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 freestyler-arb/imagine-gemini-for-claude-codex --skill gemini-reviewgit clone --depth 1 https://github.com/freestyler-arb/imagine-gemini-for-claude-codexWrote 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/freestyler-arb/imagine-gemini-for-claude-codex/gemini-review)<a href="https://agentmods.dev/skills/freestyler-arb/imagine-gemini-for-claude-codex/gemini-review"><img src="https://agentmods.dev/badge/skills/freestyler-arb/imagine-gemini-for-claude-codex/gemini-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.
<a href="https://agentmods.dev/skills/freestyler-arb/imagine-gemini-for-claude-codex/gemini-review"><img src="https://agentmods.dev/badge/skills/freestyler-arb/imagine-gemini-for-claude-codex/gemini-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00102 | $0.01046 |
| Opus 5 | $0.00051 | $0.00523 |
| Sonnet 5 | $0.00020 | $0.00209 |
| Haiku 4.5 | $0.00010 | $0.00105 |
Grade A, and why
gemini-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gemini-review
Overview
Get a structured, adversarial review from Google Gemini as a second pair of eyes. Different model families fail differently, so Gemini frequently flags correctness bugs, edge cases, and security issues that the main agent's own review misses. The review runs on the user's AI Pro subscription (agy) and does not spend the main agent's tokens.
This is a specialised wrapper around gemini-pro: same delegation mechanics, but with a fixed review prompt and a severity-tagged output format. For freeform delegation use gemini-pro; for research/digestion use gemini-research.
How to invoke
Pipe the artifact under review via stdin and ask for a structured review. Use the default Pro/High model — review quality matters more than quota here.
# A single file
cat src/order_engine.py | gemini "$(cat <<'PROMPT'
You are a senior engineer doing an adversarial code review. Find real defects only.
For each finding give: [SEVERITY: critical|high|medium|low] — file/area — the bug —
why it is wrong — a concrete fix. End with a one-line overall verdict (ship / fix-first).
Do NOT invent issues; if the code is fine, say so. Focus on:
correctness bugs, race conditions, edge cases, error handling, security, and data loss.
PROMPT
)"
# A diff / PR
git diff main...HEAD | gemini "Adversarial review of this diff. Same format: [SEVERITY] — area — bug — why — fix. Only real defects."
If gemini is not on PATH use ~/.local/bin/gemini or agy -p "<prompt>" --model "Gemini 3.1 Pro (High)".
Steps
- Collect the exact artifact — a file, a set of files,
git diff, or a written plan. Smaller and focused beats dumping the whole repo. - Strip secrets (API keys, tokens, private data) before piping. Never send credentials to an external model.
- Write the review prompt stating the role, what to look for, the severity format, and the "no invented issues" guardrail. Add domain constraints the reviewer must respect (invariants, perf budgets, API contracts) — Gemini has none of this session's context.
- Run it (Pro/High, ~20–90s; Bash
timeout~120000 ms). - Triage the findings yourself. Confirm each against the actual code before acting — Gemini can produce confident false positives. Relay a synthesised, de-duplicated list, attributed to Gemini, with your own verdict on which findings are real.
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.
- 12d ago First seen · 63 lines · 102 tokens per session scan A 8c4e2f92301f
gemini-review is a skill published in the GitHub repository freestyler-arb/imagine-gemini-for-claude-codex (4 stars, last pushed 2mo ago), licensed MIT. It adds 102 tokens to every session and 1,046 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 2026-08-31.
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