Agent skill

Hit Script Retrieval Skill

by Supreme-Ultimate in Supreme-Ultimate/novel-to-script-team

爆款剧本检索技能。使用混合搜索(语义+关键词)检索最相关的爆款剧本,为生成提供参考. An agent skill from Supreme-Ultimate/novel-to-script-team.

MITAuto-check passedMedia & Creative

Install Hit Script Retrieval Skill

skills CLI
$ npx skills add Supreme-Ultimate/novel-to-script-team --skill hit-script-retrieval-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Supreme-Ultimate/novel-to-script-team hit-script-retrieval-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Supreme-Ultimate/novel-to-script-team.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hit-script-retrieval-skill .claude/skills/hit-script-retrieval-skill && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hit-script-retrieval-skill
GitHub stars
175
Token cost
~1.6k tokens
SKILL.md length
190 words
Files
1
Skills in repo
17
Repo updated
First seen
Licence
MIT

At a glance

爆款剧本检索技能。使用混合搜索(语义+关键词)检索最相关的爆款剧本,为生成提供参考. An agent skill from Supreme-Ultimate/novel-to-script-team.

  • Works in 9 steps: 剧本生成前检索 → 检索结果使用 → 构建检索查询 → …
  • Media & Creative work in your project
  • SKILL.md covers 必读, 功能, 检索方法 and 使用场景, plus 7 more sections
  • Calls python3

What it does

Hit Script Retrieval Skill is an agent skill from Supreme-Ultimate/novel-to-script-team. 爆款剧本检索技能。使用混合搜索(语义+关键词)检索最相关的爆款剧本,为生成提供参考。

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Media & Creative. The repository describes itself as: 完整的多 Agent 多 Skill 小说改编影视流水线系统。 The licence is MIT.

When your agent uses it

  • Media & Creative work in your project

Example prompts

  • “/hit-script-retrieval-skill”

Requirements

  • Python 3

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. 剧本生成前检索
  2. 检索结果使用
  3. 构建检索查询
  4. 执行检索
  5. 读取完整内容
  6. 注入到生成提示词
  7. 节奏对比
  8. 对话风格对比
  9. 情绪冲击力对比

What it can do on your machine

Read from SKILL.md and the folder at commit 117dceb. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hit Script Retrieval Skill loads about 1.6k tokens when it runs. Until then it costs about 17 tokens; SKILL.md has 190 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~17
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Supreme-Ultimate/novel-to-script-team at commit 117dceb, republished under its MIT licence (© Supreme-Ultimate). 190 words, ~1,638 tokens.

Download SKILL.mdSave it as .claude/skills/hit-script-retrieval-skill/SKILL.md (or your agent's skills folder).
name
hit-script-retrieval-skill
description
爆款剧本检索技能。使用混合搜索(语义+关键词)检索最相关的爆款剧本,为生成提供参考。

爆款剧本检索技能

必读

  1. ../../references/00-first-principles.md — 第一性原则(可拍性、留存性、一致性)
  2. ../../references/03-script-writing-standard.md — 剧本写作标准(对话比、视觉标记、网文感)
  3. ../../references/12-genre-specific-techniques.md — 类型化技巧(男频/女频特征)

功能

从117部爆款短剧剧本中检索最相关的剧本,为剧本生成提供参考。

检索方法

使用混合搜索(Chroma语义搜索 + TF-IDF关键词搜索):

  • 语义搜索权重:60%(理解深层含义)
  • 关键词搜索权重:40%(精确匹配)

使用场景

1. 剧本生成前检索

在生成剧本前,根据以下信息检索相关剧本:

  • 剧本类型(复仇/逆袭/穿越/重生等)
  • 情绪基调(愤怒/悲伤/爽感/紧张等)
  • 主要情节(打脸/揭秘/对抗/和解等)
  • 人物关系(主角vs反派/主角vs配角等)
  • 场景类型(豪门/古代/现代/职场等)

示例查询:

"复仇女主霸总豪门打脸"
"穿越古代逆袭当皇后"
"重生复仇虐恋"
2. 检索结果使用

检索返回Top 5最相关的剧本,包含:

  • 剧本文件名
  • 相似度得分
  • 内容预览(前200字符)
  • 完整文件路径

注入到context:

参考以下爆款剧本的风格和节奏:

【参考剧本1】《封总的复仇娇妻》
- 相似度:0.892
- 特点:复仇女主、霸总、豪门恩怨、打脸爽剧
- 节奏:快节奏、高冲突密度、强情绪冲击
- 对话风格:短句、高对话比、视觉标记丰富

【参考剧本2】...

