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 LiPu-jpg/Openwrite --skill novel-reviewergit clone --depth 1 https://github.com/LiPu-jpg/OpenwriteWrote 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/lipu-jpg/openwrite/novel-reviewer)<a href="https://agentmods.dev/skills/lipu-jpg/openwrite/novel-reviewer"><img src="https://agentmods.dev/badge/skills/lipu-jpg/openwrite/novel-reviewer/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/lipu-jpg/openwrite/novel-reviewer"><img src="https://agentmods.dev/badge/skills/lipu-jpg/openwrite/novel-reviewer.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 | $0.00049 | $0.01120 |
| Opus 5.5 | $0.00020 | $0.00448 |
| Sonnet 5.5 | $0.00010 | $0.00224 |
| Haiku 4.5 | $0.00005 | $0.00112 |
Grade A, and why
novel-reviewer 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 1mo 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
小说审查润色
通过 openwrite-bridge 的 novel_* 工具评审与修订。不要调用 Python 审查类或本地 33 维脚本。
正式评审是六域累加：质量分、覆盖率、硬门禁、交付状态分开判断；37 项只作展开查询。
触发条件
- "检查逻辑" / "逻辑检查"
- "润色" / "润色风格"
- "找伏笔漏洞" / "伏笔检查"
- "审查章节" / "审查"
- "风格问题"
工作流程
novel_outline_read与novel_status确认章节与项目阶段。novel_chapter_work读取正文 revision、已有评审新鲜度、本章伏笔义务。novel_review_framework需要时查看六域与 37 项映射。novel_review_chapter对已有正文跑六域评审（可传chapter_id或稿件路径）。- 向作者报告质量分、覆盖率、门禁、交付状态，以及带正文证据的问题。
- 作者要改稿：
novel_revision_create_from_review（或选区novel_revision_create_selection）→ 展示 before/after → 确认后novel_revision_apply。 - 应用后必须
novel_review_chapter复评；正文 SHA 变了旧评审即 stale。 - 润色类局部修改走
novel_document_change_plan预览/确认，不直接整章覆盖。
工具
| 工具 | 用途 |
|---|---|
novel_review_framework |
六域 / 37 项框架 |
novel_review_chapter |
正式评审（长耗时） |
novel_chapter_work |
评审新鲜度、闭合结果、伏笔 |
novel_revision_create_from_review |
从问题生成修订提案 |
novel_revision_create_selection |
从选区生成修订 |
novel_revisions_list / novel_revision_get |
查看提案 |
novel_revision_apply / novel_revision_reject / novel_revision_regenerate |
应用、驳回、重生成 |
novel_document_change_plan |
手工/润色类正文预览确认 |
novel_continuity |
连续性、关系、未回收伏笔 |
六域（计分）与硬门禁
| 域 | 权重 | 关注 |
|---|---|---|
| 连贯与逻辑 | 20 | 时间线、因果、信息传播 |
| 人物与关系 | 15 | 动机、声音、关系 |
| 情节与承诺 | 20 | 伏笔、支线、情感账单 |
| 节奏与场景 | 15 | 章内节奏、场景完成度 |
| 文笔与表达 | 15 | AI 痕迹、信息倾倒、句式 |
| 正典与引用 | 15 | 设定、专名、前文事实 |
| 硬门禁 | 不计分 | 严重 blocker；只改 gate_status |
问题不扣质量分。inconclusive 降低覆盖率。交付要求：质量与覆盖达阈值、门禁未阻断、评审源 SHA 等于当前正文 SHA。
报告给作者看的结构
章节 / 字数 / 评审 revision
质量分 · 覆盖率 · 门禁 · 交付
证据条目（原文定位 + 建议）
本章伏笔：到期 / 超期 / 待埋入（来自 novel_chapter_work）
下一步：生成修订 / 驳回 / 复评
定位不唯一时标记失效，不要把错误原文高亮成证据。过期评审必须先复评。
错误处理
| 情况 | 处理 |
|---|---|
| 尚无正文 | 提示先写章，不要空审 |
| 评审 stale | 先 novel_review_chapter，禁止对旧问题直接 apply |
| 提案源 revision 不匹配 | novel_revision_regenerate 或重新预览 |
| 后台任务进行中 | novel_task_get 轮询，不要重复提交 |
与其他技能
- novel-creator：写章后进入本技能
- dog-review-query / dog-delivery-query：查询已物化评审/交付图，不重新调用模型
- truth-validation：正典与事实核对
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.
- 1mo ago Changed · -224 lines 8ffbf6c304c2
- 1mo ago First seen · 308 lines · 49 tokens per session scan A 3a7642ec26ba
novel-reviewer is a skill published in the GitHub repository LiPu-jpg/Openwrite (885 stars, last pushed today), licensed Apache-2.0. It adds 49 tokens to every session and 1,120 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.
Other skills, from other repositories
webnovel-init
A guided setup process for a web-novel project that collects creative requirements and creates the project’s initial structure and rules.
webnovel-plan
A planning tool for turning a web-novel outline into volume plans, timelines, and chapter outlines. It also writes new story settings back into the existing setting collection.
webnovel-write
A workflow for producing publishable web-novel chapters, from understanding the context through drafting, review, polishing, submission, and backup.
webnovel-review
A review agent for assessing the quality of fiction chapters. It produces a review report and writes review measurements back to the project.
webnovel-query
A Chinese-language skill for querying a web novel project's setting and story information, including characters, power systems, factions, and foreshadowing.
webnovel-learn
A project skill for learning from a web novel-writing project through the `/webnovel-learn` command. The provided details do not explain what learning tasks or outputs it performs.