Fetch pair-review comments and apply code changes in local or PR contexts.
npx skills add https://github.com/in-the-loop-labs/pair-review --skill user-critic
Please help me install this Agent Skill. Skill: user-critic Source: https://github.com/in-the-loop-labs/pair-review/tree/main/plugin/skills/user-critic Command: npx skills add https://github.com/in-the-loop-labs/pair-review --skill user-critic
This Skill streamlines the process of incorporating human feedback into code, ensuring that AI-generated code aligns with reviewer expectations and project standards.
pair-review to leave comments. The developer then uses this Skill to automatically address all those comments, iterating on the code until it meets the required standards.Use the user-critic skill to fix review comments in the current branch.
High-intent search queries and answers about installing and using this skill.
To address AI review feedback automatically, this Skill fetches human review comments from pair-review and applies code changes to resolve them. It parses the comments to understand required modifications and updates the code files accordingly.
You can apply human code review comments to a local branch by using the local path and head SHA context. The Skill differentiates between local and PR reviews to fetch and apply feedback accurately to your codebase.
Yes, you can use pair-review feedback to fix code changes in a pull request. The Skill determines repository and PR details automatically to fetch comments and apply the required modifications directly to the PR context.
The best way to integrate human reviewer expectations into AI-generated code is to fetch pair-review comments and automatically apply code changes. This streamlines iterating on the code until it meets project standards.
Yes, this code review automation tool works without external dependencies. It operates standalone to fetch review comments, parse required modifications, and report on the changes made to your code files.
You should use automated feedback integration for code review changes to streamline incorporating human feedback into code. This ensures AI-generated code aligns with reviewer expectations and project standards without manual updates.
nanomaderPoll head-scoped Codex review findings for the current PR head.
phraReview modified code files and auto-fix mechanical issues.
in-the-loop-labsFetches and applies AI-generated code review suggestions from pair-review.
luigiinredProcess GitHub Pull Request comments with subagent validation and proposed fixes.