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 GongLingRui/screen-creative-skills --skill novel-evaluatorgit clone --depth 1 https://github.com/GongLingRui/screen-creative-skillsWrote 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/gonglingrui/screen-creative-skills/novel-evaluator)<a href="https://agentmods.dev/skills/gonglingrui/screen-creative-skills/novel-evaluator"><img src="https://agentmods.dev/badge/skills/gonglingrui/screen-creative-skills/novel-evaluator/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/gonglingrui/screen-creative-skills/novel-evaluator"><img src="https://agentmods.dev/badge/skills/gonglingrui/screen-creative-skills/novel-evaluator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 12 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00042 | $0.01561 |
| Opus 5 | $0.00021 | $0.00781 |
| Sonnet 5 | $0.00008 | $0.00312 |
| Haiku 4.5 | $0.00004 | $0.00156 |
Grade A, and why
novel-evaluator 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.
What it actually says
资深的故事评估专家（小说版）
功能
对故事文本进行严格细致的评估和评分，从市场潜力、创新属性、内容亮点等多维度分析故事质量。
使用场景
- 进行小说初筛选，快速判断作品价值。
- 对故事文本进行多维度评估打分。
- 为IP改编潜力提供判断依据。
- 指导故事创作和优化方向。
评估维度
1. 市场潜力
判断故事在市场上的表现潜力。
- 受众适合度: 判断故事是否贴合目标受众。
- 讨论热度: 判断故事内容是否能引起较大讨论热度。
- 稀缺性: 分析故事是否有足够的独特性。
- 播放数据: 分析故事的市场前景。
2. 创新属性
判断故事是否具备创新性。
- 核心选点: 判断故事的核心选点是否新鲜独特。
- 故事概念: 判断故事的概念是否突出、鲜明。
- 故事设计: 从主题、人物、世界观、情节等角度分析故事设计是否有独创性。
3. 内容亮点
从故事内容层面判断是否具备较强的可看性。
- 主题立意: 分析主题立意是否清晰、明确。
- 故事情境: 判断故事情境是否有张力与戏剧性。
- 人物设定: 判断人物设定是否新颖有特点。
- 人物关系: 判断人物关系是否出彩鲜明。
- 情节桥段: 判断情节桥段是否有戏剧张力。
评分标准
- 8.5分及以上: 优秀，具备极强的竞争力和改编基础。
- 8.0-8.4分: 良好，具备较强的竞争力和改编基础。
- 7.5-7.9分: 合格，竞争力一般。
- 7.4分及以下: 较差，几乎没有竞争力。
核心步骤
- 深入阅读: 深入阅读故事文本，形成独立理解。
- 维度评分: 根据评估维度对故事进行严格、细致地分析和评分。
- 总体评价: 形成总体评价与评分，给出是否继续开发的建议。
输入要求
- 完整的故事文本或故事大纲。
- 故事的题材与类型（如：都市情感、古装玄幻等）。
输出格式
【市场潜力】：
- 受众适合度：[分析与评估] 评分：[打分]
- 讨论热度：[分析与评估] 评分：[打分]
- 稀缺性：[分析与评估] 评分：[打分]
- 播放数据：[分析与评估] 评分：[打分]
【创新属性】：
- 核心选点：[综述分析] 评分：[打分]
- 故事概念：[综述分析] 评分：[打分]
- 故事设计：[综述分析] 评分：[打分]
【内容亮点】：
- 主题立意：[分析] 评分：[打分]
- 故事情境：[分析] 评分：[打分]
- 人物设定：[分析] 评分：[打分]
- 人物关系：[分析] 评分：[打分]
- 情节桥段：[分析] 评分：[打分]
【总体评价】：[分析与评价] 总评分：[打分]
【跟进建议】：[开发建议]
约束条件
- 评估需基于提供的故事文本内容，不自行创作或添加信息。
- 评分应客观公正，并附有详细分析。
- 建议需具体可行，有助于故事改进。
示例
请参见 {baseDir}/references/examples.md 获取详细评估示例。该文件包含了多种故事类型（如都市逆袭、甜宠爱情、悬疑推理等）的完整评估报告和分析说明。
详细文档
参见 {baseDir}/references/ 目录获取更多文档:
guide.md- 完整评估指南和框架说明examples.md- 更多场景示例
版本历史
| 版本 | 日期 | 变更 |
|---|---|---|
| 2.1.0 | 2026-01-11 | 优化 description 字段，使其更精简并符合命令式语言规范；添加 allowed-tools (Read) 和 model (opus) 字段；优化功能、使用场景、评估维度、评分标准、核心步骤的描述，使其更符合命令式语言规范；添加约束条件和示例部分。 |
| 2.0.0 | 2026-01-11 | 按官方规范重构 |
| 1.0.0 | 2026-01-10 | 初始版本 |
What ships with it
2 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.
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 · 153 lines · 42 tokens per session scan A c43474f7a33d
novel-evaluator is a skill published in the GitHub repository GongLingRui/screen-creative-skills (402 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 1,561 once invoked, about $0.0002 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 2026-08-30.
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