autoreport-cli

Manage argparse-based CLI parsing and standardized exit codes for autoreport.

Updated Mar 15, 2026
One-click install
npx skills add https://github.com/tubtrb/autoreport --skill autoreport-cli
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: autoreport-cli
Source: https://github.com/tubtrb/autoreport/tree/main/codex/skills/autoreport-cli
Command: npx skills add https://github.com/tubtrb/autoreport --skill autoreport-cli

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This CLI handles argument parsing, standardized success messaging, and exit code semantics for the autoreport package, ensuring a consistent user experience.

Core Features & Use Cases

  • Argument parsing and validation for the autoreport CLI entrypoint (cli.py) and related components.
  • Uniform success and error messaging that aligns with tests and user expectations.
  • Clear exit-code semantics and documentation for integration in automation pipelines.

Quick Start

Run the autoreport CLI with the generate subcommand to observe standard behavior and outputs.

Frequently Asked Questions about autoreport-cli

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I parse command-line arguments for generating PPTX decks in Python?

Argument parsing for PPTX generation is managed through an argparse-based CLI layer that validates inputs and delegates to generation logic, ensuring deterministic behavior. The CLI handles subcommands like generate to produce decks predictably.

What exit codes should a command-line tool use for validation failures versus generation errors?

Command-line tools like this one map failures to specific exit codes: code 1 for general failures and code 2 for validation errors. This clear exit-code semantics ensures reliable integration in automation pipelines by distinguishing failure types.

How do I standardize user-facing messaging and success output in a CLI application?

Standardized user-facing messaging is implemented by centralizing output logic in the CLI layer, which preserves existing success and error messages while delegating core tasks to generation and validation logic. This ensures a consistent user experience across all subcommands.

Can I use a thin CLI layer to scaffold payloads and validate templates for report generation?

Yes, a thin CLI layer can scaffold payloads and validate templates by delegating argument parsing to argparse and routing to specific subcommands. This architecture keeps the CLI predictable while the underlying logic handles the actual payload scaffolding and template validation.

Why does my autoreport CLI behave unpredictably when integrated into automation pipelines?

Unpredictable CLI behavior in automation often stems from unclear exit-code semantics or inconsistent messaging. This CLI addresses that by applying deterministic exit codes (1 and 2) and standardized output, ensuring reliable pipeline integration and predictable failures.