glovebox-mcp: Instructions file for Codex

AGENTS.md

glovebox-mcp AGENTS.md is an instructions file for Codex, OpenCode from segentic-lab/glovebox-mcp. It costs 2,178 tokens per session, scanned A, original, MIT.

Operating instructions for using Glovebox, a tool that lets an agent control an isolated desktop window through screenshots and actions.

In plain words
What is it for?
Use it when opening, inspecting, clicking, typing in, or troubleshooting applications inside a Glovebox desktop instance.
Why use it?
It explains how to interpret success and error responses and how to recover from problems such as a dead window or an invalid element reference.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is segentic-lab/glovebox-mcp's own configuration. It tells Codex and OpenCode how to work on glovebox-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything glovebox-mcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to segentic-lab/glovebox-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/segentic-lab/glovebox-mcp/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/segentic-lab/glovebox-mcp

Made for: Codex, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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Per session 2,178 This file is loaded in full into every session.
When invoked 2,178 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.02178 $0.02178
Opus 5.5 $0.00871 $0.00871
Sonnet 5.5 $0.00436 $0.00436
Haiku 4.5 $0.00218 $0.00218

Measured 7d ago against content hash 666ae59d949c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

glovebox-mcp AGENTS.md scanned grade A with 0 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 7d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

glovebox-mcp — instructions for the agent

Paste this into the system prompt / context of any AI agent that will use the glovebox MCP tools. It teaches the agent how to drive the sandbox well and avoid the traps.


You are driving a real, sandboxed desktop through the glovebox MCP tools. Everything you do happens inside a nested X11 window (an "instance"). Your input and vision are confined to that window — but the apps run as the user, with the user's real files, so treat files and logged-in sessions as real.

Responses: read ok and fix

Every tool returns JSON: {"ok": true, "action": …, "instance": …, …}. When a call fails, the result is flagged as an error and contains {"ok": false, "error": …, "fix": …} — fix names the exact call that unblocks you (re-run parse_screen, check list_instances, switch vision mode, etc.). Follow it instead of retrying blindly. The server never reports success for something that didn't happen: a dead instance, an unknown element id, an invalid key name, a zero scroll, an off-screen click, an app that exited on launch all come back as errors. Clamped waits are flagged (settle_clamped), and a screen that would not settle is reported (timed_out: true), not hidden. Start with status() to see the effective vision backend (and why), live instances, GPU and deps in one call.

Mental model

  • Each instance (instance=N, default 1) is one app window on its own display. You cannot see it unless you take a screenshot or parse_screen. Always look before you act.
  • Work observe → act → verify. Never fire a sequence of clicks without confirming the screen changed the way you expected.
  • Coordinates are absolute pixels within that instance's display (top-left origin, 0 <= x < width, 0 <= y < height — get_screen_size tells you the size; anything outside is rejected).

The core loop

  1. Look — screenshot(instance) to see the screen, or parse_screen(instance) to get detected elements with ids + pixel-centers. Zoom with screenshot(region="x,y,w,h") when text is small.
  2. Act — click, type_text, press_keys, scroll, drag, click_element, upload_file.
  3. Verify — pass observe="screenshot" (or "parse") to the action and it returns the resulting screen in the same call (no extra round-trip). Add settle_ms=400..1500 after anything that triggers loading/navigation, or call wait_for_stable(instance, observe="screenshot") when you don't know how long it takes. window_info(instance) confirms a page/app change by title alone.

Read the full file on GitHub · 139 lines

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. 7d ago Changed · +28 lines · +655 tokens per session 666ae59d949c
  2. 2mo ago First seen · 111 lines · 1,523 tokens per session scan A 303f25df0fd1

Subscribe to this mod's changes

glovebox-mcp AGENTS.md is an instructions file published in the GitHub repository segentic-lab/glovebox-mcp (13 stars, last pushed 7d ago), licensed MIT. It adds 2,178 tokens to every session, about $0.0087 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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