cross-eval

Original：🇺🇸 English

Translated

/cs:cross-eval <memo> — Multi-model consensus on a board memo or strategy brief. Claude + Codex + Gemini cross-review with graceful degradation.

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Sourcealirezarezvani/claude-skills

Added on2026-05-14

NPX Install

npx skill4agent add alirezarezvani/claude-skills cross-eval

SKILL.md Content

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/cs:cross-eval — Multi-Model Consensus

Command:

/cs:cross-eval <memo-or-brief>

Runs the same memo through multiple model providers and reconciles divergences. Use for high-stakes, irreversible decisions where single-model bias is too costly: M&A, major fundraises, layoffs, strategic pivots, regulatory commitments.

Adapted from gstack's

/codex

cross-review pattern, generalized to business memos instead of code PRs.

When to Run

Before signing a term sheet
Before announcing a layoff
Before committing to a regulated market
Before any decision where reversing costs > 6 months of company time
When the boardroom vote was split or had a CRITICAL dissent

Models Used (graceful degradation)

The command tries to invoke each available model in order:

Claude (primary, always available) — the boardroom's native voice
Codex / OpenAI (if
```
OPENAI_API_KEY
```
or
```
codex
```
CLI available)
Gemini (if
```
GEMINI_API_KEY
```
or
```
gemini
```
CLI available)

If only Claude is available, the command runs Claude-only with adversarial mode — same model, different prompt seeds — and clearly labels the output as single-model.

Workflow

Read the memo / brief
Probe environment for available model CLIs / API keys
For each available model:
- Send the memo with this prompt prefix:
  
  "You are an independent C-suite reviewer. The following is a board memo from another company's boardroom. Identify the top 3 concerns, the top 3 supports, and your vote (APPROVE / REJECT / DEFER). Do not deferentially agree — assume the memo's reasoning is flawed until proven otherwise."
Collect three independent reviews
Reconcile: where do they agree? Where do they diverge?
Surface the divergences as questions for the founder

Output Format

Saved to

~/.claude/cross-eval/YYYY-MM-DD-<slug>.md

:

markdown

# Cross-Eval: <memo title>
**Date:** YYYY-MM-DD
**Memo reviewed:** <link>
**Models invoked:** Claude / Codex / Gemini (or noted fallbacks)

## Vote Tally
| Model | Vote | Confidence |
|---|---|---|
| Claude | APPROVE | High |
| Codex | DEFER | Med |
| Gemini | APPROVE | Low |

## Consensus Concerns (≥2 models flagged)
1. <concern> — flagged by Claude + Codex
2. <concern> — flagged by all 3

## Divergent Concerns (1 model flagged)
- <Codex only:> <concern> — worth a second look
- <Gemini only:> <concern> — likely noise, but check

## Consensus Supports (≥2 models endorsed)
1. <support>
2. <support>

## Recommendation
- 🟢 GO if 2+ models APPROVE and no CRITICAL concerns from any model
- 🟡 PAUSE if any model is DEFER or any concern is CRITICAL
- 🔴 STOP if 2+ models REJECT

## Open Questions for Founder
1. <question raised by divergence>
2. <question raised by divergence>

Why This Matters

Single-model recommendations have systematic biases. Claude trends helpful and may under-weight risk. Codex (OpenAI) trends more cautious on emerging-market and regulatory topics. Gemini trends more cautious on technical scale claims. Disagreement is signal, not noise.

This is the safety net before irreversibility — not a replacement for outside counsel or a real board.

Graceful Degradation

If only Claude is available: