ManuelZierl/fellow

AI Summary: Expand the existing end-to-end (E2E) tests for the Fellow CLI tool to cover a wider range of scenarios, including various CLI options, invalid inputs, resume functionality, configuration handling, and more realistic workflows. The goal is to improve the stability and reliability of Fellow by catching regressions early.

AI Summary: Improve the SEO of the Fellow project's documentation hosted on GitHub Pages using the Just the Docs theme. This involves adding meta descriptions to pages, implementing Open Graph and Twitter Card meta tags, and potentially adding a sitemap and robots.txt file. The goal is to enhance search engine visibility without overly complicating the existing setup.

AI Summary: The task is to create a standalone executable version of the Fellow CLI tool using Nuitka. This involves compiling the Python code into a single executable file that includes all dependencies, ensuring cross-platform compatibility (at least Linux and Windows), and potentially creating a build script and automating the process via GitHub Actions. Distribution methods also need to be considered.

AI Summary: The task is to design and potentially implement a multi-agent system for the Fellow CLI tool. This involves enabling multiple Fellow instances to collaborate on a project, each with a defined role, command set, and memory scope. The design should consider communication methods between agents, task delegation, and overall system architecture. The implementation could involve creating a new configuration format (e.g., YAML) for defining teams and roles.

AI Summary: Implement session management in the Fellow CLI tool to maintain context across multiple invocations. This involves tracking session IDs, storing session-specific data (memory, logs, plans), and potentially adding features like session goals and a visual session manager.

AI Summary: Implement a plugin management system for Fellow, including commands to list, validate, and install plugins. This involves defining a plugin metadata format, creating a plugin discovery mechanism (initially local, potentially remote), and adding validation checks. The project also requires updating documentation to encourage community contributions of plugins.

AI Summary: This task involves brainstorming and planning the design and development of a graphical user interface (GUI) for the Fellow command-line AI assistant. This includes deciding on the core features to include, selecting a suitable technology stack (e.g., Python GUI frameworks, Electron, or a web-based approach), and outlining a potential development roadmap. The discussion also considers alternative approaches like creating a VS Code or JetBrains plugin instead of a standalone GUI.