#7474th of 149 in Skills, plugins and rules

loopx

Local control plane that keeps goals and evidence for long-running coding agents

Stars
6.3k
License
Apache-2.0
Last commit
Oct 2026
Last release
Oct 2026
Language
Python
Stars, last 19 weeks+6,305
3 Jun 2026: 11 stars10 Jun 2026: 13 stars17 Jun 2026: 17 stars24 Jun 2026: 35 stars1 Jul 2026: 83 stars8 Jul 2026: 102 stars15 Jul 2026: 118 stars22 Jul 2026: 152 stars29 Jul 2026: 164 stars5 Aug 2026: 2,360 stars12 Aug 2026: 4,413 stars19 Aug 2026: 4,907 stars26 Aug 2026: 5,156 stars2 Sept 2026: 5,440 stars9 Sept 2026: 5,730 stars16 Sept 2026: 5,848 stars23 Sept 2026: 5,945 stars30 Sept 2026: 6,114 stars7 Oct 2026: 6,193 stars14 Oct 2026: 6,316 stars

11 on 3 Jun 20266,316 on 14 Oct 2026

From GitHub's daily star counts.

Checked on GitHub.

Overview

LoopX installs as a skill for Codex, Claude Code and DeepSeek Harness. It stores goals, Todos, decisions and evidence outside the chat session, so an agent can continue across runs through a heartbeat or loop driver and ask the owner when a gate is hit. It includes a local browser/PWA dashboard (`loopx dashboard`) and a CLI (`loopx status`, `loopx doctor`).

Who it is for: Engineers running multi-day agent loops in Codex or Claude Code

Strengths

  • Works with Codex, Claude Code and DeepSeek Harness without replacing their runtime
  • Goal state, decisions and evidence persist across sessions and restarts
  • Local-first dashboard shows what is running, waiting on you, or scheduled
  • Publishes LHTB results: 0.4948 mean reward vs 0.4218 for plain Codex on 46 tasks

Weaknesses

  • LHTB uses one trial per task and unequal budgets; not an isolated causal estimate
  • Strict pass rate (7/46) matches plain Codex; the gain is mostly partial credit
  • Needs Python 3.11+ and Node.js 22.22.3+ installed
  • Desktop App is ad-hoc signed, not notarized; Windows preview updates are manual

What it needs

  • Needs Python 3.11+, Node.js 22.22.3+, Codex, Claude Code or DeepSeek Harness
  • Models: Codex, Claude Code, DeepSeek Harness, direct-model sessions

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