Github-Codespaces-Efficiency
Github-Codespaces-Efficiency是一款productivity方向的AI技能,核心价值是Audit and improve GitHub Codespaces efficiency,可用于解决开发者在productivity领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
Audit and improve GitHub Codespaces efficiency. Use this skill when a user wants faster Codespaces startup, lower Codespaces spend, slim devcontainers, right-size machines, tune idle timeout, or scope
mkdir -p ./skills/github-codespaces-efficiency && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/github-codespaces-efficiency/SKILL.md -o ./skills/github-codespaces-efficiency/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# GitHub Codespaces Efficiency
Use this skill as a lean entrypoint for GitHub Codespaces efficiency work. Inspect the repo, identify waste, and load only needed references.
If no `.devcontainer/` exists yet, load [`references/codespaces.md`](./references/codespaces.md) and define a baseline before proceeding with the steps below.
Use This Skill When
- The user wants faster Codespaces startup or lower Codespaces spend.
- The repo has a `.devcontainer/` or explicit Codespaces configuration questions.
- The user asks for devcontainer optimization, machine sizing, prebuild strategy, or idle-timeout guidance.
- The user is setting up Codespaces for the first time or needs help creating a new `.devcontainer/` from scratch.
Load Only What You Need
- [`references/codespaces.md`](./references/codespaces.md) — devcontainer, machine-sizing, prebuild, idle-timeout guidance, and reporting.
- [`references/review-rubric.md`](./references/review-rubric.md) — load only for review passes.
Core Workflow
1. Measure first
find .devcontainer -maxdepth 2 -type f
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, proceed with static analysis of `.devcontainer/` files; mark machine-type and prebuild recommendations as unverified.
Look for: devcontainer image >2 GB or more than 10 features, machine type larger than usage data supports, missing `devcontainer-lock.json` (recommend adding — many repos predate lock-file support), prebuilds scoped too broadly, and idle timeout mismatched to usage patterns.
2. Apply guardrails
Check each proposed fix against these rules before recommending it:
1. Does not remove tools the team uses every day — drop any fix that strips required development tools or extensions.
2. Does not assume smaller is always better — balance machine cost against developer experience and throughput.
3. Does not turn the devcontainer into a production image — drop any fix that adds production-only dependencies unless the team explicitly requires it.
4. Incremental changes preferred — a greenfield baseline is appropriate only when no `.devcontainer/` exists; flag (do not drop) changes that restructure an existing config.
5. Repo changes stay separate from org settings — split any fix that mixes repo-editable files with org-level or user-level Codespaces settings into two distinct recommendations.
3. Select the top 3 fixes
From the six candidates below, keep only those supported by audit evidence from step 1 *and* passing all guardrails from step 2. Rank survivors by estimated monthly cost savings (USD). Select all candidates that meet both criteria, up to a maximum of 3.
1. Trim devcontainer — remove features, packages, or extensions not needed for everyday development work; target image <2 GB and fewer than 10 features
2. Right-size machine type — match to observed usage patterns; if data is unavailable, state assumptions explicitly
3. Scope prebuilds — enable for the default branch, `release/*` branches active in the last 14 days, and branches with more than 5 Codespaces per week; disable for all others
4. Tune idle timeout — 30 min default; 15 min if most sessions end before 30 min; 60 min if most sessions run longer
5. Remove unused extensions or port-forwarding rules
6. Reduce devcontainer image size and improve layer caching
4. Verify
- Start a test Codespace to confirm devcontainer changes build and start as expected.
- Validate machine sizing against observed usage when telemetry is available; otherwise mark as unverified.
- Treat unexpected build or startup failures as real bugs even when the configuration looks correct.
Required Output
**Waste sources:** [top cost or startup-time drivers]
**Proposed fixes:** [top 3 changes supported by audit evidence and passing guardrails]
**Validation:** [proven live / static-only / remaining risk]
**Impact:*
🎯 Best For
- Claude users
- GitHub Copilot users
- Knowledge workers
- Remote teams
- Professionals
💡 Use Cases
- Using Github-Codespaces-Efficiency in daily workflow
- Automating repetitive productivity tasks
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Github-Codespaces-Efficiency to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
How do I install Github-Codespaces-Efficiency?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/github-codespaces-efficiency/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Not reading the full skill
Skills contain important context and edge cases beyond the quick start.