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Contributing to OpenShell

OpenShell is built agent-first. We design systems and use agents to implement them. Your agent is your first collaborator — point it at this repo before opening issues, asking questions, or submitting code.

The Critical Rule

You must understand your code. Using AI agents to write code is not just acceptable, it's how this project works. But you must be able to explain what your changes do and how they interact with the rest of the system. If you can't, don't submit it.

Submitting agent-generated code without understanding it — regardless of how clean it looks — wastes maintainer time and will result in your PR being closed. Repeat offenders will be blocked from the project.

AI Usage

OpenShell is agent-first, not agent-only. The distinction matters:

  • Do use agents to explore the codebase, run diagnostics, generate code, and iterate on implementations.
  • Do use the skills in .agents/skills/ — they exist to make your agent effective.
  • Do interrogate your agent until you understand every edge case and interaction in your changes.
  • Don't submit code you can't explain without your agent open.
  • Don't use agents as a substitute for understanding the system. Read the architecture docs.

First-Time Contributors

We use a vouch system. This exists because AI makes it trivial to generate plausible-looking but low-quality contributions, and we can no longer trust by default.

  1. Open a Vouch Request discussion.
  2. Describe what you want to change and why.
  3. Write in your own words. AI-generated vouch requests will be denied.
  4. A maintainer will comment /vouch if approved.
  5. Once vouched, you can submit pull requests.

If you are not vouched, any pull request you open will be automatically closed. Org members and collaborators with push access bypass this check.

Finding Work

Issues labeled good-first-issue are scoped, well-documented, and friendly to new contributors. Start there. If you need guidance, comment on the issue.

All open issues are actionable — if it's in the issue tracker, it's ready to be worked on.

Before You Open an Issue

This project ships with agent skills that can diagnose problems, explore the codebase, generate policies, and walk you through common workflows. Before filing an issue:

  1. Clone the repo and point your coding agent at it.
  2. Load the relevant skill - debug-openshell-cluster for cluster problems, debug-inference for inference setup problems, openshell-cli for usage questions, generate-sandbox-policy for policy help.
  3. Have your agent investigate. Let it run diagnostics, read the architecture docs, and attempt a fix.
  4. If the agent cannot resolve it, open an issue with the agent's diagnostic output attached. The issue template requires this.

When to Open an Issue

  • A real bug that your agent confirmed and could not fix.
  • A feature proposal with a design — not a "please build this" request.
  • An infrastructure problem that the debug-openshell-cluster skill could not resolve.
  • An inference setup problem that the debug-inference skill could not resolve.
  • Security vulnerabilities must follow SECURITY.md — not GitHub issues.

When NOT to Open an Issue

  • Questions about how things work — your agent can answer these from the codebase and architecture docs.
  • Configuration problems - your agent can diagnose these with openshell-cli, debug-openshell-cluster, and debug-inference.
  • "How do I..." requests — the skills cover CLI usage, policy generation, TUI development, and more.

Agent Skills for Contributors

Skills live in .agents/skills/. Your agent's harness can discover and load them natively. Here is the full inventory:

Category Skill Purpose
Getting Started openshell-cli CLI usage, sandbox lifecycle, provider management, BYOC workflows
Getting Started debug-openshell-cluster Diagnose cluster startup failures and health issues
Getting Started debug-inference Diagnose inference.local, host-backed local inference, and direct external inference setup issues
Contributing create-spike Investigate a problem, produce a structured GitHub issue
Contributing build-from-issue Plan and implement work from a GitHub issue (maintainer workflow)
Contributing create-github-issue Create well-structured GitHub issues
Contributing create-github-pr Create pull requests with proper conventions
Reviewing review-github-pr Summarize PR diffs and key design decisions
Reviewing review-security-issue Assess security issues for severity and remediation
Reviewing watch-github-actions Monitor CI pipeline status and logs
Triage triage-issue Assess, classify, and route community-filed issues
Platform generate-sandbox-policy Generate YAML sandbox policies from requirements or API docs
Platform tui-development Development guide for the ratatui-based terminal UI
Documentation update-docs Scan recent commits and draft doc updates for user-facing changes
Maintenance sync-agent-infra Detect and fix drift across agent-first infrastructure files
Reference sbom Generate SBOMs and resolve dependency licenses

Workflow Chains

Skills connect into pipelines. Individual skill files don't describe these relationships.

