am-i-vibing

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Basic Information

am-i-vibing is a small open-source project that aims to detect agentic coding environments and AI editors. The repository is organized as a package under packages/am-i-vibing and was generated from ascorbic/library-template. Recent commits indicate a command-line interface was added, suggesting the project exposes detection functionality via a CLI in addition to its package form. The core purpose is to identify when a developer workspace or editor is being driven or augmented by autonomous agents or AI-assisted editing tools. The README itself is a symbolic link to the package README, indicating the package is the primary deliverable. The project appears intended for developers and researchers who need a straightforward tool to flag or characterize agentic behaviors in coding environments rather than a full platform for building agents.

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App Details

Features
The repository signals a few concrete features: a packaged library located at packages/am-i-vibing and a command-line interface added in a recent commit. It is scaffolded from a reusable library template, which implies standard packaging and developer-friendly layout. The project focuses specifically on detection of agentic coding environments and AI editors rather than agent orchestration. As an open-source package, it can be inspected and adapted by contributors. The lightweight README and symbolic link structure point to a focused single-package deliverable rather than a multi-package monorepo. The visible metadata (commit history and generation template) suggests the project is set up for iterative development and community contributions.
Use Cases
This project is useful for developers, researchers, security teams, and tool maintainers who need a way to recognize when coding environments are being influenced by autonomous agents or embedded AI editors. By providing detection functionality in a package and a CLI, it enables quick checks in local workflows, CI jobs, or research experiments. The focused scope helps teams audit workspaces, study agentic behaviors, and decide whether to allow, restrict, or adapt integrations with AI editing tools. Because it is packaged and template-generated, organizations can fork or extend the code to meet specific policy, monitoring, or research needs without adopting a large framework.

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