Agent Generator Tutor Skill
Interactive teaching agent for the goal-seeking agent generator and eval system.
What This Skill Does
Loads the GeneratorTeacher from src/amplihack/agents/teaching/generator_teacher.py
and guides users through a structured 14-lesson curriculum with exercises and quizzes.
Curriculum (14 Lessons)
Lesson Title Topics
L01 Introduction to Goal-Seeking Agents Architecture, GoalSeekingAgent interface
L02 Your First Agent (CLI Basics) Prompt files, CLI invocation, pipeline
L03 SDK Selection Guide Copilot, Claude, Microsoft, Mini SDKs
L04 Multi-Agent Architecture Coordinators, sub-agents, shared memory
L05 Agent Spawning Dynamic sub-agent creation at runtime
L06 Running Evaluations Progressive test suite, SDK eval loop
L07 Understanding Eval Levels L1-L12 Core (L1-L6) and advanced (L7-L12) levels
L08 Self-Improvement Loop EVAL-ANALYZE-RESEARCH-IMPROVE-RE-EVAL-DECIDE
L09 Security Domain Agents Domain-specific agents and eval
L10 Custom Eval Levels TestLevel, TestArticle, TestQuestion
L11 Retrieval Architecture Simple, entity, concept, tiered strategies
L12 Intent Classification and Math Code Gen Nine intent types, safe arithmetic
L13 Patch Proposer and Reviewer Voting Automated code patches, 3-perspective review
L14 Memory Export/Import Snapshots, cross-session persistence
How to Use
Start the Tutorial
from amplihack.agents.teaching.generator_teacher import GeneratorTeacher
teacher = GeneratorTeacher()
See what lesson is next
next_lesson = teacher.get_next_lesson() print(f"Start with: {next_lesson.title}")
Teach a Lesson
content = teacher.teach_lesson("L01") print(content) # Full lesson with exercises and quiz questions
Check an Exercise
feedback = teacher.check_exercise("L01", "E01-01", "your answer here") print(feedback) # PASS or NOT YET with hints
Run a Quiz
Self-grading mode (see correct answers)
result = teacher.run_quiz("L01")
Provide answers for grading
result = teacher.run_quiz("L01", answers=["PromptAnalyzer", "Explains stored knowledge", "False"]) print(f"Score: {result.quiz_score:.0%}, Passed: {result.passed}")
Check Progress
report = teacher.get_progress_report() print(report) # Shows completed/locked/available lessons
Validate Curriculum Integrity
validation = teacher.validate_tutorial() print(f"Valid: {validation['valid']}, Issues: {validation['issues']}")
Prerequisites
Each lesson has prerequisites that must be completed first. The curriculum follows a dependency graph ensuring foundational concepts are learned before advanced topics.
Exercise Validators
The teaching agent includes 15 specialized validators that check user answers for correctness. Exercises without explicit validators use a fallback that checks for key phrases from the expected output.