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one-line-installer-patterns Skill

AI Agent SkillPythonOpen source

Use when designing a curl-piped install script for a project that cannot use uv tool install or npm publish — multi-service stacks (Docker Compose), raw TS/React apps, tools that bootstrap system dependencies, or installs for non-technical audiences. Documents the security trade-off, the community convention used by ru Published by microsoft in amplifier-bundle-skills.

What is one-line-installer-patterns Skill?

Use when designing a curl-piped install script for a project that cannot use uv tool install or npm publish — multi-service stacks (Docker Compose), raw TS/React apps, tools that bootstrap system dependencies, or installs for non-technical audiences. Documents the security trade-off, the community convention used by ru Published by microsoft in amplifier-bundle-skills. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
26/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Security review
  • Deployment
  • Security review use cases
  • Deployment use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use one-line-installer-patterns Skill

  • Use it for security review.
  • Use it for deployment.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: microsoft
  • Repository: microsoft/amplifier-bundle-skills
  • Skill file: skills/one-line-installer-patterns/SKILL.md

What it does

Use when designing a curl-piped install script for a project that cannot use uv tool install or npm publish — multi-service stacks (Docker Compose), raw TS/React apps, tools that bootstrap system dependencies, or installs for non-technical audiences. Documents the security trade-off, the community convention used by ru

Skill instructions

One-Line Installer Patterns When this pattern is the right tool A curl … | bash install script is the right answer in a narrow set of cases. Outside that set, simpler distribution mechanisms exist and should be used. Use this pattern when: - The project is multi-language (Python + Node + Docker) and uv tool install cannot do the job alone - The project requires system prerequisites that must be detected and clearly directed (Docker, Node via fnm/volta, jq, etc.) - The intended audience is non-technical and cannot be expected to run more than one command - The "real" install is docker compose up, but the user needs a clean way to land the compose file, generate an .env, and start the stack Don't use this pattern when: - The project is a Python CLI → use uv tool install git+... and see cli-packaging-patterns - The project is a Node CLI → publish to npm, document npx <tool or pnpm dlx <tool - The project produces a single static binary → ship via GitHub releases, document curl -L .../tool

Explore related resources

Frequently asked questions

What is one-line-installer-patterns?

one-line-installer-patterns is a open-source AI agent skill with Copy skill directory. Use when designing a curl-piped install script for a project that cannot use uv tool install or npm publish — multi-service stacks (Docker Compose), raw TS/React apps, tools that bootstrap.

Who is one-line-installer-patterns best for?

one-line-installer-patterns is best for reusing agent instructions, scripts, and references, security review workflows, deployment workflows.

How do I install one-line-installer-patterns?

Install or run one-line-installer-patterns using Copy skill directory. Check one-line-installer-patterns for the latest setup command.

Is one-line-installer-patterns actively maintained?

one-line-installer-patterns may need a closer maintenance check before production use.

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Stars
10
Forks
9
Last commit
9 days ago
Repository age
5 months
License
MIT

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