DSH Plugins Marketplace

DSH Plugins

Plugins

/

Vision & Multimodal

/

anolisa

a

anolisa

Manifest valid★ 397

AgentSight observability plugin for DeepSeek Harness

ANOLISA

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

License Platform AARM Aligned OWASP Agentic Top 10: 7 Full, 3 Partial


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 entryContext efficiencyRuntime & security
cosh-ng
Shell copilot
Token-less
Tool-output compression
ws-ckpt
Checkpoint and rollback
OS Skills
System and DevOps expertise
AgentSight
Trace and Token visibility
SkillFS
Focused Skill views
ktuner
Kernel tuning
Agent Memory
Cross-session memory
Agent Sec Core
Sandbox and verification
Blaze
Sandbox 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 →

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

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 responsesTool schemasFull pipeline
65.8% fewer Tokens47.3% fewer Tokens62.9% fewer Tokens
ResponseCompressor · 46.85 µsSchemaCompressor · 11.44 µs198.91 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

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 →

Standards & Compliance

Standard / FrameworkStatus and details
AARMAligned · Registry entry: AgentSecCore (ANOLISA)
OWASP Agentic Top 10 (2026)All 10 ASI risk categories mapped to security controls

Documentation

Quick Start · Installation · User Guide · Troubleshooting · Build from Source · Changelog

Community

ANOLISA DingTalk community QR code

Scan the DingTalk QR code to join the ANOLISA community.

License

ANOLISA is released under the Apache License 2.0.

Comments

Loading…

Similar plugins

dsh-lens

by coffee-man666

Repository and agent-runtime analysis skills as an installable DeepSeek Harness (dsh) plugin

Security & AuditManifest valid

★ 0

MIT

TypeScript

Aug 24, 2026

dsh plugin --profile web add @deepseek-ai/dsh-lens

by aa2246740

Read-only Agent work-path observer for DeepSeek Harness

Sessions & MessagesManifest valid

★ 121

↓ 451/wk

MIT

JavaScript

Oct 26, 2026

dsh plugin --profile web add dsh-watcher

by NanmiCoder

AgentTeams plugin for DeepSeek Harness

Workflow & AutomationManifest valid

★ 2.5k

↓ 12.3k/wk

MIT

JavaScript

Oct 26, 2026

dsh plugin --profile web add @nanmicoder/dsh-agent-teams

by cyanseek

Agent-first DeepSeek Harness plugin intelligence: verify existing plugins, identify missing capabilities, and generate build-ready briefs.

Tools & CapabilitiesManifest valid

★ 6

MIT

JavaScript

Oct 27, 2026

dsh plugin --profile web add dsh-landscape

by Rgndmln

为 DeepSeek Harness 打造的 3D 智能体工作轨迹可视化插件。A 3D agent-work trajectory visualization plugin for DeepSeek Harness.

Manifest valid

★ 3

MIT

TypeScript

Aug 17, 2026

dsh plugin --profile web add spatial-trajectory

by litefuse

DeepSeek Harness Litefuse Plugin for Agent Observability and Evals

Manifest valid

★ 0

MIT

TypeScript

Aug 18, 2026

dsh plugin --profile web add dsh-litefuse-plugin