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 noho/code-is-cheap --skill deepreviewgit clone --depth 1 https://github.com/noho/code-is-cheapWrote 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/noho/code-is-cheap/deepreview)<a href="https://agentmods.dev/skills/noho/code-is-cheap/deepreview"><img src="https://agentmods.dev/badge/skills/noho/code-is-cheap/deepreview/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/noho/code-is-cheap/deepreview"><img src="https://agentmods.dev/badge/skills/noho/code-is-cheap/deepreview.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 | $0.00137 | $0.06792 |
| Opus 5.5 | $0.00055 | $0.02717 |
| Sonnet 5.5 | $0.00027 | $0.01358 |
| Haiku 4.5 | $0.00014 | $0.00679 |
Grade A, and why
deepreview 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 16d 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 — 444 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deepreview
Deepreview 执行严格、基于证据的 code review。它有三种 mode:
- Current Changes Mode:review 当前 workspace 和 branch 相对
main或指定 base ref 的 changes。 - PR Review Mode:review 指定 Pull Request 相对其 base branch 的完整 diff。
- All Repository Mode:review 仓库中的全部代码。
当用户要求 strict review、deep review、current unmerged changes review、PR review 或 full repository review 时,使用这个 skill。
Invocation Handling
直接映射这些短指令:
$deepreview
$deepreview 当前改动
$deepreview current changes
$deepreview --base main
$deepreview --base <ref>
使用 Current Changes Mode。裸 $deepreview 等价于 $deepreview --base main。如果提供了 --base <ref>,
就 review 当前 workspace 和 branch 相对该 base ref 的 changes,而不是默认 main。
$deepreview PR 123
$deepreview pr 123
$deepreview --pr 123
对 PR number 123 使用 PR Review Mode。
$deepreview --all
$deepreview all
$deepreview full
$deepreview repo
$deepreview 全部代码
$deepreview 整个仓库
使用 All Repository Mode。
如果同时提供 --all 和 --pr <number>,必须询问用户是要 review 整个仓库还是指定 PR,不要自行选择。
如果同时提供 --all 和 --base <ref>,使用 All Repository Mode,并把 --base 仅作为可选参照基线记录到 scope。
如果同时提供 --pr <number> 和 --base <ref>,使用 PR Review Mode,并把 --base 仅作为需要核对 PR base
branch 的显式期望。如果用户要求 PR review 但没有给 PR number,先询问 PR number。若请求无法判断是 current
changes、PR mode 还是 All Repository Mode,只问一个简短澄清问题。
Output Contract
始终把完整 review 结果写入 docs/reviews/ 下的 markdown 文件。目录不存在时创建。
写 review artifact 前,必须从本机系统时钟生成 timestamp。不要推断、手写或编造 timestamp。不要使用 001 这类计数器。
运行或执行等价操作:
mkdir -p docs/reviews
ts="$(date +%Y%m%d-%H%M%S)"
Current Changes Mode 使用生成的 timestamp:
docs/reviews/code-review-${ts}.md
PR Review Mode 使用生成的 timestamp:
docs/reviews/pr-<pr_number>-review-${ts}.md
All Repository Mode 使用生成的 timestamp:
docs/reviews/repo-review-${ts}.md
写入前,确认路径匹配以下格式之一:
docs/reviews/code-review-[0-9]{8}-[0-9]{6}.md
docs/reviews/pr-<pr_number>-review-[0-9]{8}-[0-9]{6}.md
docs/reviews/repo-review-[0-9]{8}-[0-9]{6}.md
最终回复用户时,只简要说明 review conclusion 和 output file path。
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.
- 16d ago Changed · +2 lines 51c1f43fa7ac
- 17d ago Changed · +12 lines 2adc6a039bba
- 29d ago Changed · +29 lines 14d71b9c0e61
- 2mo ago First seen · 401 lines · 137 tokens per session scan A cd76556e5ef4
deepreview is a skill published in the GitHub repository noho/code-is-cheap (94 stars, last pushed 7d ago), licensed Apache-2.0. It adds 137 tokens to every session and 6,792 once invoked, about $0.0005 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.
Other skills, from other repositories
autoreview
Structured code review through the shared OpenClaw agent-skills installation.
omh-code-review
This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…