AI Briefingbuttonmasher: AI Agent Skill Simulating Impatient Users to Find Duplicate Action and Race Condition Bugs
Key point
The open-source skill simulates impatient user behaviors like double-clicking and retrying to find duplicate charges and state errors, supporting Claude Code, Codex, and Copilot CLI.
Details
Overview
buttonmasher is an open-source AI agent skill designed to identify bugs caused by realistic user impatience, such as duplicate payments, double submissions, and race conditions. Unlike traditional code review or fuzzing, it simulates the behavior of a user who clicks Submit twice, retries after a timeout, or opens multiple tabs. The tool identifies issues where actions that should happen exactly once occur multiple times, or where completed actions are re-executed.
How It Works
The skill analyzes code paths to find state-changing operations and then applies specific scenarios like double-clicks, timeouts, and back-navigation. It categorizes findings by severity (BROKE, FRAGILE, ANNOYING, BORING) and indicates whether the bug was reproduced by running code or traced by reading the path. If a simple fix is identified, it applies the change and retests.
This summary was generated automatically by AI. Check the original for the author's claims and context. Copyright belongs to the original author.
Our guide explains how the AI works. Report summary errors, attribution issues, or removal requests via Contact.
Related
Porch: Open-Source Mac Menu Bar App for Summarizing Claude Code and Codex Sessions
Berthd Releases Open-Source macOS Client for Persistent Remote Coding AgentsAgent Guard: Local Security Tool Prevents Secret Leaks in Claude Code and CodexAgent Standup: Open-source tool visualizes Claude Code sub-agents as a live team meeting