Cross-Model Audit Convergence

Cross-Model Audit Convergence is an AI Engineering skill for Claude Code, published by modu-ai in moai-adk.

1.2K stars220 forkson modu-ai/moai-adkAdded 2026/08/20Repository updated 2026/08/20

agentic-aiagentic-codingagentic-workflowai-agentai-codinganthropicclaudeclaude-codecli-toolcode-generationcode-qualityddddeveloper-toolsgogolangllmmulti-agentspec-driven-developmenttddvibe-coding

Install in seconds

Install Cross-Model Audit Convergence

Copy Cross-Model Audit Convergence into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/modu-ai/moai-adk/tree/main/.claude/skills/moai-ref-cross-model-audit ~/.claude/skills/moai-ref-cross-model-audit

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/modu-ai/moai-adk.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: .claude/skills/moai-ref-cross-model-audit/SKILL.md in modu-ai/moai-adk
Installs to: ~/.claude/skills/moai-ref-cross-model-audit
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What Cross-Model Audit Convergence does

Cross-Model Audit Convergence documents how plan-auditor and sync-auditor agents invoke the audit_multi MCP tool to run code review across codex and GLM backends in parallel, converge their verdicts with Claude, and fold per-backend verdicts and a disagreement flag into audit output. Use it when a project sets audit_model to multi.

Cross-Model Audit Convergence is cataloged under AI Engineering on DirSkills. Cross-Model Audit Convergence comes from a repository tagged agentic-ai, agentic-coding, agentic-workflow, ai-agent and ai-coding.

Documentation

README

Excerpt

Cross-Model Audit Convergence

This skill is the single load-point both plan-auditor and sync-auditor use when the project opts into multi-model audit (audit_model: multi). It documents the one MCP tool the auditor calls, the independence rule that tool enforces, and how to fold the returned convergence result into the auditor's verdict.

When to use convergence vs single-model

Project setting	Path	Skill
`audit_model: claude` (default)	Claude reviews alone	(none — no second opinion needed)
`audit_model: codex`	Codex reviews alone	`moai-ref-owasp-checklist` etc., no convergence
`audit_model: glm`	GLM reviews alone	(same)
`audit_model: multi`	Claude + codex + GLM, converged	this skill

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Cross-Model Audit Convergence

What else does modu-ai publish alongside Cross-Model Audit Convergence?
Cross-Model Audit Convergence is one of 25 skills that DirSkills catalogs from modu-ai/moai-adk, the repository it ships in. Its siblings there include API Patterns Reference, Backend Development and CI Loop. Each one is a separate skill with its own page in this directory, installs the same way Cross-Model Audit Convergence does, and is maintained by modu-ai in that same repository. The rest of the collection is listed on the modu-ai/moai-adk page.
How does Cross-Model Audit Convergence compare to other AI Engineering skills?
Cross-Model Audit Convergence ranks #1194 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Cross-Model Audit Convergence against them. Open each page to compare what they document and how they install.