SShortSingh.
Back to feed

Developer Builds Open-Source SDK to Track Brand Mentions Across AI Search Engines

0
·1 views

A developer has released webscore-sdk, an npm package designed to help track brand visibility across AI platforms such as ChatGPT, Gemini, Perplexity, and Claude. The tool targets a practice known as Generative Engine Optimization (GEO), which focuses on improving how brands appear in AI-generated responses. The SDK measures two core metrics: mention rate, the percentage of relevant prompts where a brand appears, and citation rate, the percentage where the brand's website is linked. It also returns a sentiment reading and an overall GEO score ranging from 0 to 100. The package is available via npm, and a free tier offering 10 scans can be accessed at webscore.dev.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

PickleAI Launches as Open-Source Local AI Desktop Assistant Built on Ollama

PickleAI is a newly released open-source desktop AI assistant that runs entirely on a user's local machine, powered by the Ollama framework. The tool is designed for users who want a private, customizable AI experience without relying on cloud-based services. It offers features including automation tools, productivity workflows, and a desktop application interface. The project is available on GitHub and its developer is actively seeking early users to test the software and provide feedback. A demo video has also been published to help prospective users evaluate how it fits into their workflow.

0
ProgrammingDEV Community ·

Why Modern Apps Are Bloated: The Software Obesity Crisis Explained

A technical analysis published on DEV Community argues that modern software has become severely bloated, with basic chat applications now requiring up to 1.5 GB of RAM and 14 background processes to run. The piece contrasts this with the Apollo 11 Guidance Computer, which landed humans on the moon in 1969 using just 4 KB of RAM. Much of the blame is placed on Electron-based desktop apps, which bundle a full Chromium browser engine and Node.js runtime for each application, meaning tools like Slack, Discord, and Spotify each function as isolated web browsers consuming hundreds of megabytes. Developer convenience and corporate incentives are cited as key drivers, with modern projects routinely pulling in thousands of transitive dependencies just to handle simple tasks like date parsing or string formatting. The author describes the problem as a systemic, multi-layered crisis stretching from hardware-level inefficiencies up to the user interface.

0
ProgrammingDEV Community ·

Why Understanding Business Behavior Matters More Than Memorizing Data Structures

A DEV Community article series concludes with a core lesson: data structures should be chosen based on the business behavior they need to support, not technical familiarity or memorization. The series reframed common structures — such as HashMap, Queue, Heap, Trie, and Graph — by mapping each to a specific real-world software need rather than algorithmic theory. The author argues that engineers who understand behaviors adapt more easily when requirements change, while those who rely on memorized implementations often struggle. Using an online marketplace as an example, the piece illustrates how different business functions naturally call for different data structures. The overarching takeaway is that good low-level design starts with understanding responsibilities and business context, with implementation decisions following as a final step.

0
ProgrammingDEV Community ·

Understanding IPv4 Addresses: How Four Numbers Define Every Device Online

IPv4, or Internet Protocol version 4, was officially standardized in 1981 through a public document known as RFC 791. It uses a format called Dotted Decimal Notation, where an address like 172.17.0.3 is divided into four segments separated by dots. Each segment is called an octet, representing 8 binary digits (bits) that can store a value between 0 and 255. Because computers process information as electrical on/off states represented by 0s and 1s, grouping 8 bits together allows 256 possible values per octet. With four such octets combined, an IPv4 address provides a structured way to uniquely identify devices on a network.