User:FlagBot


 * Currently operating on WP France Unassesseds - don't worry if there's some glitches, once all the Unassesseds have been processed I will be going back to check on any that the bot has skipped**

Bot approved 21/March/2008 - see BAG application, then lapsed during a long Wikibreak and reapproved 10/December/2022 at Bots/Requests for approval/FlagBot 2

This is the user page of a semi-automatic bot belonging to User:FlagSteward. Its main function is to automate the assessment of articles within a WikiProject, particularly "town" articles in projects such as WikiProject Italy. It performs one-off runs, generally once per Project.

Overview
The bot is written in PHP. It scans the lists of articles covered by a project and opens each of them in turn at >1.0 second intervals using Special:Export. It extracts various statistics such as the number of tags and number of images, and also what infoboxes an article uses. If the Template:Infobox CityIT box is present, it goes to the next stage.

Assessing importance
The bot extracts the population of a commune if possible, and proposes the following assessment of importance :
 * Low : <15000 (and <2 JPG images in the article)
 * Mid : >25000, <75000
 * High :>125000

Assessing class
Class is based on an algorithm that looks at parameters such as WP:ORES classification and the length of article. In the case of Italian comuni, many have a 2kb demographic timeline which doesnt affect assessment, so the length of this is calculated and deducted from the length of the article. Classes are as follow :
 * Stub
 * Length - timeline < 2500
 * OR Length - timeline < 3200, <3 headers, <2 refs, <2 images


 * Start
 * <3000 length-timeline <12000,
 * <1800 length-timeline <12000, >3 headers and at least 1 ref and 1 image outside an infobox, or (images+headers) >2

These categories may vary depending on the Project - for instance the France Project assess all towns >100,000 people as High by definition.

Applying assessments
The list of assessments once generated is then examined by me, and any obvious tweaks applied. The list is then fed into AWB, which uses regexes based on Kingbotk's to apply the assessment. The Italy Project has about 1500 articles to do, some of the other Projects may have up to 5000.

CityIT templates
In support of the primary task, the bot may extract Comune infoboxes from the Italian versions of articles, clean up and translate eg months, and use subst:Comune to apply a CityIT infobox to the English article.