  • Community inflow: triage-issue → create-spike → build-from-issue
  • Internal development: create-spike → build-from-issue
  • Security: review-security-issue → fix-security-issue
  • Policy iteration: openshell-cli → generate-sandbox-policy

Workflow state labels use the state:* prefix, and security work uses topic:security. GitHub issue templates assign built-in issue types where applicable, and agent-created issues should use issue types or manual follow-up rather than type labels.

Prerequisites

Install mise. This is used to set up the development environment.

# Install mise (macOS/Linux)
curl https://mise.run | sh

After installing mise, activate it with mise activate or add it to your shell.

Shell setup examples:

# Fish
echo '~/.local/bin/mise activate fish | source' >> ~/.config/fish/config.fish

# Zsh
echo 'eval "$(~/.local/bin/mise activate zsh)"' >> ~/.zshrc

Project requirements:

  • Rust 1.88+
  • Python 3.12+
  • Docker (running)

Getting Started

# One-time trust
mise trust

# Launch a sandbox (deploys a cluster if one isn't running)
mise run sandbox

Building the openshell CLI

Inside this repository, openshell is a local shortcut script at scripts/bin/openshell. The script will

  1. Build openshell-cli if needed.
  2. Run the local debug CLI binary under target/debug/openshell.

Because mise adds scripts/bin to PATH for this project, you can run openshell directly from the repo.

openshell --help
openshell sandbox create -- codex

Cluster debugging helpers

Two additional scripts in scripts/bin/ provide gateway-aware wrappers for cluster debugging:

Script What it does
kubectl Runs kubectl inside the active gateway's k3s container via openshell doctor exec
k9s Runs k9s inside the active gateway's k3s container via openshell doctor exec

These work for both local and remote gateways (SSH is handled automatically). Examples:

kubectl get pods -A
kubectl logs -n openshell statefulset/openshell
k9s
k9s -n openshell

Main Tasks

These are the primary mise tasks for day-to-day development:

Task Purpose
mise run cluster Bootstrap or incremental deploy
mise run sandbox Create a sandbox on the running cluster
mise run test Default test suite
mise run e2e Default end-to-end test lane
mise run ci Full local CI checks (lint, compile/type checks, tests)
mise run docs Build and serve documentation locally
mise run clean Clean build artifacts

Project Structure

Path Purpose
crates/ Rust crates
python/ Python SDK and bindings
proto/ Protocol buffer definitions
tasks/ mise task definitions and build scripts
deploy/ Dockerfiles, Helm chart, Kubernetes manifests
architecture/ Architecture docs and plans
docs/ User-facing documentation (Sphinx/MyST)
.agents/ Agent skills and persona definitions

Documentation

If your change affects user-facing behavior (new flags, changed defaults, new features, bug fixes that contradict existing docs), update the relevant pages under docs/ in the same PR.

To ensure your doc changes follow NVIDIA documentation style, use the update-docs skill. It scans commits, identifies doc pages that need updates, and drafts content that follows the style guide in docs/CONTRIBUTING.md.

To build and preview docs locally:

mise run docs # to build the docs locally
mise run docs:serve # to serve locally and automatically rebuild on changes

See docs/CONTRIBUTING.md for more details.

Pull Requests

  1. Create a feature branch from main.
  2. Make your changes with tests.
  3. Run mise run ci to verify.
  4. Open a PR using the create-github-pr skill or manually following the PR template.

Commit Messages

This project uses Conventional Commits. All commit messages must follow the format:

<type>(<scope>): <description>

[optional body]

[optional footer(s)]

Types:

  • feat - New feature
  • fix - Bug fix
  • docs - Documentation only
  • chore - Maintenance tasks (dependencies, build config)
  • refactor - Code change that neither fixes a bug nor adds a feature
  • test - Adding or updating tests
  • ci - CI/CD changes
  • perf - Performance improvements

Examples:

feat(cli): add --verbose flag to openshell run
fix(sandbox): handle timeout errors gracefully
docs: update installation instructions
chore(deps): bump tokio to 1.40

DCO

All contributions must include a Signed-off-by line in each commit message. This certifies you have the right to submit the work under the project license. See the Developer Certificate of Origin.

git commit -s -m "feat(sandbox): add new capability"