MoAI-ADK is a Go-based harness that organizes and verifies Claude Code work across planning, implementation, synchronization, and review stages. Developers use it to structure agentic coding tasks, apply quality gates, and route work across language models, while the catalogue entries extend its workflow with skills, hooks, commands, MCP servers, instructions, and settings.
Borrowing it
Nothing to install: this file belongs to modu-ai/moai-adk. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/modu-ai/moai-adk/main/.claude/skills/moai-ref-cross-model-audit/SKILL.mdgit clone --depth 1 https://github.com/modu-ai/moai-adkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/modu-ai/moai-adk/moai-ref-cross-model-audit)<a href="https://agentmods.dev/skills/modu-ai/moai-adk/moai-ref-cross-model-audit"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-adk/moai-ref-cross-model-audit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/modu-ai/moai-adk/moai-ref-cross-model-audit"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-adk/moai-ref-cross-model-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.02410 |
| Opus 5 | $0.00049 | $0.01205 |
| Sonnet 5 | $0.00020 | $0.00482 |
| Haiku 4.5 | $0.00010 | $0.00241 |
Grade A, and why
moai-ref-cross-model-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 |
Single-model paths do NOT load this skill. Convergence is only the multi-model concern.
The audit_multi MCP tool
The single tool surface is:
mcp__moai__audit_multi
It is exposed by the moai mcp-server stdio server (the self-hosted MCP server
shipped with the binary). The tool is a thin wrapper over the convergence
engine: it does NOT re-implement the codex or GLM backends — it fans out by
calling the existing single-backend handlers in parallel and synthesizes their
results.
Input parameters
| Parameter | Type | Required | Notes |
|---|---|---|---|
claude_verdict |
object | YES | The in-session Claude review verdict. Object shape: {verdict, summary, findings, next_steps} — the same review-output.schema.json the single-backend tools return. |
target |
string | no | What the secondary backends review (uncommittedChanges, baseBranch). Passed through unchanged. |
focus |
string | no | Optional focus area forwarded to the secondary backends (e.g. concurrency, auth). |
gates |
object | no | Per-auditor gate map (claude/codex/glm ∈ off/advisory/required). When omitted, distributed defaults apply: claude required, codex required, glm advisory. |
session_id |
string | no | When set, the result is persisted to .moai/state/audit-multi/<session>.json so the multi-review-gate Stop hook reads the most recent result rather than re-invoking convergence. |
project_root |
string | no (REQUIRED in a worktree) | The tree the backends should read — this session's own git rev-parse --show-toplevel. Omitted from a worktree, the fan-out reads the PRIMARY checkout instead, so the backends review a diff that is not the one under audit and nothing in the result says so. Omit it only in the primary checkout. An unusable path is rejected with an error naming it, never silently replaced. |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 196 lines · 99 tokens per session scan A 2df2582dbd6d
moai-ref-cross-model-audit is a skill published in the GitHub repository modu-ai/moai-adk (1,206 stars, last pushed today), licensed Apache-2.0. It adds 99 tokens to every session and 2,410 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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