super-agent-integration

Name: super-agent-integration
Author: community

VERIFIED

by community

—No community reviews yet

144,126,000installs

Updated Aug 2026

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Description

把分散建成的超级智能体单点能力熔成一次真实可跑、可被度量的端到端自主闭环，是超越一线大模型的最后一公里。真实 import 并调用 planner / reason-verify / memory-cross-engine / reflection-replanner / super-agent-bootstrap / agent-eval-harness，跑通「感知→规划→执行→自验证→反思重规划→跨引擎记忆→回归评测」全链路，最后用评测引擎量化闭环健康度并判定是否闭环可用。当用户要求真正跑通自主智能体、验证"是否真的能端到端自主完成任务"、度量超级智能体健康度时使用。

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Install super-agent-integration

Run this in your OpenClaw agent to add super-agent-integration from the ClawHub registry.

terminal

$openclaw skills install super-agent-integration

Requires ClawHub registry access. Review the security analysis below before installing.

Security Analysis

❌危险50/100

Open Source

Code is publicly available for audit.

Community Verified

Reviewed by the ClawHub community.

Community Reviews

Real user ratings only — separate from the editorial assessment and ClawHub signal.

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Frequently asked questions

Is super-agent-integration safe to install?

super-agent-integration has a SkillsReview security score of 50/100. It is open source and community-verified on ClawHub. Check the full Security Analysis on this page before installing.

How much does super-agent-integration cost?

super-agent-integration is free to install for OpenClaw via ClawHub.

What are the best alternatives to super-agent-integration?

You can compare super-agent-integration side by side with similar OpenClaw skills on the SkillsReview comparison page to find the best fit for your workflow.

How do I install super-agent-integration?

Install super-agent-integration from ClawHub at clawhub.ai/skills/super-agent-integration, or use the install action on this page to copy the command for your OpenClaw agent.

Community Signal

ClawHub Community Score6120.00 / 5.00

Installs144,126,000

Last UpdateAug 14, 2026

Actively maintained (0d ago)

ClawHub community score is a third-party marketplace signal. It is shown separately from SkillsReview editorial assessment and real user review averages.

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