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AI Security Agents for Code Review

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Agen
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Agen is a platform for fully autonomous AI coding agents that run in the cloud. You connect a Git repo, describe a task in plain English, and agents clone the code, explore the codebase, write changes, run the pipeline, fix CI failures themselves, and hand back a merge-ready pull request with a live preview — no IDE, no local setup, no babysitting. It supports multi-repo sessions, unlimited parallel agents, scheduled runs with budget limits, and mobile task assignment. Agen positions itself against IDE-bound copilots and single-repo agents by being cloud-native from day one, with flat $59/mo pricing versus metered competitors. Non-technical teammates can assign work while engineers keep merge control. New accounts get $20 in free credits, making it easy to test on a real codebase before committing.

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OpenAgentd
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OpenAgentd is a self-hosted AI-agent OS that runs entirely on the user’s machine. It provides a web cockpit, streaming chat, persistent editable memory, tool use, workspace file browsing, image viewing, local voice transcription, scheduling and multi-agent teams with lead-worker delegation. Agents can read and write files, run shell commands, search the web, generate media, manage todos and extend capabilities via skills or MCP servers. The tool is for users who want a local, inspectable alternative to cloud-only agent workspaces. It is notable now because privacy, long-running autonomy and multi-agent coordination are converging into desktop systems rather than isolated chat tabs.

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Maestro
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Maestro turns an issue tracker into an execution layer for AI coding agents. The project coordinates agent work by dispatching issues, managing runtimes, choosing providers, tracking evidence, and making autonomous engineering more operable at team scale. It is aimed at engineering teams, agencies, and technical operators who already use GitHub-style issue workflows but need a safer bridge between task planning and AI-agent execution. Instead of manually copying tickets into terminals, Maestro treats issues as the control surface and keeps proof, runtime state, and provider coordination attached to the work. The repository surfaced in fresh GitHub AI-coding and workflow-automation searches with clear docs and active stars, making it a strong developer-tool candidate for Smartoolbox.

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