aibox
AGENTS.md1 starsChanged 4 months agoMITView on GitHub
aibox is a lightweight Bash launcher that runs AI coding agents inside a Bubblewrap sandbox. It is the Nix/devShell-oriented successor to aidock: no container image, no session image commits, and no runtime configuration file. The public contract is intentionally small: - bind the current project read/write at the same absolute path; - keep host networking available; - expose Nix store and the Nix daemon socket; - mount only explicit agent state/config paths from $HOME; - mount fixed system agent config…
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 31,843 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository2 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
The file
We split this AGENTS.md into the rules it gives an agent
7 rules. About 0 are common, 5 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
keep host networking available.
- Distinctive: line 16
do not mount Git/GitHub config, SSH agent, GPG agent, the host D-Bus socket, Docker, or Kubernetes state.
- Distinctive: line 29
Keep the runtime interface small.
- Very specific: line 31
Keep Bash formatted with shfmt -i 4 -ci and ShellCheck-clean.
- Very specific: line 32
Use Nix as the primary development path: nix develop -c just check.
- Distinctive: line 33
Add tests for any mount-policy or CLI behavior change.
- Distinctive: line 45
When behavior changes, update README.md in the same change.
≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agent Instructions
Project Overview
aibox is a lightweight Bash launcher that runs AI coding agents inside a
Bubblewrap sandbox. It is the Nix/devShell-oriented successor to aidock: no
container image, no session image commits, and no runtime configuration file.
The public contract is intentionally small:
- bind the current project read/write at the same absolute path;
- keep host networking available;
- expose Nix store and the Nix daemon socket;
- mount only explicit agent state/config paths from
$HOME; - mount fixed system agent config directories read-only when present;
- do not mount Git/GitHub config, SSH agent, GPG agent, the host D-Bus socket, Docker, or Kubernetes state;
- expose selected host desktop services only through explicit flags and a filtered proxy;
- print the final
bwrapcommand to stderr before executing it.
--host-ro is an opt-in compatibility mode. It exposes host files read-only
while retaining the workspace and selected state as writable. It keeps private
runtime paths and does not expose the host systemd bus.
Development Rules
- Edit
aiboxdirectly; there is no generated launcher. - Keep the runtime interface small. Do not add env-var configurability or config files. Use the existing selected-mount flags for explicit host paths.
- Keep Bash formatted with
shfmt -i 4 -ciand ShellCheck-clean. - Use Nix as the primary development path:
nix develop -c just check. - Add tests for any mount-policy or CLI behavior change.
Testing
just checkformats, lints, and runs unit tests.just test-unituses a fakebwrapand should not need kernel namespace support.just test-integrationuses real Bubblewrap and requires Linux user namespaces.
Documentation
When behavior changes, update README.md in the same change. The README should
be explicit about prerequisites and the accident-safety threat model.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

