devcontainer-setup-v2

name: devcontainer-setup-v2 description: "Devcontainer Setup Skill workflow skill. Use this skill when the user needs Creates devcontainers with Claude Code, language-specific tooling (Python/Node/Rust/Go), and persistent volumes. Use when adding devcontainer support to a project, setting up isolated development environments, or configuring sandboxed Claude Code workspaces and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off." version: "0.0.1" category: tools tags: ["devcontainer-setup-v2", "devcontainer-setup", "creates", "devcontainers", "claude", "language-specific", "tooling", "python"] complexity: advanced risk: caution tools: ["codex-cli", "claude-code", "cursor", "gemini-cli", "opencode"] source: community author: "sickn33" date_added: "2026-04-16" date_updated: "2026-04-25"

Devcontainer Setup Skill

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/devcontainer-setup from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Devcontainer Setup Skill Creates a pre-configured devcontainer with Claude Code and language-specific tooling.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Phase 1: Project Reconnaissance, Phase 2: Generate Configuration, Base Template Features, Language-Specific Sections, Adding Persistent Volumes, Output Files.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• User asks to "set up a devcontainer" or "add devcontainer support"
• User wants a sandboxed Claude Code development environment
• User needs isolated development environments with persistent configuration
• User already has a devcontainer configuration and just needs modifications
• User is asking about general Docker or container questions
• User wants to deploy production containers (this is for development only)

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. ``mermaid flowchart TB start([User requests devcontainer]) recon[1.
2. Project Reconnaissance] detect[2.
3. Detect Languages] generate[3.
4. Generate Configuration] write[4.
5. Write files to .devcontainer/] done([Done]) start --> recon recon --> detect detect --> generate generate --> write write --> done ``
6. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
7. Read the overview and provenance files before loading any copied upstream support files.

Imported Workflow Notes

Imported: Workflow

flowchart TB
    start([User requests devcontainer])
    recon[1. Project Reconnaissance]
    detect[2. Detect Languages]
    generate[3. Generate Configuration]
    write[4. Write files to .devcontainer/]
    done([Done])

    start --> recon
    recon --> detect
    detect --> generate
    generate --> write
    write --> done

Imported: Phase 1: Project Reconnaissance

Infer Project Name

Check in order (use first match):

1. package.json → name field
2. pyproject.toml → project.name
3. Cargo.toml → package.name
4. go.mod → module path (last segment after /)
5. Directory name as fallback

Convert to slug: lowercase, replace spaces/underscores with hyphens.

Detect Language Stack

Multi-Language Projects

If multiple languages are detected, configure all of them in the following priority order:

1. Python - Primary language, uses Dockerfile for uv + Python installation
2. Node/TypeScript - Uses devcontainer feature
3. Rust - Uses devcontainer feature
4. Go - Uses devcontainer feature

For multi-language postCreateCommand, chain all setup commands:

uv run /opt/post_install.py && uv sync && npm ci

Extensions and settings from all detected languages should be merged into the configuration.

Examples

Example 1: Ask for the upstream workflow directly

Use @devcontainer-setup-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @devcontainer-setup-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @devcontainer-setup-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @devcontainer-setup-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/devcontainer-setup, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Reference Material

For additional guidance, see:

• references/dockerfile-best-practices.md - Layer optimization, multi-stage builds, architecture support
• references/features-vs-dockerfile.md - When to use devcontainer features vs custom Dockerfile

Imported: Phase 2: Generate Configuration

Start with base templates from resources/ directory. Substitute:

• {{PROJECT_NAME}} → Human-readable name (e.g., "My Project")
• {{PROJECT_SLUG}} → Slug for volumes (e.g., "my-project")

Then apply language-specific modifications below.

