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Install in OpenClaw
/install journal-selector
Description
Suggest optimal academic venues for paper submission based on paper content, novelty level, and author's goals. Activated when Chopin asks 'which journal sho...
README (SKILL.md)
Journal Selector
Match papers to the right venue — maximizing acceptance odds and impact.
Input Needed
Provide one or more of:
- Full paper draft
- Abstract
- Key contributions list
- Current submission status (new / revision / rejected)
- Author preference: speed vs. prestige, theory vs. application, impact factor priority
Output: Venue Recommendations
For each suggested venue, provide:
| Field | Description |
|---|---|
| Venue | Full name + abbreviation |
| Fit Score | 1-10, how well paper matches |
| Match Reasoning | Why this paper fits this venue |
| Risk | Reach / Safe / Safety |
| Review Speed | Fast (3-6mo) / Medium (6-9mo) / Slow (9-18mo) |
| Impact Factor | If known |
| Key Concerns | What might cause rejection here |
| Strategy Tip | How to position the paper for this venue |
Risk Classification
- Reach: Top-tier, low acceptance rate, high impact if accepted
- Safe: Lower-tier, higher acceptance, less prestige
- Safety: Almost certain acceptance, but limited impact
Review Speed Classification
- Fast: Conferences (ICRA, CDC, ACC), some letters journals
- Medium: IEEE TIE, TCST, Neurocomputing
- Slow: IEEE TAC, Automatica, Springer journals
Venue Categories for Control/AI Research
Tier 1 — High Prestige, Low Acceptance
- IEEE Transactions on Automatic Control (TAC)
- Automatica
- International Journal of Robotics Research (IJRR)
Tier 2 — Strong, Balanced
- IEEE Transactions on Industrial Electronics (TIE)
- IEEE Transactions on Control Systems Technology (TCST)
- IEEE Transactions on Robotics (TRO)
- Systems & Control Letters
- International Journal of Adaptive Control and Signal Processing
Tier 3 — Applied / Specialized
- IEEE Transactions on Aerospace and Electronic Systems
- Journal of the Franklin Institute
- Asian Journal of Control
- IET Control Theory & Applications
Tier 4 — Fast Conference Track
- CDC (IEEE Conf. on Decision and Control)
- ACC (American Control Conference)
- ICRA (IEEE Intl. Conf. on Robotics and Automation)
- IROS (IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems)
- ECC (European Control Conference)
AI / Learning + Control
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- IEEE Transactions on Artificial Intelligence
- Pattern Recognition and Machine Intelligence (PRAMI)
See references/venue-database.md for full venue profiles including IF, review speed, scope, and tips.
Decision Factors
- Paper's theory-to-application ratio — Pure theory → TAC/Automatica; Applied → TIE/TCST
- Novelty level — Incremental → Mid-tier; Breakthrough → Top-tier
- Author timeline — Need publication fast → Conference first; Can wait → Journal
- Target audience — Robotics community → ICRA/IROS; Control theory → CDC/ACC/TAC
- Revision history — Rejected from top? Suggest next-tier before re-review
Workflow
- Analyze paper: extract topic, method, contribution strength, application domain
- Map to venue categories (tier + type)
- Score fit for 8-12 candidate venues
- Select top 5-8 with varied risk levels
- Sort by fit score descending
- Include reach/safe/safety spread for author choice
Warning Signs
- Paper is too theoretical for applied journal → expect desk rejection
- Paper lacks experiments for IEEE Transactions → risky
- Novelty is incremental but targeting top-tier → high rejection risk
- Mixing control + learning communities without clear contribution to either → positioning problem
See references/venue-database.md for detailed venue profiles.
Usage Guidance
This skill appears to do what it says: analyze paper text and recommend venues. Before using it, consider privacy: avoid pasting confidential or unpublished manuscripts if you do not want their contents handled by the model/service. If you must share a full draft, confirm the platform's data retention and sharing policies or provide a redacted abstract/summary instead. Also treat acceptance rates, impact factors and review-speed estimates as approximate and verify critical decisions (deadlines, scope, current CFPs) against official venue pages. If you need provenance for the venue stats, ask the skill/maintainer to cite sources or provide last-update timestamps.
Capability Analysis
Type: OpenClaw Skill
Name: journal-selector
Version: 1.0.0
The journal-selector skill is a purely informational tool designed to assist researchers in selecting academic publication venues. It analyzes user-provided paper drafts or abstracts against a local database of journal profiles (references/venue-database.md) to provide recommendations. There is no evidence of data exfiltration, malicious execution, or harmful prompt injection instructions.
Capability Assessment
Purpose & Capability
Name/description (journal selection) align with the included SKILL.md and venue database. No unrelated binaries, env vars, or config paths are requested; the provided venue list and decision factors are coherent for the stated goal.
Instruction Scope
Instructions ask the agent to analyze submitted paper text (draft, abstract, contributions) and produce ranked venue recommendations — this is appropriate. Note: the skill explicitly expects full drafts or abstracts, which are sensitive intellectual property; the SKILL.md does not instruct any external transmission, but users should be aware that providing full manuscripts to an AI may expose them to the model/service provider's data handling.
Install Mechanism
Instruction-only skill with no install spec and no code files. This minimizes on-disk risk and there are no downloadable artifacts or third-party installers referenced.
Credentials
No environment variables, credentials, or config paths are requested. The skill does not require unrelated secrets or system access.
Persistence & Privilege
Skill is user-invocable and not always-enabled. It does not request elevated persistence or modification of other skills/configuration. Autonomous invocation is allowed by platform default but is not combined with other concerning privileges here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install journal-selector - After installation, invoke the skill by name or use
/journal-selector - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of journal-selector skill.
- Suggests optimal academic venues for paper submission based on paper content, novelty, and author’s goals.
- Provides ranked recommendations with fit score, rejection risk, review speed, and reasoning for each venue.
- Supports input via paper draft, abstract, or key contributions.
- Covers multiple venue tiers for control, AI, and robotics research, including both journals and conferences.
- Offers strategy tips and highlights key concerns for each recommended venue.
Metadata
Frequently Asked Questions
What is Journal Selector?
Suggest optimal academic venues for paper submission based on paper content, novelty level, and author's goals. Activated when Chopin asks 'which journal sho... It is an AI Agent Skill for Claude Code / OpenClaw, with 131 downloads so far.
How do I install Journal Selector?
Run "/install journal-selector" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Journal Selector free?
Yes, Journal Selector is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Journal Selector support?
Journal Selector is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Journal Selector?
It is built and maintained by Chopin (@shaopanguo); the current version is v1.0.0.
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