---
title: "Normalize and filter noisy URL lists before crawling or queueing"
description: "Uses Courlan to clean, normalize, de-track, and language-filter raw URL inventories before a crawler, scraper, or analyst queue touches them. Best when an agent already has too many candidate links and needs a smaller, cleaner frontier, not a full crawling stack."
verification: "security_reviewed"
source: "https://github.com/adbar/courlan"
author: "Adrien Barbaresi"
category:
  - "Research & Scraping"
framework:
  - "Multi-Framework"
tool_ecosystem:
  github_repo: "adbar/courlan"
  github_stars: 165
---

# Normalize and filter noisy URL lists before crawling or queueing

Uses Courlan to clean, normalize, de-track, and language-filter raw URL inventories before a crawler, scraper, or analyst queue touches them. Best when an agent already has too many candidate links and needs a smaller, cleaner frontier, not a full crawling stack.

## Prerequisites

Python 3, pip, command line

## Installation

Choose whichever fits your setup:

1. Copy this skill folder into your local skills directory.
2. Clone the repo and symlink or copy the skill into your agent workspace.
3. Add the repo as a git submodule if you manage shared skills centrally.
4. Install it through your internal provisioning or packaging workflow.
5. Download the folder directly from GitHub and place it in your skills collection.

Install command or upstream instructions:

```
pip install courlan
```

## Documentation

- https://adrien.barbaresi.eu/blog/easy-content-aware-url-filtering.html

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/normalize-and-filter-noisy-url-lists-before-crawling-or-queueing/)