OpenClaw

journal-matchmaker

Recommend suitable high-impact factor or domain-specific journals for manuscript submission based on abstract content. Trigger when user provides paper abstract and asks for journal recommendations, impact factor matching, or scope alignment suggestions.

aipoch-ai0 来源安装数☆ 0 仓库 Starsv1.0.0

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install aipoch-ai/journal-matchmaker

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Journal Matchmaker

Analyzes academic paper abstracts to recommend optimal journals for submission, considering impact factors, scope alignment, and domain expertise.

Use Cases

Find the best-fit journal for a new manuscript
Identify high-impact factor journals in specific research areas
Compare journal scopes against paper content
Discover domain-specific publication venues

Usage

python scripts/main.py --abstract "Your paper abstract text here" [--field "field_name"] [--min-if 5.0] [--count 5]

Parameters

Parameter	Type	Required	Default	Description
`--abstract`	str	Yes	-	Paper abstract text to analyze
`--field`	str	No	Auto-detect	Research field (e.g., "computer_science", "biology")
`--min-if`	float	No	0.0	Minimum impact factor threshold
`--max-if`	float	No	None	Maximum impact factor (optional)
`--count`	int	No	5	Number of recommendations to return
`--format`	str	No	table	Output format: table, json, markdown

Examples

# Basic usage
python scripts/main.py --abstract "This paper presents a novel deep learning approach..."

# Specify field and minimum impact factor
python scripts/main.py --abstract "abstract.txt" --field "ai" --min-if 10.0 --count 10

# Output as JSON for integration
python scripts/main.py --abstract "..." --format json

How It Works

Abstract Analysis: Extracts key terms, methodology, and research focus
Field Classification: Identifies the primary research domain
Journal Matching: Compares content against journal scopes and aims
Impact Factor Filtering: Applies IF constraints if specified
Ranking: Scores and ranks journals by relevance and impact

Technical Details

Difficulty: Medium
Approach: Keyword extraction + journal database matching
Data Source: Journal metadata from references/journals.json
**A...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/aipoch-ai/journal-matchmaker
Version: 1.0.0
Commit: 3c45a70805adacc3997f82d989d2732c727119b8
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# Journal Matchmaker

Analyzes academic paper abstracts to recommend optimal journals for submission, considering impact factors, scope alignment, and domain expertise.

## Use Cases

- Find the best-fit journal for a new manuscript
- Identify high-impact factor journals in specific research areas
- Compare journal scopes against paper content
- Discover domain-specific publication venues

## Usage

```bash
python scripts/main.py --abstract "Your paper abstract text here" [--field "field_name"] [--min-if 5.0] [--count 5]
```

### Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| `--abstract` | str | Yes | - | Paper abstract text to analyze |
| `--field` | str | No | Auto-detect | Research field (e.g., "computer_science", "biology") |
| `--min-if` | float | No | 0.0 | Minimum impact factor threshold |
| `--max-if` | float | No | None | Maximum impact factor (optional) |
| `--count` | int | No | 5 | Number of recommendations to return |
| `--format` | str | No | table | Output format: table, json, markdown |

## Examples

```bash
# Basic usage
python scripts/main.py --abstract "This paper presents a novel deep learning approach..."

# Specify field and minimum impact factor
python scripts/main.py --abstract "abstract.txt" --field "ai" --min-if 10.0 --count 10

# Output as JSON for integration
python scripts/main.py --abstract "..." --format json
```

## How It Works

1. **Abstract Analysis**: Extracts key terms, methodology, and research focus
2. **Field Classification**: Identifies the primary research domain
3. **Journal Matching**: Compares content against journal scopes and aims
4. **Impact Factor Filtering**: Applies IF constraints if specified
5. **Ranking**: Scores and ranks journals by relevance and impact

## Technical Details

- **Difficulty**: Medium
- **Approach**: Keyword extraction + journal database matching
- **Data Source**: Journal metadata from references/journals.json
- **A...

搜索