jcode

Name: jcode
Author: 1jehuang

by 1jehuang

Verified

The most RAM efficient harness

17,865stars

2,002forks

Rust

Added 7/4/2026

Installation

# Add to your Claude Code skills
git clone https://github.com/1jehuang/jcode

Getting Started

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Security ReportVerified

Last scanned: 7/4/2026

{
  "issues": [
    {
      "file": "README.md",
      "line": 37,
      "type": "remote-install",
      "message": "Install command (remote install script piped to a shell — review the source before running): \"curl -fsSL https://raw.githubusercontent.com/1jehuang/jcode/master/scripts/insta\"",
      "severity": "low"
    }
  ],
  "status": "PASSED",
  "scannedAt": "2026-07-04T06:46:26.138Z",
  "npmAuditRan": true,
  "pipAuditRan": true,
  "promptInjectionRan": true
}

README.md

Frequently Asked Questions

What is jcode?

jcode is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by 1jehuang. The most RAM efficient harness. It has 17,865 GitHub stars.

Is jcode safe to use?

Yes. jcode 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.

How do I install jcode?

Clone the repository with "git clone https://github.com/1jehuang/jcode" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is jcode written in?

jcode is primarily written in Rust. It is open-source under 1jehuang on GitHub, so you can review or fork the full source.

Are there alternatives to jcode?

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 jcode against similar tools.

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jcode

The most RAM efficient harness The most intelligent harness

Website · Docs · SDK · Benchmarks · Features · Install · Quick Start · Further Reading · Contributing

Installation

# macOS & Linux
curl -fsSL https://jcode.sh/install | bash

# Windows 11 (PowerShell 5.1+)
irm https://jcode.sh/install.ps1 | iex

Need Homebrew, source builds, provider setup, or want an agent to set it up for you? Jump to detailed installation.

Performance & Resource Efficiency

jcode is built to be as performant and resource efficient as possible. Every metric is optimized to the bone, which is important for scaling multi-session workflows. Here we sample a few metrics to show the difference: RAM usage and boot up.

RAM comparison

Time to first frame

Tool	Time to first frame	Range	Comparison
jcode	14.0 ms	10.1–19.3 ms	baseline
Antigravity CLI	383.5 ms	363.1–415.4 ms	27.4× slower
pi	590.7 ms	369.6–934.8 ms	42.2× slower
Codex CLI	882.8 ms	742.3–1640.9 ms	63.1× slower
OpenCode	1035.9 ms	922.5–1104.4 ms	74.0× slower
GitHub Copilot CLI	1518.6 ms	1357.4–1826.8 ms	108.5× slower
Cursor Agent	1949.7 ms	1711.0–2104.8 ms	139.3× slower
Claude Code	3436.9 ms	2032.7–8927.2 ms	245.5× slower

Measured on this Linux machine across 10 interactive PTY launches.

Time to first input

(time until typed probe text appears on the rendered screen; Antigravity uses its internal input-ready log marker because the sign-in screen suppresses probe echo.)

Tool	Time to first input	Range	Comparison
jcode	48.7 ms	30.3–62.7 ms	baseline
Antigravity CLI	383.7 ms	363.4–415.7 ms	7.9× slower
pi	596.4 ms	373.9–955.2 ms	12.2× slower
Codex CLI	905.8 ms	760.1–1675.7 ms	18.6× slower
OpenCode	1047.9 ms	931.1–1116.9 ms	21.5× slower
GitHub Copilot CLI	1583.4 ms	1422.8–1880.0 ms	32.5× slower
Cursor Agent	1978.7 ms	1727.3–2130.0 ms	40.6× slower
Claude Code	3512.8 ms	2137.4–9002.0 ms	72.2× slower

Measured on this Linux machine across 10 interactive PTY launches. Antigravity CLI was unauthenticated for this run; its sign-in screen rendered normally and emitted an internal CLI ready for user input marker, but did not echo the typed probe.

Additional clients / memory scaling

Tool	Extra PSS per added session	Comparison
jcode (local embedding off)	~9.9 MB	baseline
jcode	~10.4 MB	1.1× more RAM
pi	~76.5 MB	7.7× more RAM
Codex CLI	~21.6 MB	2.2× more RAM
OpenCode	~318.4 MB	32.2× more RAM
GitHub Copilot CLI	~158.1 MB	16.0× more RAM
Cursor Agent	~157.5 MB	15.9× more RAM
Claude Code	~212.7 MB	21.5× more RAM
Antigravity CLI	~86.4 MB	8.7× more RAM

jcode v0.9.1888-dev (be386f2)
pi 0.62.0
codex-cli 0.120.0
opencode 1.0.203
GitHub Copilot CLI 1.0.24 for the 1-session rerun, GitHub Copilot CLI 1.0.27 for the 10-session rerun
Cursor Agent 2026.04.08-a41fba1
Claude Code 2.1.86 (Claude Code)
Antigravity CLI 1.0.0