Valid Route Hybrid Agent

ValidRoute Hybrid Agent is a Track 1 general-purpose AI system built for the AMD Hackathon ACT II evaluation environment. It solves factual reasoning, mathematics, sentiment classification, summarization, named-entity recognition, logic, code debugging, and code generation while balancing two goals: strong accuracy on randomized hidden prompts and efficient Fireworks token usage. The core design is validator-gated hybrid routing. Instead of sending every prompt to the same model, the agent first classifies the task, estimates risk, and attempts deterministic or local solving only when the answer is safe. Each candidate answer is then checked by category-specific validation logic for structure, completeness, and instruction compliance. If the answer is ambiguous, incomplete, brittle, or likely wrong, the task escalates through the Fireworks pathway using only models from ALLOWED_MODELS and FIREWORKS_BASE_URL. This architecture is designed for final judging on refreshed randomized prompts rather than benchmark memorization. It preserves output requirements, handles multi-part answers carefully, and avoids trusting local answers when confidence is weak. Hard categories such as logic, constrained summarization, explanation-heavy factual prompts, code tasks, and named-entity recognition are handled conservatively because output shape alone does not prove correctness. The hosted inference path was also optimized for reliability and token discipline. Reasoning-heavy generation was disabled when it increased token cost and truncation risk without improving answer quality. In our strongest frozen unseen randomized evaluation, the system achieved 86.36% accuracy (38/44) using 7,861 Fireworks tokens across 44 tasks, about 179 tokens per task or roughly 3.4K tokens projected to a 19-task run. The submission container was validated on linux/amd64, completes within the time limit, writes the required /output/results.json contract, and guarantees non-blank answers.