Imported: Base Template Features

The base template includes:

• Claude Code with marketplace plugins (anthropics/skills, trailofbits/skills, trailofbits/skills-curated)
• Python 3.13 via uv (fast binary download)
• Node 22 via fnm (Fast Node Manager)
• ast-grep for AST-based code search
• Network isolation tools (iptables, ipset) with NET_ADMIN capability
• Modern CLI tools: ripgrep, fd, fzf, tmux, git-delta

Imported: Language-Specific Sections

Python Projects

Detection: pyproject.toml, requirements.txt, setup.py, or *.py files

Dockerfile additions:

The base Dockerfile already includes Python 3.13 via uv. If a different version is required (detected from pyproject.toml), modify the Python installation:

# Install Python via uv (fast binary download, not source compilation)
RUN uv python install <version> --default

devcontainer.json extensions:

Add to customizations.vscode.extensions:

"ms-python.python",
"ms-python.vscode-pylance",
"charliermarsh.ruff"

Add to customizations.vscode.settings:

"python.defaultInterpreterPath": ".venv/bin/python",
"[python]": {
  "editor.defaultFormatter": "charliermarsh.ruff",
  "editor.codeActionsOnSave": {
    "source.organizeImports": "explicit"
  }
}

postCreateCommand: If pyproject.toml exists, chain commands:

rm -rf .venv && uv sync && uv run /opt/post_install.py

Node/TypeScript Projects

Detection: package.json or tsconfig.json

No Dockerfile additions needed: The base template includes Node 22 via fnm (Fast Node Manager).

devcontainer.json extensions:

Add to customizations.vscode.extensions:

"dbaeumer.vscode-eslint",
"esbenp.prettier-vscode"

Add to customizations.vscode.settings:

"editor.defaultFormatter": "esbenp.prettier-vscode",
"editor.codeActionsOnSave": {
  "source.fixAll.eslint": "explicit"
}

postCreateCommand: Detect package manager from lockfile and chain with base command:

• pnpm-lock.yaml → uv run /opt/post_install.py && pnpm install --frozen-lockfile
• yarn.lock → uv run /opt/post_install.py && yarn install --frozen-lockfile
• package-lock.json → uv run /opt/post_install.py && npm ci
• No lockfile → uv run /opt/post_install.py && npm install

Rust Projects

Detection: Cargo.toml

Features to add:

"ghcr.io/devcontainers/features/rust:1": {}

devcontainer.json extensions:

Add to customizations.vscode.extensions:

"rust-lang.rust-analyzer",
"tamasfe.even-better-toml"

Add to customizations.vscode.settings:

"[rust]": {
  "editor.defaultFormatter": "rust-lang.rust-analyzer"
}

postCreateCommand: If Cargo.lock exists, use locked builds:

uv run /opt/post_install.py && cargo build --locked

If no lockfile, use standard build:

uv run /opt/post_install.py && cargo build

Go Projects

Detection: go.mod

Features to add:

"ghcr.io/devcontainers/features/go:1": {
  "version": "latest"
}

devcontainer.json extensions:

Add to customizations.vscode.extensions:

"golang.go"

Add to customizations.vscode.settings:

"[go]": {
  "editor.defaultFormatter": "golang.go"
},
"go.useLanguageServer": true

postCreateCommand:

uv run /opt/post_install.py && go mod download

Imported: Adding Persistent Volumes

Pattern for new mounts in devcontainer.json:

"mounts": [
  "source={{PROJECT_SLUG}}-<purpose>-${devcontainerId},target=<container-path>,type=volume"
]

Common additions:

• source={{PROJECT_SLUG}}-cargo-${devcontainerId},target=/home/vscode/.cargo,type=volume (Rust)
• source={{PROJECT_SLUG}}-go-${devcontainerId},target=/home/vscode/go,type=volume (Go)

Imported: Output Files

Generate these files in the project's .devcontainer/ directory:

1. Dockerfile - Container build instructions
2. devcontainer.json - VS Code/devcontainer configuration
3. post_install.py - Post-creation setup script
4. .zshrc - Shell configuration
5. install.sh - CLI helper for managing the devcontainer (devc command)

Imported: Validation Checklist

Before presenting files to the user, verify:

1. All {{PROJECT_NAME}} placeholders are replaced with the human-readable name
2. All {{PROJECT_SLUG}} placeholders are replaced with the slugified name
3. JSON syntax is valid in devcontainer.json (no trailing commas, proper nesting)
4. Language-specific extensions are added for all detected languages
5. postCreateCommand includes all required setup commands (chained with &&)

Imported: User Instructions

After generating, inform the user:

1. How to start: "Open in VS Code and select 'Reopen in Container'"
2. Alternative: devcontainer up --workspace-folder .
3. CLI helper: Run .devcontainer/install.sh self-install to add the devc command to PATH

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.