Install script generator
A curated collection of Agent Skills by Montimage. Supercharge your AI agents with specialized workflows for development tasks. Works with Claude Code, Codex, OpenClaw, and other AI tools.
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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".
SKILL.md
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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.pyand 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:
- Identify dependencies - List all required packages/libraries
- Check existing installations - Avoid reinstalling what exists
- Order operations - Resolve dependency graph
- Add verification steps - Each step must be verifiable
- 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.mdwith the execution log, step-by-step status, and any warnings or errors encountered during installation. - Agent B — Usage guide: Generate
USAGE_GUIDE.mdwith 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:
| File | Description |
|---|---|
env_info.json | System environment analysis |
installation_plan.yaml | Detailed installation steps |
install_report.md | Execution log and status |
USAGE_GUIDE.md | User documentation |
Platform-Specific Notes
Windows
- Prefer
wingetoverchocowhen 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"
- Run env_explorer.py to detect system
- Generate plan with Node.js as target
- Execute plan (installs Node.js + npm)
- 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