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 Supreme-Ultimate/novel-to-script-team --skill style-analysis-skillgit clone --depth 1 https://github.com/Supreme-Ultimate/novel-to-script-teamWrote 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/supreme-ultimate/novel-to-script-team/style-analysis-skill)<a href="https://agentmods.dev/skills/supreme-ultimate/novel-to-script-team/style-analysis-skill"><img src="https://agentmods.dev/badge/skills/supreme-ultimate/novel-to-script-team/style-analysis-skill/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/supreme-ultimate/novel-to-script-team/style-analysis-skill"><img src="https://agentmods.dev/badge/skills/supreme-ultimate/novel-to-script-team/style-analysis-skill.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 | $0.00034 | $0.02950 |
| Opus 5 | $0.00017 | $0.01475 |
| Sonnet 5 | $0.00007 | $0.00590 |
| Haiku 4.5 | $0.00003 | $0.00295 |
Grade A, and why
style-analysis-skill 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 10d 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 — 356 lines — stays where its author put it; the contents beside it link to each section on GitHub.
风格分析技能
必读
../../references/00-first-principles.md— 第一性原则(可拍性、留存性)../../references/03-script-writing-standard.md— 剧本写作标准(句长、对话比、视觉标记、网文感关键词)../../references/12-genre-specific-techniques.md— 类型化技巧(男频/女频风格差异)
功能
深度分析剧本的语言风格,确保生成的剧本具有网文感、节奏感和可读性。
分析维度
1. 句长分析
统计方法:
import re
def analyze_sentence_length(script):
# 按句号、问号、感叹号分句
sentences = re.split(r'[。!?]', script)
sentences = [s.strip() for s in sentences if s.strip()]
lengths = [len(s) for s in sentences]
return {
'avg_length': sum(lengths) / len(lengths),
'short_ratio': len([l for l in lengths if l < 10]) / len(lengths),
'medium_ratio': len([l for l in lengths if 10 <= l < 20]) / len(lengths),
'long_ratio': len([l for l in lengths if l >= 20]) / len(lengths)
}
理想指标:
- 平均句长:10-14字符
- 短句比例(<10字符):30-40%
- 中句比例(10-20字符):50-60%
- 长句比例(≥20字符):<10%
2. 对话比分析
统计方法:
def analyze_dialogue_ratio(script):
# 识别对话(引号内的内容)
dialogues = re.findall(r'[「『""]([^」』""]+)[」』""]', script)
dialogue_chars = sum(len(d) for d in dialogues)
total_chars = len(script)
return {
'dialogue_ratio': dialogue_chars / total_chars,
'dialogue_count': len(dialogues),
'avg_dialogue_length': dialogue_chars / len(dialogues) if dialogues else 0
}
理想指标:
- 对话比:70-80%
- 对话数量:每1000字15-25条
- 平均对话长度:20-40字符
3. 视觉标记分析
视觉标记列表:
visual_markers = {
'表情': ['冷笑', '嗤笑', '冷哼', '微笑', '狞笑', '苦笑'],
'眼神': ['眼神一冷', '眸光一沉', '目光如炬', '眼中闪过', '瞳孔一缩'],
'动作': ['嘴角勾起', '挑眉', '皱眉', '咬牙', '握拳', '转身'],
'气场': ['气势汹汹', '霸气侧漏', '冷气逼人', '杀气腾腾']
}
统计方法:
def analyze_visual_markers(script):
all_markers = []
for category, markers in visual_markers.items():
all_markers.extend(markers)
marker_count = sum(script.count(marker) for marker in all_markers)
chars_per_100 = len(script) / 100
return {
'markers_per_100': marker_count / chars_per_100,
'marker_distribution': {
category: sum(script.count(m) for m in markers)
for category, markers in visual_markers.items()
}
}
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.
- 10d ago First seen · 356 lines · 34 tokens per session scan A ecd65d17a4a4
style-analysis-skill is a skill published in the GitHub repository Supreme-Ultimate/novel-to-script-team (163 stars, last pushed 4mo ago), licensed MIT. It adds 34 tokens to every session and 2,950 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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