An intelligent academic assistant that matches research papers with optimal publication venues based on content, impact, and review speed.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install journal-selector
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install journal-selector using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Journal Selector?
The Journal Selector is a specialized tool designed to assist researchers in navigating the complex landscape of academic publishing. By leveraging Openclaw Skills, this tool analyzes a paper's theoretical depth, practical application, and novelty to suggest the most appropriate venues. It bridge the gap between finishing a draft and finding a home for your work, ensuring that researchers target journals and conferences where they have the highest probability of success and impact.
This skill is particularly valuable for authors working in interdisciplinary fields like AI, control theory, and robotics, where choosing between a high-prestige journal and a fast-tracked conference can significantly affect a paper's lifecycle. By providing a ranked list of recommendations with associated risk levels, the skill empowers authors to make data-driven decisions about their submission strategy.
Journal Selector Use Cases
- Selecting the most appropriate conference or journal for a newly completed research draft.
- Finding a secondary venue after receiving a rejection from a top-tier publication.
- Identifying journals with fast review cycles when facing strict graduation or funding deadlines.
- Determining if a paper is better suited for a theoretical venue like Automatica or an applied one like IEEE TIE.
How Journal Selector Works
- The researcher provides the paper draft, abstract, or a summary of key contributions to the agent.
- The skill extracts critical features such as the topic, methodology, contribution strength, and application domain.
- It maps these features against a categorized database of tiers ranging from high-prestige (Tier 1) to specialized or conference tracks (Tier 4).
- Each potential venue is assigned a fit score based on the theory-to-application ratio and novelty level.
- The tool generates a ranked list of 5-8 recommendations, categorized by risk level (Reach, Safe, Safety) and review speed.
Journal Selector Setup
To start using this skill within your environment, ensure you have the core framework installed and then add the selector:
openclaw install journal-selector
Users can customize the recommendation engine by updating the references/venue-database.md file with specific impact factors or internal institutional preferences.
Journal Selector Data Schema & Taxonomy
The Journal Selector organizes its output into a structured report to ensure clarity. The data is presented using the following metadata taxonomy:
| Attribute | Description |
|---|---|
| Venue | Full name and abbreviation of the journal or conference |
| Fit Score | A 1-10 rating of how well the paper matches the venue scope |
| Risk Level | Categorization into Reach (High impact/Low rate), Safe, or Safety (High probability) |
| Review Speed | Estimated timeline: Fast (3-6mo), Medium (6-9mo), or Slow (9-18mo) |
| Strategy Tip | Actionable advice on how to frame the paper for that specific audience |
Journal Selector Advanced Features
- Multi-tier risk spread providing a balanced portfolio of submission options from 'Reach' to 'Safety' venues.
- Specialized filtering for AI and Learning + Control communities, identifying journals like TNNLS or PRAMI.
- Automated warning system that identifies 'desk rejection' risks, such as lack of experimental data for specific transactions.
- Integrated revision history analysis to suggest the next logical step in a submission pipeline after a prior rejection.
SKILL.md
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