agentcookie-install

An installation workflow that keeps Chrome cookies synchronised between a Mac where you log in and a second Mac or Linux machine where an AI agent works. Cookies are small browser files that preserve sign-ins and session settings.

In plain words
What is it for?
Use it to set up the source and sink machines, pair them, and keep Chrome sessions updated automatically, including injecting cookies into a running Linux Chrome session.
Why use it?
It removes the need to log in again on the agent machine whenever a Chrome session changes. The two machines must be connected through Tailscale, a private network service.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/mvanhorn/agentcookie/skill
Any agent
npx skills add mvanhorn/agentcookie --skill skill
Clone the repo
git clone --depth 1 https://github.com/mvanhorn/agentcookie

Made for: Claude Code, Codex.

Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,147 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00063 $0.02147
Opus 5 $0.00032 $0.01073
Sonnet 5 $0.00013 $0.00429
Haiku 4.5 $0.00006 $0.00215

Measured 2d ago against content hash bad7392e5498, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

agentcookie-install scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

sudo mv agentcookie /usr/local/bin/

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -LO https://github.com/mvanhorn/agentcookie/releases/download/v1.0.0/agentcookie_1.0.0_darwin_arm64.tar.gz
skill/SKILL.md · 240 lines

How it starts

The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.

agentcookie install

You are helping the user install agentcookie on two machines that are both on the same Tailscale tailnet, then pair them, so that the sink's Chrome stays continuously in sync with the source's Chrome.

After install, the user does not touch agentcookie again. The source watches Chrome via fsnotify and pushes every cookie change to the sink within seconds. On Linux, the sink injects cookies via CDP into an already-running Chrome. On macOS, a LaunchAgent keeps the daemon running across reboots.

Inputs you need

  1. Which machine is the source (the Mac the user logs into Chrome on, usually their laptop).
  2. Which machine is the sink (where AI agents act - a Linux VM like Grok Bot, or a second Mac).
  3. Tailscale is up on both.
  4. On Linux: Chrome is running with --remote-debugging-port=9223 (or another port).

If any of these are missing, stop and ask.

Step 0: detect the lay of the land

Run on the current machine:

uname -s  # Darwin = macOS, Linux = Linux
tailscale status 2>&1 | head -20

From the Tailscale status output, identify which host is the Mac and which is the Linux box.

Step 1: confirm source vs sink with the user

Use the platform's blocking question primitive. Phrase it concretely:

I see you're on <current-hostname>. Looks like <other-hostname> (Tailscale IP 100.x.y.z) is your other machine. Should I install agentcookie with <current-hostname> as the source (your logged-in Chrome) and <other-hostname> as the sink (where your agents run)?

Confirm before proceeding. If wrong, ask which is which.

Step 2: install on the Mac source

Install the binary if missing:

# Download from GitHub Releases
curl -LO https://github.com/mvanhorn/agentcookie/releases/download/v1.0.0/agentcookie_1.0.0_darwin_arm64.tar.gz
tar -xzf agentcookie_1.0.0_darwin_arm64.tar.gz
sudo mv agentcookie /usr/local/bin/

Or build from source:

go install github.com/mvanhorn/agentcookie/cmd/[email protected]

Read the full file on GitHub · 240 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 240 lines · 63 tokens per session scan B bad7392e5498

Subscribe to this mod's changes

agentcookie-install is a skill published in the GitHub repository mvanhorn/agentcookie (808 stars, last pushed 8d ago), licensed MIT. It adds 63 tokens to every session and 2,147 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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