prompt-engineer

Structured prompts use task contracts to separate inputs, outputs, and refusal rules. This skill provides reusable templates and guidelines to define these contracts, ensuring your LLM instructions remain clear, reliable, and reproducible across different agents.

Evaluating prompt performance requires end-to-end workflows with evaluation loops and rubrics. This skill includes reference materials to test prompts against specific criteria, enabling you to measure and refine instruction effectiveness in production environments.

Repeatable prompt engineering is achieved by using structured kits containing templates, examples, and guidelines. This skill provides reusable kits that standardize the design process, allowing teams to produce consistent prompts across various AI workflows.

Yes, the structured task contracts explicitly include refusal rules alongside inputs and outputs. These templates ensure your agents understand boundaries and handle refusals correctly within the defined prompt workflow.

No external framework is required. This skill provides self-contained scripts and reference materials to implement evaluation loops and rubrics directly within your existing AI assistant or agent development environment.

Inconsistent outputs often result from missing task contracts and lack of structured evaluation. By applying structured templates, examples, and evaluation rubrics, this skill standardizes inputs and outputs to significantly reduce output variability.