Search Results for "command line" - Page 2

Kimchi is a terminal coding agent powered by multi-model orchestration. It is designed to help developers run AI-assisted coding sessions from the command line while coordinating specialized agents, tools, permissions, and project context. The repository includes systems for subagents, task classification, model delegation, MCP integration, web search, web fetching, Language Server Protocol support, authentication, and interactive terminal workflows. It also supports ACP-style JSON-RPC integration for editor workflows and remote session multiplexing through its teleport mode. ...

Amazon Q Developer CLI brings an agentic, chat-driven coding assistant to your terminal so you can ask for help, generate code, and perform routine dev tasks with natural language. It blends knowledge of your local workspace with command-line context to suggest commands, explain flags, and scaffold files or workflows. The tool aims to shorten the gap between intent and action by letting you request operations like creating a test, refactoring a function, or drafting a Dockerfile without leaving the shell. It also integrates with common developer flows, offering autocompletion and step-by-step plans before running potentially destructive actions. ...

VTCode is a terminal-based AI coding agent designed to provide semantic code understanding and interactive assistance directly within a command-line environment. It is implemented in Rust and focuses on performance, portability, and deep integration with developer workflows that rely on terminal tools. The system leverages syntax-aware parsing technologies such as tree-sitter and AST-based analysis to understand code structure rather than relying solely on raw text, which enables more accurate and context-aware suggestions. ...

SERA CLI is a command-line tool created by AllenAI to enable developers to interact with the SERA (Soft-Verified Efficient Repository Agents) model family using Claude Code as the execution front end. It provides a convenient interface for deploying, testing, and using SERA models without needing to write scaffold code from scratch, acting as both a proxy and utility wrapper to simplify workflows that involve large agent models.

...A team member that accelerates the pace of development and helps you write better code. We've planned to build out multiple different interfaces for interacting with AICodeBot. To start, it's a command-line tool that you can install and run in your terminal and a GitHub Action for Code Reviews. This project was built before AI Coding Assistants were cool. As such, much of the functionality has been replicated in various IDEs. Where AICodeBot shines is a) it's in the terminal, not GUI, and b) it can be used in processes like GitHub actions. ...

...Instead of just offering autocomplete, Sourcery analyzes existing functions and code patterns to provide context-aware suggestions that can simplify logic, reduce duplication, improve naming, and correct anti-patterns, helping developers adhere to idiomatic style without manual review. It integrates directly into development workflows through plugins for editors like VS Code, JetBrains IDEs, and command-line tools, so suggestions appear where developers already write code. Because it continuously evaluates changes, it can catch inefficiencies and suggest enhancements both while typing and during dedicated refactor passes. Teams can standardize code quality across codebases by adopting Sourcery’s automated suggestions as part of review or CI pipelines.

Mentat is the AI tool that assists you with any coding task, right from your command line. Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project, no copy and pasting is required. Run Mentat from within your project directory. Mentat uses Git, so if your project doesn't already have Git set up, run git init. List the files you would like Mentat to read and edit as arguments.