research-report

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Original

English

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Translation

Chinese

Research Report - Summary Report

研究报告 - 汇总报告

Trigger

触发指令

/research-report

/research-report

Workflow

工作流程

Step 1: Locate Results Directory

步骤1：定位结果目录

Find

*/outline.yaml

in current working directory, read topic and output_dir config.

在当前工作目录中查找

*/outline.yaml

，读取topic和output_dir配置。

Step 2: Scan Optional Summary Fields

步骤2：扫描可选汇总字段

Read all JSON results, extract fields suitable for TOC display (numeric, short metrics), e.g.:

github_stars
google_scholar_cites
swe_bench_score
user_scale
valuation
release_date

Use request_user_input to ask user:

Which fields to display in TOC besides item name?
Provide dynamic options list (based on actual fields in JSON)

读取所有JSON结果，提取适合在TOC中展示的字段（数值型、短指标），例如：

github_stars
google_scholar_cites
swe_bench_score
user_scale
valuation
release_date

使用request_user_input询问用户：

除项目名称外，哪些字段需要在TOC中展示？
提供动态选项列表（基于JSON中的实际字段）

Step 3: Generate Python Conversion Script

步骤3：生成Python转换脚本

Generate

generate_report.py

{topic}/

directory, script requirements:

Read all JSON from output_dir
Read fields.yaml to get field structure
Cover all field values from each JSON
Skip fields with values containing [uncertain]
Skip fields listed in uncertain array
Generate markdown report format: Table of contents (with anchor links + user-selected summary fields) + Detailed content (by field category)
Save to
```
{topic}/report.md
```

TOC Format Requirements:

Must include every item
Each item displays: number, name (anchor link), user-selected summary fields

Example:

1. [GitHub Copilot](#github-copilot) - Stars: 10k | Score: 85%

在

{topic}/

目录下生成

generate_report.py

脚本，脚本要求：

读取output_dir中的所有JSON文件
读取fields.yaml获取字段结构
覆盖每个JSON中的所有字段值
跳过值包含[uncertain]的字段
跳过uncertain数组中列出的字段
生成Markdown报告格式：目录（含锚点链接 + 用户选择的汇总字段） + 详细内容（按字段分类）
保存至
```
{topic}/report.md
```

TOC格式要求：

必须包含所有项目
每个项目展示：编号、名称（锚点链接）、用户选择的汇总字段

示例：

1. [GitHub Copilot](#github-copilot) - Stars: 10k | Score: 85%

Script Technical Requirements (Must Follow)

脚本技术要求（必须遵守）

1. JSON Structure Compatibility Support two JSON structures:

Flat structure: Fields directly at top level
```
{"name": "xxx", "release_date": "xxx"}
```

Nested structure: Fields in category sub-dict

{"basic_info": {"name": "xxx"}, "technical_features": {...}}

Field lookup order: Top level -> category mapping key -> Traverse all nested dicts

2. Category Multi-language Mapping fields.yaml category names and JSON keys can be any combination (CN-CN, CN-EN, EN-CN, EN-EN). Must establish bidirectional mapping:

python

CATEGORY_MAPPING = {
    "Basic Info": ["basic_info", "Basic Info"],
    "Technical Features": ["technical_features", "technical_characteristics", "Technical Features"],
    "Performance Metrics": ["performance_metrics", "performance", "Performance Metrics"],
    "Milestone Significance": ["milestone_significance", "milestones", "Milestone Significance"],
    "Business Info": ["business_info", "commercial_info", "Business Info"],
    "Competition & Ecosystem": ["competition_ecosystem", "competition", "Competition & Ecosystem"],
    "History": ["history", "History"],
    "Market Positioning": ["market_positioning", "market", "Market Positioning"],
}

3. Complex Value Formatting

list of dicts (e.g., key_events, funding_history): Format each dict as one line, separate kv with
```
|
```
Normal list: Short lists joined with comma, long lists displayed with line breaks
Nested dict: Recursive formatting, display with semicolon or line breaks
Long text strings (over 100 chars): Add line breaks
```
<br>
```
or use blockquote format for readability

4. Extra Fields Collection Collect fields that exist in JSON but not defined in fields.yaml, put in "Other Info" category. Note to filter:

Internal fields:
```
_source_file
```
,
```
uncertain
```
Nested structure top-level keys:
```
basic_info
```
,
```
technical_features
```
etc.
```
uncertain
```
array: Display each field name on separate line, don't compress into one line

5. Uncertain Value Skipping Skip conditions:

Field value contains
```
[uncertain]
```
string
Field name is in
```
uncertain
```
array
Field value is None or empty string

1. JSON结构兼容性 支持两种JSON结构：

扁平结构：字段直接位于顶层
```
{"name": "xxx", "release_date": "xxx"}
```

嵌套结构：字段位于分类子字典中

{"basic_info": {"name": "xxx"}, "technical_features": {...}}

字段查找顺序：顶层 -> 分类映射键 -> 遍历所有嵌套字典

2. 分类多语言映射 fields.yaml中的分类名称和JSON键可以是任意组合（中-中、中-英、英-中、英-英）。必须建立双向映射：

python

CATEGORY_MAPPING = {
    "Basic Info": ["basic_info", "Basic Info"],
    "Technical Features": ["technical_features", "technical_characteristics", "Technical Features"],
    "Performance Metrics": ["performance_metrics", "performance", "Performance Metrics"],
    "Milestone Significance": ["milestone_significance", "milestones", "Milestone Significance"],
    "Business Info": ["business_info", "commercial_info", "Business Info"],
    "Competition & Ecosystem": ["competition_ecosystem", "competition", "Competition & Ecosystem"],
    "History": ["history", "History"],
    "Market Positioning": ["market_positioning", "market", "Market Positioning"],
}

3. 复杂值格式化

字典列表（如key_events、funding_history）：将每个字典格式为一行，键值对用
```
|
```
分隔
普通列表：短列表用逗号连接，长列表换行展示
嵌套字典：递归格式化，用分号或换行展示
长文本字符串（超过100字符）：添加换行符
```
<br>
```
或使用块引用格式提升可读性

4. 额外字段收集 收集JSON中存在但fields.yaml未定义的字段，放入“Other Info”分类。注意过滤：

内部字段：
```
_source_file
```
、
```
uncertain
```
嵌套结构顶层键：
```
basic_info
```
、
```
technical_features
```
等
```
uncertain
```
数组：每个字段名称单独一行展示，不要压缩为一行

5. 不确定值跳过规则 跳过条件：

字段值包含
```
[uncertain]
```
字符串
字段名称在
```
uncertain
```
数组中
字段值为None或空字符串

Step 4: Execute Script

步骤4：执行脚本

Run

python {topic}/generate_report.py

运行

python {topic}/generate_report.py

Output

输出

```
{topic}/generate_report.py
```
- Conversion script
```
{topic}/report.md
```
- Summary report

```
{topic}/generate_report.py
```
- 转换脚本
```
{topic}/report.md
```
- 汇总报告