v0.1.2 - Cover refresh and first-use documentation

AI Product Teardown Studio v0.1.2

A polish-and-clarity release focused on first impressions, first-use onboarding, and easier interpretation of what the project actually does.

Highlights

• Clearer repository cover graphic for GitHub visitors
• Better first-use guidance for prompts, outputs, and interpretation boundaries
• Stronger onboarding path from README into the most useful reference files

Added

• references/example-prompts.md with stronger prompt starting points
• references/sample-teardown-output.md showing what a useful teardown should contain
• references/faq-troubleshooting.md answering common first-use questions and interpretation pitfalls

Improved

• Refreshed the repository cover graphic so the project identity and workflow are clearer on GitHub
• Expanded the README with example use cases, stronger output expectations, and a clearer reading path
• Made the repo easier to understand at a glance for new users landing from GitHub

Fixed

• Reduced ambiguity in the project presentation by replacing a more abstract cover concept with a more explicit one
• Reduced first-use friction by making example prompts and output expectations easier to find

Who this helps

• Skill creators trying to study reusable repo patterns without copying expression
• AI product builders who want clearer teardown outputs and onboarding examples
• GitHub project learners who need a faster path from landing page to method

Recommended next step

• Read README.md
• Skim references/example-prompts.md
• Skim references/sample-teardown-output.md
• Run the scripts on one real repository and compare the result with the sample teardown structure

v0.1.1 - Contributor guide and maintenance polish

AI Product Teardown Studio v0.1.1

Small maintenance release focused on contributor clarity and healthier public project upkeep.

Added

• CONTRIBUTING.md with contribution scope, privacy reminders, bug report expectations, and pull request guidance
• A lightweight release rhythm covering patch vs. minor updates

Improved

• README now includes a clearer contributing path for new collaborators
• Public repository maintenance is easier to understand for future users and contributors

Why this release matters

This update makes the project easier to extend without diluting its original purpose: structured AI repository teardown, AI surface analysis, reusable pattern extraction, and originality-safe skill drafting.

v0.1.0 - Initial public release

AI Product Teardown Studio v0.1.0

Initial public release of ai-product-teardown-studio.

Highlights

• Repository classification across skill repos, AI apps, workflow repos, embedded-skill repos, and portfolio/showcase projects
• AI surface audit for CLAUDE.md, AGENTS.md, .claude/skills/, SKILL.md, MCP signals, modes, and runtime AI layers
• Reusable pattern extraction designed to avoid copying source wording or repo-specific expression
• Originality-safe skill drafting workflow for turning repo observations into a stronger new project concept
• Lightweight local Python scripts for repo inventory, signal scanning, and teardown report generation

Included in this release

• Public-safe README.md, SKILL.md, and agents/openai.yaml
• references/ teardown framework documents
• scripts/repo_inventory.py
• scripts/feature_signal_scan.py
• scripts/teardown_report_builder.py
• MIT LICENSE, .gitignore, and repository cover asset

Notes

This project is intended for local analysis and learning. It helps users study repository structure, AI integration patterns, and originality-safe reuse strategies without republishing someone else's wording as their own.