review-feedback-schema

What it does

This skill enables AI agents to generate structured feedback schemas for reviewing specific outputs or processes. It defines clear evaluation criteria and formats results consistently, ensuring that reviews are actionable and standardized across different tasks.

When to use it

• Automated Code Reviews: Create a checklist for an agent to evaluate pull requests against style guides and security standards.
• Content Quality Assurance: Define specific metrics (e.g., tone, clarity, fact-checking) for reviewing blog posts or marketing copy before publication.
• Project Status Updates: Structure feedback on sprint reports to ensure all team members address blockers and completed tasks uniformly.
• Data Validation: Establish a schema for agents to verify the accuracy and completeness of generated datasets or API responses.

Key capabilities

• Generates predefined evaluation rubrics tailored to specific domains.
• Structures unstructured review notes into consistent, machine-readable formats.
• Enforces standardized output patterns for feedback loops.
• Facilitates clear communication between AI agents and human reviewers.

Example prompts

• "Create a review-feedback-schema for evaluating Python code against PEP 8 standards."
• "Generate a schema to assess the clarity and persuasiveness of a sales email draft."
• "Define a feedback structure for an agent to critique a weekly project status report."

Tips & gotchas

Ensure you provide sufficient context about the specific domain or output type when requesting a schema, as generic templates may lack necessary detail. This skill is most effective when paired with other evaluation or analysis skills to execute the actual review process.