# How Logging Is Implemented in the i-have-adhd Backend: A Complete Codebase Analysis

> Analyze i-have-adhd backend logging. Discover how simple print statements are used for diagnostic output instead of a structured logging framework in this codebase.

- Repository: [Ayoub Ghriss/i-have-adhd](https://github.com/ayghri/i-have-adhd)
- Tags: internals
- Published: 2026-07-30

---

**The i-have-adhd repository does not implement a structured logging framework; all diagnostic output is limited to simple `print` statements in auxiliary Python scripts.**

The i-have-adhd project is an open-source skill definition repository focused on ADHD assistance tools. Unlike traditional backend services that rely on structured logging libraries like `winston`, `log4js`, or Python's `logging` module, this codebase takes a minimal approach to observability with only basic console output.

## Absence of Structured Logging Libraries

A comprehensive review of the repository reveals **zero imports** of formal logging libraries. The codebase contains no configuration for `winston` (Node.js), `log4js`, or Python's built-in `logging` module. Searches for standard logging imports such as `import winston`, `import logging`, or similar patterns return no results across the entire codebase. This confirms that the i-have-adhd backend does not implement a centralized logging system, structured log levels, or persistent log file rotation.

## Console Output in Utility Scripts

The only "log-like" output in the i-have-adhd backend appears in small utility scripts that execute skill evaluations. These scripts use basic stdout printing rather than formal logging APIs.

### Evaluation Runner Script ([`scripts/run_evals.py`](https://github.com/ayghri/i-have-adhd/blob/main/scripts/run_evals.py))

The primary evaluation script located at [`scripts/run_evals.py`](https://github.com/ayghri/i-have-adhd/blob/main/scripts/run_evals.py) produces status updates using standard Python `print` functions:

```python
print("Running evaluation cases…")

# … evaluation logic …

print("Finished all cases")

```

This approach writes diagnostic information directly to stdout without timestamps, severity levels, or structured formatting typically associated with production logging systems.

### Test Diagnostics ([`tests/test_run_evals.py`](https://github.com/ayghri/i-have-adhd/blob/main/tests/test_run_evals.py))

The corresponding test file at [`tests/test_run_evals.py`](https://github.com/ayghri/i-have-adhd/blob/main/tests/test_run_evals.py) follows the same pattern, using basic print statements for test visibility:

```python
print("Running test:", case["name"])

```

These ad-hoc console outputs serve only for immediate debugging during script execution and do not persist to log files or integrate with monitoring systems.

## Declarative Skill Definition ([`SKILL.md`](https://github.com/ayghri/i-have-adhd/blob/main/SKILL.md))

The core skill definition in [`SKILL.md`](https://github.com/ayghri/i-have-adhd/blob/main/SKILL.md) operates as a purely declarative document containing rules, examples, and formatting specifications. As a markdown-based skill definition rather than executable code, it contains no function calls, import statements, or logging logic. This architectural choice means the "backend" of i-have-adhd is essentially stateless and serverless, requiring no runtime observability beyond the simple print statements found in the auxiliary evaluation scripts.

## Summary

- **No logging libraries** are imported or configured anywhere in the i-have-adhd repository.
- **All output** is generated via basic `print` statements in [`scripts/run_evals.py`](https://github.com/ayghri/i-have-adhd/blob/main/scripts/run_evals.py) and [`tests/test_run_evals.py`](https://github.com/ayghri/i-have-adhd/blob/main/tests/test_run_evals.py).
- **[`SKILL.md`](https://github.com/ayghri/i-have-adhd/blob/main/SKILL.md)** contains no executable code and therefore implements no logging functionality.
- The backend relies on **stdout console output** rather than structured, persistent logging systems.

## Frequently Asked Questions

### Does i-have-adhd use Winston or Log4js for logging?

No. The repository contains no JavaScript/TypeScript logging libraries like `winston` or `log4js`. A complete search of the codebase confirms zero occurrences of these imports, as the project is primarily Python-based for its utility scripts and declarative markdown for its core skill definition.

### Where does the i-have-adhd backend output diagnostic information?

Diagnostic output appears exclusively in [`scripts/run_evals.py`](https://github.com/ayghri/i-have-adhd/blob/main/scripts/run_evals.py) and [`tests/test_run_evals.py`](https://github.com/ayghri/i-have-adhd/blob/main/tests/test_run_evals.py), where standard Python `print` functions write status messages to stdout. These scripts output strings like "Running evaluation cases…" and "Finished all cases" without structured formatting or log levels.

### Is there any Python logging module configuration in the backend?

No. The codebase does not import Python's standard `logging` module or configure loggers, handlers, or formatters. All status reporting uses bare `print` statements, making the output unsuitable for production log aggregation or automated monitoring systems.

### Why doesn't the i-have-adhd backend implement formal logging?

The repository is architected as a declarative skill definition rather than a persistent backend service. With [`SKILL.md`](https://github.com/ayghri/i-have-adhd/blob/main/SKILL.md) serving as the core artifact and evaluation scripts acting as temporary test runners, the project has no long-running processes that would require structured logging, log rotation, or persistent audit trails.