this field. Do not copy the whole file if the error occurs in one function. Remove commented code, unnecessary imports and everything unrelated. Always add the full error message text, including the exception type and line. If the error is in logs, provide the last 10–20 lines, not just 'something went wrong'.
If the error does not reproduce stably, indicate this. For example: 'IndexError appears only when the list is empty'. The model must understand the conditions. It is also useful to show what data is fed into the input: an array example, a string, JSON. But do not insert real personal data, tokens or passwords. Replace them with conditional values.
Bad: 'print(items[3]) — IndexError.' Good: 'items = [1, 2, 3]; print(items[3]) → IndexError: list index out of range. I expect to output the fourth element, but the list is shorter'.
Field 'Platform or application': why it is needed
The same error can have different causes in Python 3.8 and 3.12, in Node.js 18 and 20, in browser Chrome and Safari. Specify the language, version, operating system, if it is important. For example: 'Python 3.10, Windows 11, pandas 2.0'. If the error is related to a framework, name it and the version: Django 4.2, React 18, .NET 6.
Do not write 'latest version' — it is undefined. If you do not know the exact version, specify at least the major version. For web applications add the browser and its version. For mobile — device and OS. This information helps the model not to offer syntax that is not supported in your environment.
Bad: 'Python.' Good: 'Python 3.11.4, Ubuntu 22.04, requests library 2.31'.
Field 'Context and requirements': goal, constraints, format
Here you explain what the code should do, what constraints exist and what is considered a successful fix. For example: 'The function must return None if the list is empty, and must not use external libraries.' Or: 'A minimal change is needed, without rewriting the architecture.' If you have already tried to fix something and it did not help, write about this — the model will not repeat the failed variant.
Specify the answer format if it is important: 'Show only the corrected line and explanation in one paragraph'. The tool has no style settings, so all format wishes must be expressed in text. Also mention if the code is educational and you want to understand the cause, not just get a ready-made solution.
Bad: 'Make it work.' Good: 'This is an educational example. I need to understand why IndexError occurs, and get a minimal fix with length check. No changes to original data'.
Example of bad and good task
A bad task often looks like this: a whole file of 300 lines is inserted into the code field, the platform field says 'computer', and the context says 'does not work'. The model may find a syntax error, but the likely cause remains unclear. Moreover, a large fragment blurs attention, and the answer will be superficial.
A good task contains three components: exact minimal code with error, specific environment and clear description of expected behavior. For example: code from five lines, platform 'Python 3.11, Windows', context 'I expect the program to output the third element, but the list contains only two'. Then the tool will with high probability point out the out-of-bounds error and suggest a fix.
Bad task: code: <entire project>; platform: 'laptop'; context: 'error.' Good task: code: `items = [1, 2, 3]; print(items[3])`; platform: 'Python 3.11, Linux'; context: 'need to output the fourth element, but list is shorter. Suggest minimal fix with length check'.
How to check the result
After receiving the answer do not apply it immediately. First check whether the proposed fix corresponds to your context. If the model suggests changing data structure or adding a library, and you asked for a minimal change, this is a signal to clarify the task. Remember: the tool does not run the code, so its solution may be logical but not working in your environment.
Run the corrected fragment on test data. If the error disappears, check edge cases: empty list, None, negative numbers. If the error remains, return to the task and add missing details. Perhaps you did not specify version or did not provide full exception text. One result — one iteration; for a repeat attempt you need to formulate a new task.
After answer 'add a check if len(items) > 3' test: items = [1,2,3] → no exception; items = [1,2,3,4] → should output 4.
Tool limitations
The tool works only with text. It does not connect to your repository, does not see commit history and does not analyse dependencies. It cannot run tests or check performance. Answers may contain errors, and queue and availability vary. Do not use it for security audit or analysis of large projects.
Maximum length of the first field is 8000 characters, the others 1000. If code is larger, reduce it to a minimal example. The tool does not automatically save results, does not send them by email and has no premium plan. You can copy the answer or download it as TXT. No registration is required. All these limitations are important to consider when composing a task.
If the error occurs only when loading a 10 MB file, do not insert the file entirely. Describe its structure and provide a small data example.
Precise task for the 'Find the error' tool saves time and increases the chance of getting a useful minimal fix. Specify exact environment, provide minimal reproducible code with full error text and describe expected behavior. Check the answer on test data and remember the limitations: the tool does not run code and does not replace a debugger. Following these recommendations you will faster find failure causes and learn from your mistakes.
Open tool: Code debugger ↗Interface translations are machine-assisted and may need refinement.