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.
curl -O https://raw.githubusercontent.com/segentic-lab/glovebox-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/segentic-lab/glovebox-mcpWrote 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.
[](https://agentmods.dev/instructions/segentic-lab/glovebox-mcp/agents-md)<a href="https://agentmods.dev/instructions/segentic-lab/glovebox-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/segentic-lab/glovebox-mcp/agents-md.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01523 | $0.01523 |
| Opus 5 | $0.00762 | $0.00762 |
| Sonnet 5 | $0.00305 | $0.00305 |
| Haiku 4.5 | $0.00152 | $0.00152 |
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.
How it starts
The opening of the file, as written. The whole thing — 111 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"), isolated from the user's real screen and files.
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, 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 all come back as errors.
Start with status() to see the vision backend, live instances, and installed deps in one call.
Mental model
- Each instance (
instance=N, default1) is one app window on its own display. You cannot see it unless you take ascreenshotorparse_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).
The core loop
- Look —
screenshot(instance)to see the screen, orparse_screen(instance)to get detected elements with ids + pixel-centers. - Act —
click,type_text,press_keys,scroll,drag,click_element,upload_file. - Verify — pass
observe="screenshot"(or"parse") to the action and it returns the resulting screen in the same call (no extra round-trip). Addsettle_ms=400..1500after anything that triggers loading/navigation so the UI settles before the screenshot.
Grounding: how to know WHERE to click
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.
- 7d ago First seen · 111 lines · 1,523 tokens per session scan A 303f25df0fd1
glovebox-mcp AGENTS.md is an instructions file published in the GitHub repository segentic-lab/glovebox-mcp (13 stars, last pushed 2mo ago), licensed MIT. It adds 1,523 tokens to every session, about $0.0076 per session on Opus 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.
Other instructions, from other repositories
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vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
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