Closing the Loop: Enhancing Agentic Workflows with Crit
As AI agents transition from simple chat interfaces to autonomous coding tools, a new bottleneck has emerged: the review process. While agents can generate complex plans and massive diffs in seconds, the cognitive load required for a human to verify that work remains high. Reviewing plausible-looking code faster than a human can read it often leads to errors or a tedious cycle of manual corrections.
Crit is designed to solve this specific friction point. By providing a dedicated, local-first review tool for agent plans and code diffs, it transforms the interaction with AI agents from a linear conversation into a structured, iterative review loop.
The Core Challenge: Reviewing at AI Speed
For many developers using tools like Claude Code or Cursor, the primary struggle isn't the agent's ability to write code, but the developer's ability to review it. When an agent proposes a multi-file change or a complex implementation plan, the traditional methods of feedback—such as typing "on point 3, change X to Y" in a chat window—are imprecise and cumbersome.
Crit addresses this by treating the agent's output as a pull request before it ever hits a version control system. It allows developers to highlight specific lines of a plan or a diff, leave precise inline comments, and then signal the agent to act on that feedback automatically.
Key Features of the Crit Workflow
Local-First and Privacy-Centric
Crit is distributed as a single binary and operates locally by default. Reviews stay on the user's machine, and sharing is an opt-in feature. This is critical for professional environments where code privacy and security are paramount. For those who need collaboration, Crit offers a one-click public link generation or the ability to self-host the sharing target.
A Unified Review Interface
One of the most significant advantages of Crit is its consistency. Whether you are reviewing a high-level markdown plan or a technical code diff, the UI remains the same. This eliminates the need to switch tools mid-feature, providing a seamless transition from planning to implementation.
Iterative, Multi-Round Feedback
Crit supports multi-round and concurrent reviews. Developers can iterate over several rounds of feedback per file, and because the tool supports round-over-round diffs, users can track exactly how the agent's output has evolved based on their specific comments. This prevents the loss of context that often occurs in long chat histories.
Real-World Impact on Developer Experience
Feedback from early adopters highlights how Crit fills a critical gap in current AI coding harnesses. Users have noted several key improvements to their daily workflows:
- Precision in Planning: Instead of fumbling with line numbers in a terminal, developers can use a clean UI to batch feedback on complex plans.
- Reduced Tool Overhead: Some users have avoided setting up complex local Git servers (like Gitea) just to have a place to review iterative AI changes before pushing to a main branch.
- Integration with CLI Agents: For those using agents in the command line without a full IDE, Crit provides the necessary rendering and interaction layer to make agentic work feel controlled rather than chaotic.
"It's like a pull request review but for your plan. On long, complex plans I used to ask Claude things like 'on point 3., we should do X, drop point 7., ...'. Using comments makes it more straightforward and easy to review later."
Technical Specifications and "Small Wins"
Beyond the core loop, Crit includes a suite of features designed for power users:
- Developer-Centric Controls: Vim keybindings and support for both split and unified Git diffs.
- Broad Compatibility: Syntax highlighting for over 190 languages and support for Mermaid diagrams.
- Curation Tools: A table of contents for long documents and draft autosave to prevent data loss during review sessions.
By focusing on the "review