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.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add modu-ai/moai-adk --skill moai-ref-cross-model-auditgit 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 | $0.00096 | $0.04752 |
| Opus 5.5 | $0.00038 | $0.01901 |
| Sonnet 5.5 | $0.00019 | $0.00950 |
| Haiku 4.5 | $0.00010 | $0.00475 |
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 21d 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 — 339 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 audit plan reports a cross-model backend. It documents the one MCP tool the auditor calls, the independence rule that tool enforces, how to check the result against the plan, and how to fold the returned convergence result into the auditor's verdict.
When to use convergence vs single-model
The auditor does not choose a backend by interpreting the audit_model value. It
runs moai verify audit-plan --project-root <own toplevel> first (the full flow
is in each agent's MCP Audit Tools section; pass the toplevel yourself, because
CLAUDE_PROJECT_DIR names the primary checkout in a worktree session) and
follows the plan:
| Outcome of the verb | Path | This skill |
|---|---|---|
config_status ok or absent, cross_model_active: false (the distributed default, an explicit claude token) |
Claude main: in-session review; GPT/GLM main: claude_audit |
for external-main sessions |
cross_model_active: true |
audit_multi without a gates argument: the plan's backends, converged |
this skill |
The output is the verify group's help text (it contains Shared diagnostic snapshot contract and neither config_status nor an audit-plan: line) |
The legacy path below, with "plan surface unreachable, legacy path used" named as a Gap | only as the legacy path says |
config_status: unreadable, an audit-plan: error, or any other failure to run the verb (refused, crashed, timed out, malformed output) |
Not the legacy path: a PASS-blocking Gap; a configured required backend that does not answer stays fail-closed | no PASS on this audit |
Legacy path (a binary that predates the verb). Behave as before the plan
verb existed: read the project's audit_model from workflow.yaml — multi
converges Claude, codex and GLM via audit_multi, claude keeps the
single-model path, glm and codex call that one backend directly. Wherever
audit_multi is called, pass it without a gates argument, and call it
whenever the tree's workflow.yaml sets an audit model other than claude or
any audit.gates key, so a plan-aware server applies the configured plan.
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.
- 21d ago Changed · +143 lines · -3 tokens per session b4ed96e25764
- 1mo 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 (1,237 stars, last pushed yesterday), licensed Apache-2.0. It adds 96 tokens to every session and 4,752 once invoked, about $0.0004 per session on Opus 5.5. 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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