From 03f7b551be24d7b0e8b24882658d46fc7bf9d4ca Mon Sep 17 00:00:00 2001
From: teknium1
Date: Fri, 27 Feb 2026 03:27:15 -0800
Subject: [PATCH] Update README.md: Add DeepWiki Docs badge and enhance
security description for sandboxing feature
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README.md | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/README.md b/README.md
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**The fully open-source AI agent that grows with you.** Install it on a machine, give it your messaging accounts, and it becomes a persistent personal agent — learning your projects, building its own skills, running tasks on a schedule, and reaching you wherever you are. An autonomous agent that lives on your server, remembers what it learns, and gets more capable the longer it runs.
@@ -23,7 +24,7 @@ Built by [Nous Research](https://nousresearch.com). Under the hood, the same arc
| Grows the longer it runs | Persistent memory across sessions — the agent remembers your preferences, your projects, your environment. When it solves a hard problem, it writes a skill document for next time. Skills are searchable, shareable, and compatible with the agentskills.io open standard. A Skills Hub lets you install community skills or publish your own. |
| Scheduled automations | Built-in cron scheduler with delivery to any platform. Set up a daily AI funding report delivered to Telegram, a nightly backup verification on Discord, a weekly dependency audit that opens PRs, or a morning news briefing — all in natural language. The gateway runs them unattended. |
| Delegates and parallelizes | Spawn isolated subagents for parallel workstreams — each gets its own conversation and terminal. The agent can also write Python scripts that call its own tools via RPC, collapsing multi-step pipelines into a single turn with zero intermediate context cost. |
-| Real sandboxing | Five terminal backends — local, Docker, SSH, Singularity, and Modal — with persistent workspaces, background process management, with the option to make these machines ephemeral. Run it against a remote machine so it can't modify its own code. |
+| Real sandboxing | Five terminal backends — local, Docker, SSH, Singularity, and Modal — with persistent workspaces, background process management, with the option to make these machines ephemeral. Run it against a remote machine so it can't modify its own code or read private API keys for added security. |
| Research-ready | Batch runner for generating thousands of tool-calling trajectories in parallel. Atropos RL environments for training models with reinforcement learning on agentic tasks. Trajectory compression for fitting training data into token budgets. |