Code Generation Agent Swarm — Parallel Test & Code Generation

I will build a code generation agent swarm — simultaneously generating multiple implementation variants for a specification, testing each variant against a test suite, and selecting the best-performing implementation — applying evolutionary selection pressure to code generation that a single sequential attempt cannot achieve. Code generation via agent swarm with test-based selection consistently produces higher-quality implementations than single-attempt generation because the swarm explores a wider solution space, and test-based selection filters out syntactically correct but logically flawed implementations that manual review might miss.

The swarm covers specification parsing, parallel implementation generation with configurable variant count, automated test suite execution per variant, quality scoring (test pass rate, code quality metrics), variant selection, and delivery of the highest-scoring implementation.