cross-agent-review

cross-agent-review is a skill for Claude Code from randommonicle/claude-skills. It costs 154 tokens per session (2,949 once invoked), scanned A, original, Apache-2.0.

A review process that asks independent AI agents, such as Claude, Gemini, or GPT, to challenge a proposed code change, design, or finding. The agents share evidence through files and cite exact file lines.

In plain words
What is it for?
It helps examine implementation changes, designs, and investigation results using read-only evidence and mandatory line citations.
Why use it?
It exposes disagreements and weak assumptions that one reviewer might miss. The review ends with a shared conclusion or clearly separated positions.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ash plugin — 43 skills, 3 hooks shipped together

Good fit It helps examine implementation changes, designs, and investigation results using read-only evidence and mandatory line citations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/randommonicle/claude-skills/cross-agent-review
Install

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.

Any agent
npx skills add randommonicle/claude-skills --skill cross-agent-review
Clone the repo
git clone --depth 1 https://github.com/randommonicle/claude-skills

Made for: Claude Code.

Or install ash, the plugin that ships this one along with the rest of its 43 skills, 3 hooks.

Wrote 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.

agentmods badge for cross-agent-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/randommonicle/claude-skills/cross-agent-review/github.svg)](https://agentmods.dev/skills/randommonicle/claude-skills/cross-agent-review)
Your own site
<a href="https://agentmods.dev/skills/randommonicle/claude-skills/cross-agent-review"><img src="https://agentmods.dev/badge/skills/randommonicle/claude-skills/cross-agent-review/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.

agentmods 80×15 button for cross-agent-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/randommonicle/claude-skills/cross-agent-review"><img src="https://agentmods.dev/badge/skills/randommonicle/claude-skills/cross-agent-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 154 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,949 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00154 $0.02949
Opus 5 $0.00077 $0.01474
Sonnet 5 $0.00031 $0.00590
Haiku 4.5 $0.00015 $0.00295

Measured 11d ago against content hash afefbd0a0992, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

cross-agent-review 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 11d 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.

cross-agent-review/SKILL.md · 165 lines

How it starts

The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cross-agent review

Two or more DIFFERENT AI agents (Claude here, the hub; plus one or more the user operates, e.g. Gemini or GPT in Antigravity) review one change by appending to a shared file, each forced to cite and to concede on evidence. The value over a solo review: an independent model catches what you are too close to, and you catch its mistakes, so a claim only survives if it survives the other agent. First run: PropOS, 2026-08-09 (five exchanges, one external agent). Second run: PropOS, 2026-08-25 (cross-firm isolation, four seats at once: Gemini 3.1 Pro, Gemini 3.7 Flash, Claude Sonnet 4.6, GPT), which added the multi-seat handle model, the hub-and-spoke turn rule, and the tracked-scaffolding git split below. Composes with findings-are-evidence, verified-citations, live-state-first, server-side-authority, confirm-before-push.

The reusable scaffolding (protocol, kickoffs, review template) is bundled in templates/ next to this file. Copy it into the exchange dir rather than retyping the rules from prose.

When to use, and when not

Use for a SCOPED target: one migration, one finding, one design decision, one document's claims. Three modes, all the same machinery:

  • Challenger-external: the other agent(s) produce findings, Claude verifies and rebuts.
  • Challenger-Claude: Claude puts up a claim or a provisional verdict, the other agent(s) attack it.
  • Peer design: all sides propose and critique a design; expected to diverge.

It scales to several independent seats at once (different models), which sharpens completeness work because each model hunts blind to what the others surface. Not for whole-project audits (use committee-review), and not for a quick check you can do yourself in one pass. It costs each agent's tokens per round and a human in the loop to drive the external agents.

Handles: how several models stay distinct and never reply to themselves

Every participant holds exactly ONE handle for the whole exchange, and a handle is a SEAT, not a model: if two chats run the same model they still get different handles.

  • CLAUDE = the hub, in this repo. BEN (or the operator's name) = the human.
  • Each external chat = a distinct handle assigned in its kickoff: GEMPRO, GEMFLASH, SONNET, GPT.

Read the full file on GitHub · 165 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 11d ago First seen · 165 lines · 154 tokens per session scan A afefbd0a0992

Subscribe to this mod's changes

cross-agent-review is a skill published in the GitHub repository randommonicle/claude-skills (23 stars, last pushed 5d ago), licensed Apache-2.0. It adds 154 tokens to every session and 2,949 once invoked, about $0.0008 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 2026-08-31.