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moai-ref-cross-model-audit

Cross-model audit convergence reference for the plan-auditor and sync-auditor agents. Documents how to invoke the `audit_multi` MCP tool to fan a code review out across the codex and GLM (z.ai) backends in parallel, converge their verdicts with the in-session Claude verdict, and fold the resulting per-backend verdicts + disagreement flag into the audit output. The single skill both audit entry points load — no duplication.

64

Quality

75%

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SecuritybySnyk

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tessl review fix ./.claude/skills/moai-ref-cross-model-audit/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

75%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A lean, well-structured tool reference with concrete parameters, an invocation snippet, an explicit convergence-policy table, and clear folding guidance. It is consistently solid across dimensions with only minor verbosity and small enumeration gaps.

Suggestions

Consolidate the Independence rule's prose and its 'Concretely' bullets to remove the restated 'do not pass full Claude analysis' guidance and tighten conciseness.

Fully enumerate the claude_verdict object shape (verdict/summary/findings/next_steps and their types) in the parameter table so the invocation is copy-paste complete.

Trim the verbose project_root note to its essential constraint (required in a worktree, must point at this checkout) without the extended rationale.

DimensionReasoningScore

Conciseness

Mostly efficient and well-structured, but a few minor repeats — the independence rule is stated, then restated as 'Concretely' bullets, and the project_root note is wordy — that could be trimmed.

4 / 5

Actionability

Concrete tool name, a parameter table with types/required/notes, an invocation snippet with real field names, and the output JSON shape give mostly executable guidance with only minor gaps (e.g. claude_verdict sub-fields not fully enumerated).

4 / 5

Workflow Clarity

The convergence policy is an explicit 4-case condition→verdict→flag table and the folding table maps per-(verdict,flag) auditor actions; checkpoints are mostly present though there is no validate→fix→retry loop (not required for this non-destructive audit skill).

4 / 5

Progressive Disclosure

Single well-organized SKILL.md with clear headers and a Cross-references section pointing to sibling tools and config keys; no bundle files to split, and the inline parameter/output detail is appropriately placed for a tool reference.

4 / 5

Total

16

/

20

Passed

Description

76%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A precise, third-person description that names concrete actions and carves out a distinct niche, with explicit trigger guidance supplied via the `when_to_use` field. Weakest on natural user-uttered trigger terms, which lean toward internal jargon.

Suggestions

Add user-facing natural-language trigger phrases to the description (e.g. 'cross-model review', 'second-opinion code review', 'multi-backend audit') so it matches how a user would actually ask for it.

Fold a short 'Use when...' clause into the description itself rather than relying solely on the separate when_to_use field, to push completeness toward 5.

Include common synonyms/variations of the trigger terms (e.g. 'codex review', 'GLM/z.ai review', 'cross-LLM verdict') to broaden keyword coverage.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'invoke the `audit_multi` MCP tool', 'fan a code review out across the codex and GLM (z.ai) backends in parallel', 'converge their verdicts', 'fold the resulting per-backend verdicts + disagreement flag into the audit output' — with comprehensive coverage.

5 / 5

Completeness

Both 'what' (invoke audit_multi, fan out, converge, fold verdicts) and 'when' (the sibling `when_to_use` field gives explicit 'Use when audit_model is multi' guidance) are present and concrete, though the trigger lives in a separate field rather than inline in the description.

4 / 5

Trigger Term Quality

Relevant domain terms ('multi-model audit', 'cross-backend second opinion', 'codex and GLM (z.ai) backends') are present but are largely internal jargon rather than natural phrases a user would utter; common synonyms and user-facing variations are missing.

3 / 5

Distinctiveness Conflict Risk

Clear niche (multi-model audit convergence) with an explicit carve-out that single-model paths do NOT load it, minimizing overlap with sibling single-backend skills.

5 / 5

Total

17

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
modu-ai/moai-adk
Reviewed

Table of Contents

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