Review Cycle

The review-cycle skill manages iterative feedback loops within AI agent workflows, ensuring code or output quality through structured review stages. It facilitates continuous improvement by systematically evaluating results against defined criteria before proceeding to the next phase of execution.

When to use it

• Implementing a multi-stage development process where each step requires validation before moving forward.
• Ensuring consistent code quality in automated pipelines by integrating human or AI checkpoints.
• Debugging complex tasks that benefit from incremental refinement rather than single-pass generation.
• Orchestrating workflows where intermediate outputs must be verified to prevent error propagation.

Key capabilities

• Executes defined review stages within a workflow sequence.
• Validates outputs against specific criteria or standards.
• Triggers subsequent actions only upon successful review completion.
• Maintains context across multiple iterations of the same task.

Example prompts

• "Run the review-cycle skill to validate my Python script before deploying it to production."
• "Initiate a three-stage review process for this design document, checking clarity, logic, and formatting."
• "Use the review-cycle skill to iteratively refine this SQL query until it meets performance benchmarks."

Tips & gotchas

Ensure your workflow defines clear success criteria for each review stage to avoid ambiguous feedback loops. This skill is most effective when paired with specific validation rules rather than relying solely on general quality checks.