Structured cross-model peer review for DeepSeek Harness

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.

Run agent fan-outs across two AI subscriptions at once: pick each subagent's model by complexity, length and token efficiency against live usage limits, spend Codex before Claude, and always grade work on the vendor that did not produce it.

ARIS research-workflow skills + interactive workbench panel for DeepSeek Harness (user fork of dsh-aris: 82 skills, cross-model Codex review, idea/workflow launcher, research status board).

Modula Relay — the cross-model team messaging protocol core.

ARIS research-workflow skills as a DeepSeek Harness bundle: 82 skills plus cross-model adversarial review through Codex.

Cross-model audit gate with structural enforcement. Edit → audit → agree → retro → commit.

Vendor-neutral cross-model agent collaboration runtime over a shared directory (MMAC protocol) — npm wrapper for the Python CLI

A cross-model pull request review loop. One model reviews, a second verifies and replies in-thread, then the first looks again. Runs on the AI subscriptions you already have.

One private, local memory your AI tools share. Cross-model, on-device, never lose a session.

Install the workflow substrate a cross-model AI team actually runs on: ticket intake, PR review gates, lane coordination and guards, versioned as a package. The skills Neo.mjs maintainers load every session — materialized into your repo, not copied.

Two coding agents, one better answer — cross-model collaboration broker for Claude Code and Codex.

Lightweight file-backed CLI for cross-model AI agent communication setup

智能上下文压缩 pi extension：把 compact 时机交给 agent 自决，压缩生成用双模式接管（same-model KV 缓存命中 / cross-model 廉价模型），3 档阈值提醒不强制。

Dynamic multimodal-to-text projection and cross-model vision bridge for DeepSeek Harness (dsh), allowing seamless hot-switching between vision models (Gemini/Claude) and text-only models (DeepSeek).

Cross-model, cryptographically verifiable memory for Claude, ChatGPT, and any AI agent — own your AI's memory and carry it across every model. MCP server, 36 tools: remember, semantic search, on-chain verification proofs, forensic audit, selective inject,

Cross platform child_process#spawn and child_process#spawnSync

Clean thinking blocks from Claude Code sessions to fix cross-model compatibility

Universal WHATWG Fetch API for Node, Browsers and React Native

Run scripts that set and use environment variables across platforms