Create prompts.jsonl

prompts.jsonl

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+{"id":"YL001","category":"agent_planning","prompt":"Break down how you would build a simple agent that can search notes, summarize, and draft a reply. List components and data flow.","expected_traits":"structured steps, practical components, clear data flow"}
+{"id":"YL002","category":"agent_tools","prompt":"Design a tool calling interface for an agent that uses three tools: search, calculator, and http fetch. Provide a minimal schema and call examples.","expected_traits":"clear schema, safe defaults, realistic examples"}
+{"id":"YL003","category":"reproducibility","prompt":"Given an experiment prompt, show how you would log parameters, model id, and outputs for reproducible runs. Keep it simple.","expected_traits":"logging mindset, minimal but complete fields"}
+{"id":"YL004","category":"efficiency","prompt":"Explain how you would reduce GPU memory use for local inference on a consumer GPU. Include quantization and batching tradeoffs.","expected_traits":"accurate tradeoffs, practical suggestions"}
+{"id":"YL005","category":"latency","prompt":"You have a slow local model. List the top causes of latency and the first measurements you would take.","expected_traits":"diagnostic approach, measurable steps"}
+{"id":"YL006","category":"rag_design","prompt":"Design a minimal RAG pipeline for personal notes. Include chunking, embeddings, retrieval, and a basic evaluation plan.","expected_traits":"end to end design, evaluation included"}
+{"id":"YL007","category":"rag_grounding","prompt":"What are reliable ways to reduce hallucinations in a RAG system? Include what to measure.","expected_traits":"grounding methods, metrics, failure modes"}
+{"id":"YL008","category":"prompt_quality","prompt":"Rewrite this vague prompt into three testable prompts for an engineering assistant. Explain why each is better.","expected_traits":"prompt clarity, testability, rationale"}
+{"id":"YL009","category":"safety_policy","prompt":"An agent can run shell commands. Describe guardrails you would implement to prevent destructive actions.","expected_traits":"practical guardrails, least privilege mindset"}
+{"id":"YL010","category":"system_design","prompt":"Propose an architecture for running local inference plus optional cloud fallback. Focus on reliability and cost control.","expected_traits":"clear architecture, failure handling, cost awareness"}
+{"id":"YL011","category":"evaluation","prompt":"Create a lightweight rubric to score agent responses on correctness, actionability, and uncertainty handling.","expected_traits":"rubric with criteria and scoring"}
+{"id":"YL012","category":"uncertainty","prompt":"Answer a question where you are not sure. Demonstrate how you state uncertainty and what you would verify next.","expected_traits":"explicit uncertainty, verification steps"}
+{"id":"YL013","category":"debugging","prompt":"A model output quality regressed after a prompt change. Outline a debugging approach to isolate the cause.","expected_traits":"A B testing, controlled variables, clear steps"}
+{"id":"YL014","category":"documentation","prompt":"Write a short model card section describing intended use, limitations, and ethical considerations for a home lab agent.","expected_traits":"honest limitations, clear intended use"}
+{"id":"YL015","category":"workflow","prompt":"Design a daily workflow for home lab research that balances building, measuring, and documenting results.","expected_traits":"repeatable workflow, measurement emphasis"}