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整合智能体输出结果为结构化最终输出，支持多种格式。适用于整合分析报告、生成结构化报告
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Basierend auf der SOC-Berufsklassifikation
Create vertical short drama scripts covering macro construction, episode writing, precise optimization, and creative ideation using Emotional Spring Theory. Use when creating short dramas from scratch, optimizing existing script dialogue and pacing, designing story outlines with suspense hooks, or brainstorming slap-in-the-face scenes and character biographies.
Evaluate film and TV scripts across ideological, artistic, and entertainment value dimensions, producing structured scoring reports with follow-up recommendations. Use when assessing script development quality, determining modification direction, reviewing scripts before project approval, or benchmarking screenwriter capabilities.
Evaluate and score story text across market potential, innovation attributes, and content highlights dimensions, producing structured scoring reports with development recommendations. Use when conducting novel initial screening, assessing IP adaptation potential, scoring stories for multi-dimensional quality comparison, or guiding story creation and optimization direction.
Analyze five core story elements — genre type, story summary, character biographies, character relationships, and major plot points — producing a structured comprehensive report with optional mind map. Use when preparing for script adaptation, conducting deep story analysis, creating story development documentation, or evaluating overall story quality and market potential.
Orchestrate the full plot-point dramatic function analysis pipeline — text preprocessing, parallel segment analysis, result integration, and report generation — for long-form story content. Use when analyzing plot points and dramatic functions in long texts, producing structured dramatic analysis reports, or coordinating multi-step story analysis workflows.
基于故事文本分析人物特征，生成详细的人物小传。适用于深度理解故事人物设定、为演员塑造角色提供参考、为剧本创作建立人物档案
| name | output-formatter |
| description | 整合智能体输出结果为结构化最终输出，支持多种格式。适用于整合分析报告、生成结构化报告 |
| category | result-processing |
| version | 2.1.0 |
| last_updated | "2026-01-11T00:00:00.000Z" |
| license | MIT |
| compatibility | Claude Code 1.0+ |
| maintainer | 宫凡 |
| allowed-tools | [] |
| model | opus |
| changelog | [{"version":"2.1.0","date":"2026-01-11T00:00:00.000Z","changes":[{"type":"improved","content":"优化 description 字段，使其更精简并符合命令式语言规范"},{"type":"changed","content":"模型更改为 opus"},{"type":"improved","content":"优化功能、使用场景、核心能力、核心步骤、输入要求、输出格式的描述，使其更符合命令式语言规范"},{"type":"added","content":"添加约束条件、示例和详细文档部分"}]},{"version":"2.0.0","date":"2026-01-11T00:00:00.000Z","changes":[{"type":"breaking","content":"按照 Agent Skills 官方规范重构"},{"type":"improved","content":"优化 description，使用命令式语言，精简主内容"},{"type":"added","content":"添加 license、compatibility 可选字段"}]},{"version":"1.0.0","date":"2026-01-10T00:00:00.000Z","changes":[{"type":"added","content":"初始版本"}]}] |
将各个智能体的输出结果整合为结构化的最终输出，支持多种输出格式。
接收智能体输出结果
↓
根据指定输出格式进行格式化
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整合所有结果数据
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生成结构化最终输出
↓
返回格式化结果
根据指定的输出格式，提供结构化的最终结果。例如，在Markdown格式下，可能包含以下内容：
# 综合报告标题
## 故事大纲
[完整的故事大纲内容]
## 大情节点
- 情节点1: [描述]
- 情节点2: [描述]
## 思维导图
[思维导图编辑链接]
## 详细情节点
### 情节点1
[详细描述]
## 元数据信息
- 创建日期: [日期]
- 报告版本: [版本号]
参见 {baseDir}/references/examples.md 目录获取更多详细示例:
examples.md - 包含不同智能体输出整合（如故事大纲+情节点+思维导图）和多种格式转换的详细示例。参见 {baseDir}/references/examples.md 获取关于输出整理的详细指导与案例。
| 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；模型更改为 opus；优化功能、使用场景、核心能力、核心步骤、输入要求、输出格式的描述，使其更符合命令式语言规范；添加约束条件、示例和详细文档部分。 |
| 2.0.0 | 2026-01-11 | 按官方规范重构 |
| 1.0.0 | 2026-01-10 | 初始版本 |