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Install script generator

Skill Montimage/skills/skills/install-script-generator

Generate cross-platform installation scripts for any software, library, or module. Use when users ask to "create an installer", "generate installation script", "automate installation", "setup script for X", "install X on any OS", "write an install script", "deployment script", or need automated deployment across Windows, Linux, and macOS. Follows a three-phase approach with environment detection, installation planning with verification/rollback, and documentation generation. Trigger this skill whenever the user wants to automate installing or deploying software, even if they just say "how do I install X everywhere".From its SKILL.md

Install
npx -y skills add Montimage/skills --skill install-script-generator

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 9 stars9 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
  • runs commandsInstructs the agent to run 6 commands, including `git fetch origin` and 5 more.

SKILL.md

6.0 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it

Install Script Generator

Generate robust, cross-platform installation scripts with automatic environment detection, verification, and documentation.

Repo Sync Before Edits (mandatory)

Before generating any output files, sync with the remote to avoid conflicts:

branch="$(git rev-parse --abbrev-ref HEAD)"
git fetch origin
git pull --rebase origin "$branch"

If the working tree is dirty, stash first, sync, then pop. If origin is missing or conflicts occur, stop and ask the user before continuing.

Workflow

Phase 1: Environment Exploration

Gather comprehensive system information:

# Run the environment explorer script
python3 {SKILL_DIR}/scripts/env_explorer.py

Use sub-agents for parallel discovery. Launch multiple Agent tool calls concurrently to keep the main context clean:

  • Agent 1 — System detection: Run env_explorer.py and parse the JSON output. Detect OS, version, CPU architecture, and user permissions (admin/sudo availability). Return a structured summary.
  • Agent 2 — Package manager inventory: Identify all available package managers (apt, yum, brew, choco, winget) and their versions. Check shell environment (bash, zsh, powershell, cmd). Return a capability list.
  • Agent 3 — Existing dependencies: Scan for already-installed dependencies and their versions relevant to the target software. Return a dependency status report.

Collect the results from all three agents before proceeding.

The script detects:

  • Operating system (Windows/Linux/macOS) and version
  • CPU architecture (x86_64, ARM64, etc.)
  • Package managers available (apt, yum, brew, choco, winget)
  • Shell environment (bash, zsh, powershell, cmd)
  • Existing dependencies and versions
  • User permissions (admin/sudo availability)

Output: JSON summary of system capabilities and constraints.

Phase 2: Installation Planning

Based on the environment analysis and target software:

  1. Identify dependencies - List all required packages/libraries
  2. Check existing installations - Avoid reinstalling what exists
  3. Order operations - Resolve dependency graph
  4. Add verification steps - Each step must be verifiable
  5. Plan rollback - Define cleanup on failure

Create the plan using:

python3 {SKILL_DIR}/scripts/plan_generator.py --target "<software_name>" --env-file env_info.json

Plan structure:

target: "<software_name>"
platform: "detected_os"
steps:
  - name: "Install dependency X"
    command: "..."
    verify: "command to verify success"
    rollback: "cleanup command if failed"
  - name: "Configure system"
    command: "..."
    verify: "..."

Phase 3: Execution

Execute the plan with real-time verification:

python3 {SKILL_DIR}/scripts/executor.py --plan installation_plan.yaml

Execution behavior:

  • Run each step sequentially
  • Verify success after each step
  • On failure: execute rollback, report error, stop
  • Log all output for debugging
  • Generate installation report

Phase 4: Documentation Generation

After successful installation, generate usage documentation:

python3 {SKILL_DIR}/scripts/doc_generator.py --target "<software_name>" --plan installation_plan.yaml

Use sub-agents for parallel documentation. The documentation sections are independent of each other. Dispatch them concurrently using the Agent tool, then collect results:

  • Agent A — Installation report: Generate install_report.md with the execution log, step-by-step status, and any warnings or errors encountered during installation.
  • Agent B — Usage guide: Generate USAGE_GUIDE.md with a quick start guide, common commands/usage examples, and troubleshooting tips based on the installed software.
  • Agent C — Uninstall & maintenance: Generate the uninstallation instructions and maintenance notes (upgrade paths, configuration locations, log file paths).

Each agent should return the path(s) of files it created or updated.

Output includes:

  • Installation summary (what was installed, where)
  • Quick start guide
  • Common commands/usage examples
  • Troubleshooting tips
  • Uninstallation instructions

Output Files

The skill generates these files in the current directory:

FileDescription
env_info.jsonSystem environment analysis
installation_plan.yamlDetailed installation steps
install_report.mdExecution log and status
USAGE_GUIDE.mdUser documentation

Platform-Specific Notes

Windows

  • Prefer winget over choco when available
  • Use PowerShell for script execution
  • Handle UAC elevation requirements

Linux

  • Detect distro family (Debian/RedHat/Arch)
  • Use appropriate package manager
  • Handle sudo requirements gracefully

macOS

  • Use Homebrew as primary package manager
  • Handle Apple Silicon vs Intel differences
  • Respect Gatekeeper and notarization

Example Usage

User request: "Create an installation script for Node.js"

  1. Run env_explorer.py to detect system
  2. Generate plan with Node.js as target
  3. Execute plan (installs Node.js + npm)
  4. Generate USAGE_GUIDE.md with npm commands

Error Handling

  • All scripts exit with non-zero codes on failure
  • Verification failures trigger rollback
  • Detailed error messages include remediation hints
  • Partial installations are cleaned up automatically

What ships with it: 5 files

40.2 KB alongside SKILL.md, 4 of them executable

scripts/

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