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github-codespaces-efficiency

drvoss/everything-copilot-cli/skills/copilot-exclusive/github-codespaces-efficiency/SKILL.md

Use when optimizing GitHub Codespaces — faster startup times, lower spend, slimmer devcontainers, right-sizing machines, or scoping prebuilds.

Skill47 starsChanged 56 days ago

What's in it

  1. GitHub Codespaces Efficiency
  2. Why This is Copilot-Exclusive
  3. When to Use
  4. When NOT to Use
  5. Prerequisites
  6. Load Only What You Need
  7. Core Workflow
  8. 1. Measure first
  9. 2. Apply guardrails
  10. 3. Select the top 3 fixes
  11. 4. Verify
  12. Required Output
  13. Tips
  14. See Also
---
name: github-codespaces-efficiency
description: >
  Use when optimizing GitHub Codespaces — faster startup times, lower spend,
  slimmer devcontainers, right-sizing machines, or scoping prebuilds.
metadata:
  category: copilot-exclusive
  agent_type: general-purpose
  origin: adapted from github/awesome-copilot github-codespaces-efficiency (MIT)
---

# GitHub Codespaces Efficiency

Audit GitHub Codespaces efficiency with a GitHub-native lens. Focus on devcontainer size,
startup time, machine sizing, prebuild scope, and idle-time discipline without stripping away
tools the team relies on every day.

## Why This is Copilot-Exclusive

GitHub Codespaces is a GitHub-native development environment. This skill is most useful when
you can inspect repository configuration, correlate it with `gh`-based Codespaces metadata,
and turn the result into Copilot-driven GitHub workflow guidance.

## When to Use

- Codespaces start too slowly or cost more than the team expects
- `.devcontainer/` exists and needs trimming, right-sizing, or prebuild tuning
- A team wants guidance on machine sizing, idle timeout, or prebuild scope
- The repository is onboarding Codespaces for the first time and needs a minimal baseline

## When NOT to Use

| Instead of github-codespaces-efficiency | Use |
|-----------------------------------------|-----|
| Debugging a failing GitHub Actions run | `actions-debugging` |
| Reviewing PR lifecycle and checks | `github-pr-workflow` |
| General local development environment setup without Codespaces | ordinary repo setup guidance |

## Prerequisites

- Access to `.devcontainer/` when it exists
- `gh` CLI access if you want live Codespaces or machine data
- Understanding of the team's baseline tooling requirements

## Load Only What You Need

- [`../../../references/github-codespaces-efficiency/codespaces.md`](../../../references/github-codespaces-efficiency/codespaces.md) - audit order, preferred fix order, safe-change rules, and reporting focus
- [`../../../references/github-codespaces-efficiency/review-rubric.md`](../../../references/github-codespaces-efficiency/review-rubric.md) - compact rubric for review passes

If no `.devcontainer/` exists yet, start with `codespaces.md` and define a minimal baseline
before optimizing.

## Core Workflow

### 1. Measure first

```powershell
Get-ChildItem .devcontainer -Recurse -File | Select-Object -ExpandProperty FullName
gh codespace list
$repo = gh repo view --json nameWithOwner --jq ".nameWithOwner"
gh api "/repos/$repo/codespaces/machines"
```

If `gh` auth fails or the user lacks repo admin scope, continue with static analysis of
`.devcontainer/` files and mark machine-type or prebuild recommendations as unverified.

Look for:

- devcontainer image larger than the task justifies
- too many features, packages, or extensions
- machine types larger than usage patterns support
- missing `devcontainer-lock.json`
- prebuilds scoped too broadly
- idle timeout guidance mismatched to actual usage

### 2. Apply guardrails

1. Do not remove tools the team uses every day.
2. Do not assume smaller is always better; balance cost against developer throughput.
3. Do not turn the devcontainer into a production image unless the team explicitly needs it.
4. Prefer incremental changes for existing configs; a greenfield reset is for missing configs, not stable ones.
5. Split repo-editable changes from org-level or user-level Codespaces settings.

### 3. Select the top 3 fixes

Rank by expected monthly savings or startup-time improvement:

1. trim the devcontainer
2. right-size the machine type
3. scope prebuilds to sustained-usage branches
4. tune idle timeout
5. remove unused extensions or port-forwarding rules
6. reduce image size and improve layer caching

Keep only evidence-backed, guardrail-safe recommendations. Return up to three.

### 4. Verify

- Start a test Codespace when possible and confirm that devcontainer changes still build and boot correctly.
- Validate machine sizing against observed usage when telemetry exists; otherwise mark it as an assumption.
- Treat startup or build regressions as real bugs even if the configuration looks "cleaner" on paper.

## Required Output

1. **Waste sources** - top startup-time or cost drivers
2. **Proposed fixes** - up to 3 recommendations backed by audit evidence
3. **Validation** - live, static-only, and unverified areas
4. **Impact** - expected versus measured startup time, spend, and utilization

## Tips

- Optimize the slowest, most common developer path first
- Separate startup-time wins from steady-state cost wins
- Prefer documentation changes when the real control lives outside the repository
- Keep prebuild recommendations tight and usage-based

## See Also

- [`github-pr-workflow`](../github-pr-workflow/SKILL.md) - manage GitHub pull requests and related checks
- [`actions-debugging`](../actions-debugging/SKILL.md) - debug workflow failures that block Codespaces-related changes
- [`using-git-worktrees`](../../workflow/using-git-worktrees/SKILL.md) - isolate risky environment changes in a separate checkout

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