import json __all__ = ["OnboardingPrompts"] class OnboardingPrompts: @staticmethod def default_system_prompt(): return ( "You are a helpful onboarding assistant that helps new employees get onboarded to their new company." "You may use relevant tools to assist you to provide the best support." ) @staticmethod def force_reasoning_prompt(): return "Double check your reasoning and provide the final improved answer." @staticmethod def curriculum_generation_prompt(): return ( "Based on available documentation, create an onboarding curriculum for this role. " "Output ONLY a valid JSON array of 3-5 strings representing module titles. " "Example: [\"Introduction\", \"Safety\", \"Operations\"]" ) @staticmethod def knowledge_generation_prompt(topic, context_markdown): return ( f"Write a practical onboarding training guide for the topic '{topic}'. " "Think step-by-step internally before writing the final answer. " "Use the MCP search context below as your primary source, and call additional tools if needed. " "If no indexed documents are available, provide a concise best-practice overview and clearly say no indexed documents were found. " "Use Markdown formatting and do NOT include a table of contents in this section. " "Generate substantial depth: target 900-1400 words. " "Include these sections in order: Overview, Core Concepts, Role-Specific Workflow, Practical Examples, Common Pitfalls, and Action Checklist. " "In Practical Examples, provide at least 2 concrete examples relevant to this role/topic. " "In Action Checklist, provide at least 8 actionable checklist items.\n\n" f"Topic: {topic}\n" f"MCP search context:\n{context_markdown}" ) @staticmethod def quiz_generation_prompt(question_count, module_briefs): return ( "Create a final onboarding quiz that assesses all generated modules. " f"Output ONLY a valid JSON array of exactly {question_count} question objects. " "Use a mix of question types: at least 2 short-answer questions and at least 2 multiple-choice questions. " "For multiple-choice objects: field_type='select', options (4 unique strings), and validation.correct_option. " "For short-answer objects: field_type='textarea' (or 'text') and validation.accepted_answers (array of valid answers/keywords). " "Each object MUST include key, label, field_type, required=true, and validation.explanation. " "Cover all topics with balanced difficulty and avoid ambiguous wording.\n\n" f"Modules JSON:\n{json.dumps(module_briefs, ensure_ascii=False)}" ) @staticmethod def quiz_generation_retry_prompt(question_count, module_briefs): return OnboardingPrompts.quiz_generation_prompt(question_count, module_briefs) + ( "Return ONLY raw JSON. Do not use markdown fences. Do not include explanations outside JSON." ) @staticmethod def progress_monitoring_prompt(progress_context): return ( "You are a progress monitoring agent for onboarding. " "Analyze the role onboarding data below and provide concise feedback with:\n" "1) current status\n2) strengths\n3) gaps\n4) next actions\n" "Use prior learner question/answer evidence and any saved marking details when available. " "If evidence is insufficient, explicitly state what is missing.\n" "Keep it short and practical.\n\n" f"Progress context JSON:\n{json.dumps(progress_context)}" )