执行步骤

Step 1: 构建检索查询

从当前剧本需求中提取关键信息:

python
# 示例:从分集规划中提取
query_parts = []
if "类型" in episode_plan:
    query_parts.append(episode_plan["类型"])
if "情绪" in episode_plan:
    query_parts.append(episode_plan["情绪"])
if "主要情节" in episode_plan:
    query_parts.append(episode_plan["主要情节"])

query = " ".join(query_parts)
# 结果:query = "复仇 愤怒 打脸揭秘"
Step 2: 执行检索

使用混合搜索引擎:

python
from hybrid_search import HybridSearchEngine

# 初始化(只需一次)
engine = HybridSearchEngine("../../knowledge/hit-scripts-md")

# 检索Top 5
results = engine.hybrid_search(
    query=query,
    n_results=5,
    semantic_weight=0.6,
    keyword_weight=0.4
)
Step 3: 读取完整内容
python
reference_scripts = []
for result in results:
    with open(result['path'], 'r', encoding='utf-8') as f:
        content = f.read()
        reference_scripts.append({
            'filename': result['filename'],
            'score': result['score'],
            'content': content[:5000]  # 取前5000字符
        })
Step 4: 注入到生成提示词
你是一名短剧编剧,现在需要创作第N集剧本。

【参考爆款剧本】
以下是5个最相关的爆款剧本,请参考它们的:
- 节奏:场景数、冲突密度、时长分布
- 对话:句长、对话比、视觉标记
- 情绪:情绪强度、情感极性摆动
- 框架:开局-发展-高潮-反转-结局

1. 《封总的复仇娇妻》(相似度:0.892)
[内容节选...]

2. 《...》(相似度:0.856)
[内容节选...]

...

【当前任务】
根据以上参考,创作第N集剧本...

对比分析

生成剧本后,使用相同的5个参考剧本进行对比分析:

1. 节奏对比
python
# 统计生成剧本的节奏指标
generated_metrics = {
    'scene_count': 6,
    'conflict_density': 0.015,
    'avg_scene_duration': 10,
    'emotion_intensity': 0.012
}

# 统计参考剧本的平均指标
reference_metrics = {
    'scene_count': 8.5,
    'conflict_density': 0.035,
    'avg_scene_duration': 7.5,
    'emotion_intensity': 0.025
}

# 对比分析
if generated_metrics['scene_count'] < reference_metrics['scene_count']:
    feedback.append("场景数偏少,建议增加2个过渡场景")
2. 对话风格对比
python
# 统计对话指标
generated_style = {
    'avg_sentence_length': 18,
    'dialogue_ratio': 0.45,
    'visual_markers_per_100': 1
}

reference_style = {
    'avg_sentence_length': 12,
    'dialogue_ratio': 0.72,
    'visual_markers_per_100': 4
}

# 对比分析
if generated_style['dialogue_ratio'] < reference_style['dialogue_ratio']:
    feedback.append("对话比偏低,建议增加对话,减少叙述")
3. 情绪冲击力对比
python
# 分析情绪词汇密度
generated_emotion_density = 0.5  # 每100字0.5个情绪词
reference_emotion_density = 2.0  # 每100字2个情绪词

if generated_emotion_density < reference_emotion_density:
    feedback.append("情绪词汇偏少,建议增加情绪化表达")

复审流程

导演复审(review-director)

使用 comparative-review-skill 进行综合对比:

  1. 加载生成剧本和5个参考剧本
  2. 对比节奏、对话、情绪、框架
  3. 给出PASS/FAIL判断
  4. 提供具体改进建议(引用具体的参考剧本)

输出示例:

【综合审核】FAIL

节奏问题:
- 场景数:生成6场景,参考平均8.5场景 → 建议增加2个过渡场景
- 冲突密度:生成0.015,参考平均0.035 → 建议在第3、5场景增加对抗

对话风格问题:
- 句长:生成18字符,参考平均12字符 → 建议拆分长句
- 对话比:生成45%,参考平均72% → 建议增加对话,减少叙述

参考示例:
请参考《封总的复仇娇妻》第15集的对抗场景结构
请参考《霸总的替身新娘》第8集的对话节奏
编剧复审(script-writer)

使用 style-analysis-skill 分析风格:

  1. 统计生成剧本的语言风格指标
  2. 统计5个参考剧本的平均指标
  3. 对比分析差异
  4. 提供改进建议

输出示例:

