Libraries tagged by aissue

Low-bootlevel Drush commands to deal with Drupal caches and related issues.

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Fixes WordPress compatibility issues when running on Symfony Local Server with local domain names

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Find and fix accessibility issues in TYPO3: missing-alt detection and AI alt-text generation, decorative-image controls, heading/landmark checks, axe-core scans with optional AI audits, semantic Fluid ViewHelpers, and accessible form-validation feedback.

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Provides single-sign-on ability to Microsoft Azure Active Directory enabled apps. This package is updated to work with Laravel 8, as the forked package had depency issues with guzzle.

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Allows to check the project's database against most common issues

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Checks Wordpress installation for CVE security issues at wpvulndb.com

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Mark-a-Spot is a Drupal distribution for crowdmapping and public civic issue tracking

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Fixes WordPress issues with home and site URL on multisite when using Bedrock

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With Magento 2 FAQ Extension, you will not need to worry about creating useful and nice FAQ page for your ecommerce website. The extension will help you to set up nice informative & SEO-friendly magento 2 FAQ page. With faq page, your customers will find convenient, easily and quick to resolve common issues.

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slick - the last carousel you'll ever need. For more informations please have a look at https://github.com/misterboe/slickcarousel. If you need more features please create an issue on github.

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A set of rules for the Psalm static analysis tool that help to detect popular issues when working with the Laravel framework.

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# Introduction **INDA (INtelligent Data Analysis)** is an [Intervieweb](https://www.intervieweb.it/hrm/) AI solution provided as a RESTful API. The INDA pricing model is *credits-based*, which means that a certain number of credits is associated to each API request. Hence, users have to purchase a certain amount of credits (established according to their needs) which will be reduced at each API call. INDA accepts and processes a user's request only if their credits quota is grater than - or, at least, equal to - the number of credits required by that request. To obtain further details on the pricing, please visit our [site](https://inda.ai) or contact us. INDA HR embraces a wide range of functionalities to manage the main elements of a recruitment process: + [**candidate**](https://api.inda.ai/hr/docs/v2/#tag/Resume-Management) (hereafter also referred to as **resume** or **applicant**), or rather a person looking for a job; + [**job advertisement**](https://api.inda.ai/hr/docs/v2/#tag/JobAd-Management) (hereafter also referred to as **job ad**), which is a document that collects all the main information and details about a job vacancy; + [**application**](https://api.inda.ai/hr/docs/v2/#tag/Application-Management), that binds candidates to job ads; it is generated whenever a candidate applies for a job. Each of them has a specific set of methods that grants users the ability to create, read, update and delete the relative documents, plus some special features based on AI approaches (such as *document parsing* or *semantic search*). They can be explored in their respective sections. Data about the listed document types can be enriched by connecting them to other INDA supported entities, such as [**companies**](https://api.inda.ai/hr/docs/v2/#tag/Company-Management) and [**universities**](https://api.inda.ai/hr/docs/v2/#tag/Universities), so that recruiters may get a better and more detailed idea on the candidates' experiences and acquired skills. All the functionalities mentioned above are meant to help recruiters during the talent acquisition process, by exploiting the power of AI systems. Among the advantages a recruiter has by using this kind of systems, tackling the bias problem is surely one of the most relevant. Bias in recruitment is a serious issue that affect both recruiters and candidates, since it may cause wrong hiring decisions. As we care a lot about this problem, we are constantly working on reduce the bias in original data so that INDA results may be as fair as possible. As of now, in order to tackle the bias issue, INDA automatically ignores specific fields (such as name, gender, age and nationality) during the initial processing of each candidate data. Furthermore, we decided to let users collect data of various types, including personal or sensitive details, but we do not allow their usage if it is different from statistical purposes; our aim is to discourage recruiters from focusing on candidates' personal information, and to put their attention on the candidate's skills and abilities. We want to help recruiters to prevent any kind of bias while searching for the most valuable candidates they really need. The following documentation is addressed both to developers, in order to provide all technical details for INDA integration, and to managers, to guide them in the exploration of the implementation possibilities. The host of the API is [https://api.inda.ai/hr/v2/](https://api.inda.ai/hr/v2/). We recommend to check the API version and build (displayed near the documentation title). You can contact us at [email protected] in case of problems, suggestions, or particular needs. The search panel on the left can be used to navigate through the documentation and provides an overview of the API structure. On the right, you can find (*i*) the url of the method, (*ii*) an example of request body (if present), and (*iii*) an example of response for each response code. Finally, in the central section of each API method, you can find (*i*) a general description of the purpose of the method, (*ii*) details on parameters and request body schema (if present), and (*iii*) details on response schema, error models, and error codes.

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Symfony bundle that captures Monolog errors, deduplicates them by fingerprint, emails a daily digest of new/spiking/top issues to admins, and provides a triage UI.

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Rich Block Kit Slack deploy notifications for Deployer — environment, commit list, and ticket summary linked to your issue tracker.

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Fix for 500 error in Mage 2.2.2 (issue 12655).

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