Zleap-Agent — security grade SAFE, quality 79/100

Security audit verdict: SAFE · quality 79/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by Zleap-AI · Codex Skill · ★ 218

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

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About Zleap-Agent

Workspace Is All Agents Need English | 简体中文 Preview status Zleap-Agent is an early preview. The public repository is intended for source review, local development, and feedback. APIs, UI details, packaging, and release flows may change before a stable release. What Is Zleap-Agent? Zleap-Agent is a workspace-first agent harness for local and OpenAI-compatible models. It is built around one practical idea: An agent should not see every tool, memory, rule, and previous message on every step. It should first know which workspace it is in, then receive only the context needed for that workspace. Instead of treating context as one large prompt, Zleap-Agent separates the agent runtime into workspaces. Each workspace can have its own prompt, tools, skills, memory, model, and execution history. This makes the system easier to reason about when running smaller local models, enterprise-local deployments, or workflows where permissions and data boundaries matter. Highlights Workspace isolation for prompts, tools, skills, models, memory, and history. Web UI for chat, workspaces, assistants, models, tools, MCP servers, skills, memory, tasks, gateway configuration, and artifacts.

agentagent-harnesshermes-agentllmnodejsopenclawzleap-agent

Quick Facts

Stars218
Forks26
LanguageTypeScript
CategoryCodex Skill
LicenseApache-2.0
Quality Score79.3250756686424/100
Open Issues1
Last Updated2026-08-05
Created2026-05-31
Platformsnode
Est. Tokens~15k

Compatible Skills

These tools work well together with Zleap-Agent for enhanced workflows:

  • agent-harness-generator — semantic(0.41)+complementary+same_lang+similar_pop+shared_platform (64%)
  • munder-difflin — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (62%)
  • Repo-to-Agent-Context — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)
  • agent-harness-kit — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (58%)

Zleap-Agent alternative? Top 6 similar tools

Looking for a Zleap-Agent alternative? If you're comparing Zleap-Agent with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • Network-AI by Jovancoding · ⭐ 78

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  • mateclaw by matevip · ⭐ 624

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  • omnicoreagent by omnirexflora-labs · ⭐ 250

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  • bitrouter by bitrouter · ⭐ 233

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  • open-skills by besoeasy · ⭐ 132

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  • openlegion by openlegion-ai · ⭐ 116

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Frequently Asked Questions

What is Zleap-Agent?

Zleap-Agent is Agent Harness developed specifically for local small-parameter models.. It is categorized as a Codex Skill with 218 GitHub stars.

What programming language is Zleap-Agent written in?

Zleap-Agent is primarily written in TypeScript. It covers topics such as agent, agent-harness, hermes-agent.

How do I install or use Zleap-Agent?

You can find installation instructions and usage details in the Zleap-Agent GitHub repository at github.com/Zleap-AI/Zleap-Agent. The project has 218 stars and 26 forks, indicating an active community.

What license does Zleap-Agent use?

Zleap-Agent is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to Zleap-Agent?

The top alternatives to Zleap-Agent on Agent Skills Hub include Network-AI, mateclaw, omnicoreagent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Codex Skill tools