Add AlphaLattice to Quant Research Environments (#833)

Co-authored-by: Wilson Freitas <wilson.freitas@gmail.com>

README.md

@@ -645,6 +645,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [dsh-quant](https://github.com/pengpengyi92/dsh-quant) - `TypeScript` `DeepSeek Harness` - Agent-native quantitative research toolkit for DeepSeek Harness: 46 tools across data, alpha, ML, risk, execution and ecosystem domains, with an end-to-end research pipeline.
 - [easy-stock](https://github.com/jundizhou/easy-stock) - `Go` `React` `A-shares` - Local-first AI research workbench for China A-shares: unified market overview, theme radar, limit-up ladder and sentiment-cycle analysis, AI stock reports, portfolio inspection, and agent-based collection of post-market commentary with evidence tracing.
 - [Jupyter Quant](https://github.com/quantbelt/jupyter-quant) - `Python` - A dockerized Jupyter quant research environment with preloaded tools for quant analysis, statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, etc.
+- [AlphaLattice](https://github.com/xinglin-li/alphalattice) - `Python` `Claude Code` `Codex` - Local research workbench that a coding agent drives from one sentence: dated US large-cap research positions bounded by each date's information cutoff, SEC-filing evidence review, and an investment committee that changes no numbers.
 - [SmartMoney-Cub](https://github.com/myc0576/SmartMoney-Cub) - `Python` `LLM` - Local-first, agent-agnostic trading journal and review harness that freezes point-in-time run envelopes and evidence packs, replays them deterministically, and evaluates rule candidates against a frozen 240-case finance benchmark, with no order or broker access.
 
 ## Cross-Language Frameworks