GenLayer adds Intelligent Contracts to GenVM

GenLayer’s genvm-linter enforces safety and SDK conformance with commands like genvm-lint check / lint / validate and can extract an ABI with genvm-lint schema --output abi.json, with the linter’s fast AST pass reported at ~50ms and full SDK validation at ~200ms (GitHub). (github.com) The protocol’s Equivalence Principle requires contract authors to declare equivalence criteria and exposes SDK helpers such as gl.eq_principle.prompt_comparative(), prompt_non_comparative(), and strict_eq() so validators can judge non‑deterministic outputs against application-defined norms (GenLayer docs). (docs.genlayer.com) A pytest-based in-memory testing package published as genlayer-test (version 0.25.0, released Mar 11, 2026) provides two execution modes for local contract validation, enabling unit-style checks of nondeterministic flows before any network deployment (PyPI). (pypi.org) The GenLayer CLI (documented at versioned docs and a 0.34.0 reference) supports quick deployments via genlayer deploy --contract <path> --args... and also supports deploy scripts for multi-contract or CI-friendly workflows, with explicit RPC targeting for localnet, studionet, and testnets such as Bradbury (CLI docs). (docs.genlayer.com) Operational observability is surfaced through genlayer trace, which returns execution traces including return data, stdout/stderr and GenVM logs, and the CLI also offers commands like genlayer receipt and genlayer appeal to inspect transactions and appeal bonds for disputed outcomes (CLI reference). (github.com) Developer tooling includes a VS Code extension that integrates the linter, a GenLayer Studio web IDE, and a CLI 'init' + 'up' simulator workflow to reproduce validator/leader conditions locally, enabling faster DevX loops and reproducible failure-mode debugging (VS Code marketplace and docs). (marketplace.visualstudio.com) GenVM itself is a WASM-backed Python execution environment that supports both deterministic and non-deterministic execution modes and exposes runner traces and logs for post‑mortem analysis, which the GenLayer tooling set ties into linting, testing, and the CLI deploy/trace pipeline (GenVM spec and repo). (github.com) All of the above tooling supports machine-readable outputs (genvm-lint --json, schema ABI JSON, CLI JSON flags) intended for CI gating and automated safety checks, and the documentation explicitly recommends a workflow: local CLI iteration → studionet collaboration → testnetBradbury validation for real AI workloads (linter docs and deployment guides). (pypi.org)