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 tobihagemann/turbo --skill peer-reviewgit clone --depth 1 https://github.com/tobihagemann/turboWrote 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/tobihagemann/turbo/peer-review)<a href="https://agentmods.dev/skills/tobihagemann/turbo/peer-review"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/peer-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/tobihagemann/turbo/peer-review"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/peer-review.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 | $0.00046 | $0.01483 |
| Opus 5.5 | $0.00018 | $0.00593 |
| Sonnet 5.5 | $0.00009 | $0.00297 |
| Haiku 4.5 | $0.00005 | $0.00148 |
Grade A, and why
peer-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 5d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Peer Review
Independent peer review via codex. Translates a natural-language review request into a codex-specific prompt so invocations stay implementation-agnostic.
Step 1: Understand the Request
Identify from the invoking prompt or conversation context:
- Material — the code scope, artifact text, feedback items, or other content under review
- Criteria — reference file paths codex should read directly, inline criteria text, or the material's own domain conventions
- Dimensions — one review concern (single-pass) or multiple independent concerns (fan-out, one per dimension)
- Skepticism guidance — any material-specific instruction for pushing past surface findings; optional
- Prior adjudications — findings already judged, one line each with its verdict and the recorded reason; optional
- Output format — finding layout, priority scale, or verdict labels; optional
If no reviewable material is available, stop and state that material is required.
Step 2: Build the Codex Prompt
Assemble the prompt using codex's XML tag conventions (see /codex-exec Prompt Shaping):
<task>— the scope or material, criteria pointers (file paths codex should read, or inline criteria), and any needed context. When the material is a git diff or working-tree scope, write the diff to a file under.turbo/and reference that file as the review subject. Pin it as the sole subject: state that only this diff is under review and that any output addressing other files, languages, or topics is off-topic. List the changed file paths to reinforce the pin. When the review revisits material an earlier round already covered, rebuild the review subject from the material's current content and state that any earlier version of it is superseded. When prior adjudications were identified in Step 1, carry them into the<task>labeled as decisions already reached on proposed changes rather than as established properties of the material, and state that a listed finding is raised again only on evidence its recorded reason does not already account for. When multiple independent dimensions are specified, wrap the dimension list with explicit parallel fan-out instructions so codex delegates each dimension to its own sub-agent and waits for all before synthesizing. When the request instead asks explicitly for a single-pass review covering all dimensions, keep the review in one pass with each dimension in its own labeled section rather than fanning out, stating an explicit outcome for every dimension, including one with no qualifying findings. See/codex-execreferences/parallel-execution.md for the prompt pattern.
What ships with it
1 file 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.
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.
- 5d ago Changed dc38adc8dbe5
- 1mo ago Changed 63213988299c
- 1mo ago First seen · 67 lines · 46 tokens per session scan A f74c207981ed
peer-review is a skill published in the GitHub repository tobihagemann/turbo (417 stars, last pushed 4d ago), licensed MIT. It adds 46 tokens to every session and 1,483 once invoked, about $0.0002 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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