Bench for Claude Code is a specialized tool for developers using Claude Code. It automatically records, stores, and allows you to review your entire Claude Code interaction sessions. It provides detailed insights into tool calls, subagent activity, web searches, and highlights potential issues, making code review and collaboration more transparent and efficient.
Free
How to use Bench for Claude Code?
Install the provided Git hook globally via the command line. Once configured, simply use Claude Code as normal. All your sessions, including every action, decision, and tool call, are automatically sent to Bench. You can then review the detailed traces in the 'Last Sessions' view, inspect step-by-step logic, jump to failure points, and share complete session traces with teammates or link them in Pull Requests for better context.
Bench for Claude Code 's Core Features
Automatically captures and stores complete Claude Code sessions, including all prompts, code generations, and agent interactions.
Provides an Activity Recap that lists every tool call, subagent invocation, and web search performed during a session for full transparency.
Enables Step-by-Step Inspection to examine each action, understand the agent's decision-making process, and see element selections and outcomes.
Features Auto Highlights to automatically flag and draw attention to potentially dangerous or risky actions taken by the AI agent.
Allows easy sharing of complete session traces with others, perfect for embedding context in code reviews, PRs, or team discussions.
Offers a simple setup via command-line Git hook installation, requiring minimal configuration to start capturing sessions immediately.
Bench for Claude Code 's Use Cases
Developers can review complex Claude Code sessions to understand why the AI generated specific code, debugging logic and unexpected outputs.
Engineering teams share full AI coding session context in PRs, eliminating guesswork about how a feature was built or refactored.
Tech leads audit AI-assisted development workflows, ensuring code quality and identifying patterns in AI agent behavior and potential risks.
Solo developers or learners track their coding journey with Claude, revisiting sessions to learn from the AI's problem-solving approaches.
Open-source contributors provide transparent development logs when submitting AI-generated code, building trust and clarity in collaborative projects.