alibaba/anolisa: ANOLISA (Agentic Nexus Operating Layer & Interface System Architecture) | Agentic OS with runtim

github.com · 2026-08-21 · by Long Nguyen ·github
ANOLISA (Agentic Nexus Operating Layer & Interface System Architecture) | Agentic OS with runtime, security, observability, and Tokenless response compression for lower token usage and cost. - alibaba/anolisa

alibaba/anolisa

ANOLISA (Agentic Nexus Operating Layer & Interface System Architecture) | Agentic OS with runtime, security, observability, and Tokenless response compression for lower token usage and cost. - ...

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Agentic Nexus Operating Layer & Interface System Architecture The operating system layer for Agent workloads. Let Agents drive the system straight from your terminal, and strip the tool responses that reach the model before they cost you — while keeping the Shell, Agent framework, and sandbox you already run. 中文版 · Website · Quick Start · User Guide · Contributing

ANOLISA is a server-side operating layer for AI Agent workloads. It addresses three practical constraints of Agent execution: terminal entry, Token cost, and execution environments. Keep the Shell, Agent framework, and sandbox you already use. ANOLISA CLI provides a single installation entry point, while each capability can be enabled independently. New to ANOLISA? Choose your first outcome in the Quick Start → Components

Agent entry Context efficiency Runtime & security cosh-ngShell copilot Token-lessTool-output compression ws-ckptCheckpoint and rollback OS SkillsSystem and DevOps expertise AgentSightTrace and Token visibility SkillFSFocused Skill views ktunerKernel tuning Agent MemoryCross-session memory Agent Sec CoreSandbox and verification BlazeSandbox lifecycle

What it solves 01 · AGENT INTERFACE Let the Agent work directly in the terminal cosh-ng is an AI-native Linux terminal: it keeps familiar Bash/Zsh behavior, then adds an Agent that can understand intent, use tools and Skills, and ask for approval before risky work. Shell commands and natural language share one terminal instead of forcing users into a separate chat application. Get started with cosh-ng → 02 · CONTEXT EFFICIENCY See where Tokens go and cut waste before it reaches the model Token-less removes redundancy from tool schemas and responses before they reach the model. Agent Memory reuses useful context across sessions. SkillFS keeps the current Skill view focused and makes other Skills discoverable when needed. AgentSight shows where Tokens are spent. See an Agent run from the kernel up On Linux, AgentSight uses eBPF to observe an Agent without changing its code. Follow user input through model and tool calls, with Token use and sub-agent branches in the same view. Open the AgentSight guide →

agentsight-demo-en-ebpf-cover-1080p.mp4

Try Token-less with Claude Code in 3 minutes Install Token-less and connect it to Claude Code: curl -fsSL https://get.agentic-os.sh | bash export PATH="$HOME/.local/bin:$PATH" anolisa install tokenless anolisa adapter enable tokenless claude-code Restart Claude Code, run one tool-heavy task, then inspect the result: tokenless stats summary tokenless stats list --limit 5 Open the full Token-less Quick Start → · Read the user manual

tokenless-context-efficiency-hd.mp4

In one observed coding task, Token-less saved 317K Tokens (40.5%), based on AgentSight measurements. Results vary by workload.

debug and trace are dropped by the field blacklist, metadata as null, and tags / extra as empty values. Compression runs between the Agent and the model, so no Agent framework code changes. Dropped array items stay retrievable through a <<tokenless:KEY>> marker, which keeps the compression reversible.

Tool responses Tool schemas Full pipeline

65.8% fewer Tokens 47.3% fewer Tokens 62.9% fewer Tokens

ResponseCompressor · 46.85 µs SchemaCompressor · 11.44 µs 198.91 µs

Savings apply to the tool responses entering the context, not to the whole session bill. The Token-less user manual explains how to estimate the effect for a given workload. 03 · EXECUTION RUNTIME Give every Agent execution a boundary and a way back ANOLISA is building out the Agent execution environment: Agent Sec Core isolates risky operations, and ws-ckpt keeps recovery points for workspace changes. Catch a changed Skill before it runs When a signed Skill changes, the Agent reports drifted before using it again. A rescan records blocking findings as deny. Try the Agent demo → · Skill Ledger guide

skill-ledger-demo-en-with-cover.mp4

Choose a runtime or security starting point → · Start with ANOLISA CLI Install ANOLISA CLI is the common installation entry point. cosh-ng is installed in system mode; Token-less and other capabilities can be added independently. curl -fsSL https://get.agentic-os.sh | bash

sudo anolisa --install-mode system install cosh-ng anolisa install tokenless Run cosh to enter the AI-native terminal. Token-less can also optimize tool calls from an existing Agent without changing its framework. Read the Quick Start → Documentation Quick Start · Installation · User Guide · Troubleshooting · Build from Source · Changelog Community

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Open an issue for bugs and feature requests. Read CONTRIBUTING.md before submitting a pull request. Report vulnerabilities through the Security Policy.

License ANOLISA is released under the Apache License 2.0.

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