Samples · learn by running

Samples

Start small, then add semantic complexity. The samples are teaching applications; benchmark fixtures remain separate experimental artifacts.

The learning path

Sample Purpose Start with
Foundgine.SupplyChain (.NET) Minimal realistic application: application boundary, semantics, authorization, MCP and PostgreSQL. Starter tutorial
Foundgine.SupplyChain.Advanced (.NET) Full semantic proving ground: grounding, retrieval, richer authorization, high-assurance mutation and agent-facing execution. Tutorial index
foundgine-supply-chain (Java) Domain, semantic annotations and authorization shape — the smallest path to a compiling Foundgine Java application. Starter tutorial
foundgine-supply-chain-advanced (Java) Claims/authorization, high-assurance mutation, MCP transport and PostgreSQL, and adversarial security scenarios. Tutorial
Supply Chain PenTest (.NET) Deterministic security regression across MCP and GraphQL. PenTest page

Why separate samples?

The starter teaches the basic application shape without requiring the reader to absorb every semantic feature at once. The advanced sample then adds ambiguity, retrieval, authorization depth and adversarial behavior. Benchmark-only fixtures stay under benchmarks/ so experimental evidence does not become confused with reference architecture.

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