Maintainer of this skill?
Automated security scan — not a certification.
Turn long-horizon goals into verifiable results. A local-first semantic control plane and research workbench for long-running agent teams, across sessions and runtimes.
# Add to your Claude Code skills
git clone https://github.com/loopx-project/loopxGuides for using ai agents skills like loopx.
Last scanned: 9/24/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-09-24T09:01:03.501Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}See how loopx compares with popular alternatives.
loopx is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by loopx-project. Turn long-horizon goals into verifiable results. A local-first semantic control plane and research workbench for long-running agent teams, across sessions and runtimes. It has 6,559 GitHub stars.
Yes. loopx passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/loopx-project/loopx" and add it to your Claude Code skills directory (see the Installation section above).
loopx is primarily written in Python. It is open-source under loopx-project on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh loopx against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
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Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Automated security scan — not a certification.
Turn long-horizon goals into verifiable results.
A local-first semantic control plane and research workbench for long-running agent teams, across sessions and runtimes. Keep goals, decisions, ownership and evidence durable. Work with Codex, Claude Code, DeepSeek Harness and other runtimes you already use.
Get started · Why LoopX · See it in action · Evidence · Contribute · Docs · 简体中文
1. Install LoopX and its Agent skills. Requires Python 3.11+ and Node.js 22.22.3+ (24 LTS recommended).
python3 -m pip install --upgrade loopx && loopx workflow-skills --install
2. Give your Agent a concrete task. Restart your Agent host, open your project, then send this in Codex:
$loopx speed up this project's slowest workflow; compare approaches and verify the gains
Claude Code uses /loopx <complex task>; see host setup
for other runtimes. Prefer a guided first run? Choose a task below.
An agent can finish a task in one session. Long-running work is harder: objectives change, owner decisions appear, evidence goes stale, and agents hand work to peers. A timer can keep a loop running without making it useful.
Your Agent runtime supplies the model and tools. LoopX’s semantic control plane preserves goals, acceptance, decisions, ownership and evidence across sessions and runtimes for engineering, research and operations. Agents and people use those facts to reassess what to do next. Human authorization still governs protected actions.
| What you want to do | Start here |
|---|---|
| Keep a coding or research agent working across sessions | Install and start |
| Manage personal projects, schedules and decisions in one place | Personal Agent Workspace |
| Let agents collaborate and deliver verifiable results | Agent collaboration guide |
LoopX keeps the durable control state in one compact layer:
Agent runtimes execute the work. LoopX governs the state that lets engineering, research, discovery, and operations loops continue across runs. It is not another agent framework or a provider-specific orchestration runtime.
A useful mental model is an agent-native Kanban for long-running work. Cards carry identity, authority, evidence, and continuation. Moves are validated operators such as claim, gate, monitor, and writeback. The board is a projection; LoopX state remains the source of truth.
Registered agents are peers. Claims, leases, task boundaries, capabilities, and typed continuation decide who acts next; no durable leader identity is required.
LoopX is useful when you run:
LoopX is not an autonomous production controller. Dangerous permissions, publishing, production writes, and final ownership stay with the human.
Watch the research-workbench film · 86s · transcripts, subtitles and sources. Recorded App excerpts, synthetic examples and illustrations are labelled.
Open a Goal to inspect its work, responsible Agents and recorded Explore history. Use Deep analysis to inspect a registered trajectory, its citations, native outcome readback and separately measured costs. An Agent prepares the source; opening a page or reading a resul