Mini Coding Agent

This repository was created for the "Build Your Own Coding Agent" hackathon, organized by HackerRank, which took place from 5 September 2025 at 05:30 IST to 8 September 2025 at 05:30 IST.

Overview

This project is intended as a practical developer tool and lab: it demonstrates an automated, test-driven workflow where a small agent inspects subprojects under projects/, runs their tests, and reports actions taken. Key points:

• Design intent: keep fixes minimal and focused — the agent performs small, deterministic edits (e.g., bugfixes, missing return values, simple refactors) so test behavior changes are easy to review.
• Validation model: every change is validated by running the affected project's test suite; results are reported as JSON summaries and human-readable logs.
• Extensibility: agent logic is intentionally modular — add new project detectors, test runners, or language handlers by implementing small adapters under the top-level agent module.
• Safety and reproducibility: the agent avoids committing secrets, writes no persistent side effects outside project directories, and can run in dry-run mode to preview planned edits.
• Usage notes: configure required environment variables (no .env assumed), run python tests.py to run all projects' tests, and use python agent.py --dry-run to preview actions before applying them.

Supported projects:

• flask-easy — basic event ticketing example
• flask-intermediate — JWT authentication example
• flask-hard — log processing and notification example

Primary workflows:

• Run all tests: python tests.py
• Run the agent in dry-run mode: python agent.py --dry-run
• Run a single project tests: see projects/<project>/README.md

High Level Structure

mini-coding-agent/
├── agent.py (implement your agent here)
├── tests.py (for running all the test cases)
├── check_usage.py (for checking LLM resource utilisation)
├── projects
        ├── project_1
                ├── app/
                ├── README.md
        ├── project_2
                ├── app/
                ├── README.md
└── requirements.txt

How to run (local)

1. Create and activate a virtual environment (recommended):

python -m venv .venv
.\.venv\Scripts\Activate.ps1

2. Install dependencies:

pip install -r requirements.txt

3. Run all tests (top-level):

python tests.py

4. Run the agent in dry-run to see planned actions:

python agent.py --dry-run