【风格分析】

句长分布:
- 生成剧本:平均18字符
- 参考剧本:平均12字符
- 建议:拆分长句,增加短句比例

对话比:
- 生成剧本:45%
- 参考剧本:72%
- 建议:增加对话,减少叙述性文字

视觉标记:
- 生成剧本:1个/100字
- 参考剧本:4个/100字
- 建议:增加视觉标记(如:冷笑、嗤笑、冷哼等)

成功标准

  1. 检索准确性:检索到的5个剧本相似度 > 0.5
  2. 参考有效性:生成剧本的指标接近参考剧本(±20%)
  3. 风格一致性:网文感、节奏感、情绪冲击力达标
  4. 复审通过:导演和编剧复审均PASS

注意事项

  1. 开源版语料:默认不包含 knowledge/hit-scripts-md/,请自行放入有权使用的 .md 剧本语料
  2. 首次使用:首次运行需要构建索引(约60秒),索引会持久化保存到本地 .search_index/
  3. 后续使用:索引已保存,加载速度快(1-2秒)
  4. 男女频分类:支持按男频/女频/全部进行过滤,提高检索精准度
  5. 权重调整:可根据实际效果调整语义/关键词权重
  6. 参考数量:默认检索Top 5,可根据需要调整(3-10个)
  7. 内容长度:注入context时建议每个参考剧本取前5000字符,避免超出上下文限制

文件位置

  • 检索引擎:../../scripts/improved_hybrid_search.py(推荐)或 ../../scripts/hybrid_search.py(备选)
  • 爆款剧本:../../knowledge/hit-scripts-md/*.md(本地自备语料,开源版默认不包含)
  • 对比分析:comparative-review-skill
  • 风格分析:style-analysis-skill

使用指南(Agent 集成)

在 script-writer 中使用

Step 0:判断原小说类型(男频/女频/中性)

根据原小说特征判断(核心判断标准:主角性别):

男频特征:
- 【核心】主角:男性主角为中心,男主视角
- 类型:复仇、逆袭、霸道、战神、龙王、赘婿、神医
- 情节:打脸、装逼、碾压、称霸
- 示例:《赘婿之王》《战神归来》《神医下山》

女频特征:
- 【核心】主角:女性主角为中心,女主视角
- 类型:虐恋、甜宠、豪门、替身、真假千金、重生复仇
- 情节:误会、虐心、和解、宠溺、逆袭
- 示例:《豪门替身妻》《真假千金》《霸总的替身新娘》

中性/不确定:
- 双主角、群像剧、或类型不明显
- 使用 `all` 参数不限类型

判断流程:
1. 首先看主角性别:男主 → 男频,女主 → 女频
2. 其次看类型关键词:复仇/战神/赘婿 → 男频,虐恋/甜宠/替身 → 女频
3. 最后看情节特征:打脸/碾压 → 男频,误会/虐心 → 女频

判断结果:
- 男频 → 使用 `male` 参数
- 女频 → 使用 `female` 参数
- 中性 → 使用 `all` 参数

Step 1:构建查询关键词

根据剧本特征选择关键词:
- 核心类型:重生、穿越、复仇、逆袭、虐恋、甜宠
- 场景类型:豪门、古代、现代、职场、校园、宫廷
- 特殊元素:道门、玄幻、霸总、白莲花、打脸(可选)

示例:query = "重生 复仇 豪门"

Step 2:执行检索

bash
# 推荐:使用改进版混合搜索(持久化索引 + 男女频分类)
python3 scripts/improved_hybrid_search.py "重生 复仇 豪门" male
# 或指定女频:python3 scripts/improved_hybrid_search.py "重生 复仇 豪门" female
# 或不限类型:python3 scripts/improved_hybrid_search.py "重生 复仇 豪门" all

# 备选:使用快速搜索(如环境不支持)
python3 scripts/quick_search.py "重生 复仇 豪门"

Step 3:读取参考剧本

读取检索结果的前5000字作为参考

Step 4:注入到 Context

将参考剧本内容注入到生成 prompt 中,参考其:
1. 对话比(约70%)
2. 视觉标记密度(3.5-4.5个/100字)
3. 网文感关键词(1.8-3.0个/100字)
4. 句长控制(10-14字符)
5. 节奏感(起承转合)
关键词选择建议

优先级1:核心类型(必选)

  • 重生、穿越、复仇、逆袭、虐恋、甜宠

优先级2:场景类型(必选)

