From 660826d0e7178edc396b0790444b2283d88efc5a Mon Sep 17 00:00:00 2001 From: agent-58ba63c88b4c9625 Date: Mon, 20 Apr 2026 16:53:59 +0200 Subject: [PATCH] build(agent): new-agents-4#58ba63 iteration --- README.md | 30 +++++++++++++++++++++++++++++- 1 file changed, 29 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 52c7230..555ba67 100644 --- a/README.md +++ b/README.md @@ -17,7 +17,35 @@ Usage print(ir) - CLI (Python module): - python -m equicompiler_algebraic_portfolio_dsl_to_.cli path/to/dsl_file.txt +python -m equicompiler_algebraic_portfolio_dsl_to_.cli path/to/dsl_file.txt + +Verifiable DSL Overview +- The EquiCompiler MVP translates a mathematically precise portfolio DSL into a portable, verifiable IR (EquiIR). +- Each transformation step embeds lightweight cryptographic attestations (digest-based) to ensure auditability and replayability without leaking sensitive data. +- A Graph-of-Contracts (GoC) skeleton is attached to the IR to enable plug-and-play adapters for data feeds and brokers, while preserving versioned contracts and compatibility. +- The system supports offline-first evaluation with deterministic delta-sync, enabling local backtests and plan replay when connectivity resumes. +- Backends are designed for cross-runtime portability: Python backtester for offline tests, C++ for live trading, and WebAssembly for browser-based evaluation. +- The MVP keeps a minimal, stable surface area while providing clear extension points for future formal verification hooks and delta-sync workflows. + +Example workflow +- Parse a DSL to IR (programmatic): + ``from equicompiler_algebraic_portfolio_dsl_to_.core import parse_dsl_to_ir`` + ``dsl = "assets: AAPL, MSFT, GOOG\nobjectives: maximize_return\nconstraints: max_drawdown=0.2, var=0.95"`` + ``ir = parse_dsl_to_ir(dsl)`` + ``print(ir)`` +- Use the CLI to validate and inspect the IR produced from a file: + ``python -m equicompiler_algebraic_portfolio_dsl_to_.cli path/to/dsl_file.txt`` + +Roadmap (high level) +- Phase 0: DSL to IR, start backends (Python backtester, minimal C++ live skeleton) and a minimal GoC registry. +- Phase 1: Formal verification hooks and delta-sync for offline/online reconciliation. +- Phase 2: Cross-backend interoperability tests with toy adapters. +- Phase 3: Hardware-in-the-loop (HIL) testing with partitioned portfolios. + +Publishing readiness +- This repository is designed for packaging as a Python module named + ``equicompiler_algebraic_portfolio_dsl_to`` with versioning in ``pyproject.toml``. +- The README now includes a marketing-style overview and usage examples to aid publication. Project structure - AGENTS.md: architecture and testing guidelines for future agents