Search Results for "role based access control"

Role-specific agent modes keep AI focused, reliable, and aligned with real engineering workflows. Open source, secure, and highly configurable, Roo Code fits seamlessly into both individual and team-based development environments.

OpenCode is an open-source AI coding agent designed to assist developers directly from the terminal, desktop, or IDE environments. It functions as a locally running assistant that can analyze codebases, execute development tasks, and interact with external tools while remaining highly configurable. The system is built around an agent model that can perform actions such as file manipulation, shell execution, and web access with user confirmation. Its provider-agnostic design allows developers...

T3 Code is a minimal web GUI for running coding agents such as Codex, Claude, and OpenCode. It gives developers a cleaner interface for working with agent sessions without relying only on terminal-based workflows. The project can be launched quickly with npx, and it also supports desktop and remote access setups. Users need to install and authenticate at least one supported provider before using it, which keeps the actual agent accounts under the user’s control. The repository includes guidance for exposing a T3 Code server to another device, such as a phone, tablet, or separate desktop app. ...

49Agents is an open-source “agentic IDE” that reimagines how developers interact with multiple AI agents, terminals, and development environments by placing everything onto a single infinite, zoomable canvas. Instead of relying on traditional tab-based workflows, it provides a spatial interface where terminals, editors, Git views, and monitoring tools coexist as movable panes, enabling users to manage complex multi-agent systems visually and intuitively. The platform is designed to work...

...It organizes the audit into multiple phases so the agent does not simply search randomly for vulnerabilities. The workflow begins with reconnaissance, then moves into parallel hunting across attack classes such as injection, access control, business logic, cryptography, feature abuse, and chained attacks. Findings are then challenged through separate validation agents to reduce false positives. The skill produces human-readable reports, detailed finding traces, structured JSON output, and independent verification against the actual source code. Overall, it is designed to make AI-assisted security review more systematic, adversarial, and evidence-based.