  • 豪门、古代、现代、职场、校园、宫廷

优先级3:特殊元素(可选)

  • 道门、玄幻、霸总、白莲花、打脸

示例:

✅ 好的查询:"重生 复仇 豪门"(3个核心关键词)
❌ 不好的查询:"重生复仇道门天师豪门虐待"(太多关键词)
匹配度阈值
  • 高相关:匹配度 ≥ 3(推荐使用)
  • 中相关:匹配度 = 2(可参考)
  • 低相关:匹配度 = 1(不推荐)
数量建议
  • 精读:Top 3(完整阅读前5000字)
  • 略读:Top 5(阅读前1000字)
  • 浏览:Top 10(仅看标题和简介)
常见问题

Q1:为什么检索不到结果?

  • 使用更通用的关键词(如:"重生 复仇")
  • 降低匹配度阈值(从3降到2)
  • 增加关键词变体(如:"豪门" + "富豪")

Q2:检索结果不相关?

  • 增加更具体的关键词
  • 提高匹配度阈值(从2提到3)
  • 手动筛选结果

Q3:检索速度慢?

  • 首次初始化慢是正常的(Chroma 建立索引约60秒)
  • 后续查询会很快(索引已持久化保存)
  • 如需快速测试,可临时使用 quick_search.py
  • 缓存检索结果供后续使用

Q4:如何选择男频/女频?

  • 根据原小说类型选择:男频通常是复仇、逆袭、霸道;女频通常是虐恋、甜宠、豪门
  • 使用 male 参数检索男频剧本
  • 使用 female 参数检索女频剧本
  • 使用 all 参数不限类型(默认)

© Supreme-Ultimate, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/hit-script-retrieval-skill of Supreme-Ultimate/novel-to-script-team.

Open the folder on GitHubat commit 117dceb

Compare with similar skills

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Questions about Hit Script Retrieval Skill

What does Hit Script Retrieval Skill do?

爆款剧本检索技能。使用混合搜索(语义+关键词)检索最相关的爆款剧本,为生成提供参考. An agent skill from Supreme-Ultimate/novel-to-script-team. Hit Script Retrieval Skill is an agent skill from Supreme-Ultimate/novel-to-script-team.

When should I use Hit Script Retrieval Skill?

Hit Script Retrieval Skill fits situations like: media & Creative work in your project.

How do I install Hit Script Retrieval Skill in Claude Code?

Run `npx skills add Supreme-Ultimate/novel-to-script-team --skill hit-script-retrieval-skill -a claude-code`. Or copy the skill folder (skills/hit-script-retrieval-skill in Supreme-Ultimate/novel-to-script-team) into .claude/skills/hit-script-retrieval-skill in your project. Claude Code loads it when a task matches its description.

How do I install Hit Script Retrieval Skill in Codex?

Run `npx skills add Supreme-Ultimate/novel-to-script-team --skill hit-script-retrieval-skill -a codex`. Or copy the skill folder (skills/hit-script-retrieval-skill in Supreme-Ultimate/novel-to-script-team) into .agents/skills/hit-script-retrieval-skill in your project. Codex loads it when a task matches its description.

Can I use Hit Script Retrieval Skill in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Supreme-Ultimate/novel-to-script-team --skill hit-script-retrieval-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hit-script-retrieval-skill, .gemini/skills/hit-script-retrieval-skill, .github/skills/hit-script-retrieval-skill and .opencode/skills/hit-script-retrieval-skill in your project.

What does Hit Script Retrieval Skill need to run?

Going by SKILL.md and its folder, Hit Script Retrieval Skill needs the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Hit Script Retrieval Skill access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Hit Script Retrieval Skill safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Hit Script Retrieval Skill use?

Hit Script Retrieval Skill is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hit Script Retrieval Skill use?

About 1.6k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Hit Script Retrieval Skill?

Skills that share tags, products or a category with Hit Script Retrieval Skill: Guizang Social Cards (op7418/guizang-social-card-skill, 7.4k stars), Weekly Changelog Video (heygen-com/hyperframes, 59k stars), Anthropic Brand Styling (anthropics/skills, 180k stars) and Native Subtitle Quote Image (chengyi-ai/native-subtitle-quote-image, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hit Script Retrieval Skill?

Supreme-Ultimate (a GitHub organization) maintains it in Supreme-Ultimate/novel-to-script-team, which has 175 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on May 2, 2026.

Source: Supreme-Ultimate/novel-to-script-team on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.