Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Content Creation
Journal Matchmaker
Recommend suitable high-impact factor or domain-specific journals for manuscript submission based on abstract content. Trigger when user provides paper abstr...
skill openclawclawhub Free
Recommend suitable high-impact factor or domain-specific journals for manuscript submission based on abstract content. Trigger when user provides paper abstr...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- requirements.txt, SKILL.md, scripts/main.py, references/fields.json, references/journals.json, references/scoring_weights.json
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- AIPOCH-AI
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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
ParameterTypeRequiredDefaultDescription--abstractstrYes-Paper abstract text to analyze--fieldstrNoAuto-detectResearch field (e.g., "computer_science", "biology")--min-iffloatNo0.0Minimum impact factor threshold--max-iffloatNoNoneMaximum impact factor (optional)--countintNo5Number of recommendations to return--formatstrNotableOutput 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 Algorithm: TF-IDF + cosine similarity for scope matching
References
references/journals.json - Journal database with impact factors and scopes references/fields.json - Research field classifications references/scoring_weights.json - Algorithm tuning parameters
Notes
Journal database should be updated periodically (quarterly recommended) Impact factor data sourced from Journal Citation Reports (JCR) Scope descriptions parsed from official journal websites For emerging fields, manual curation may be needed
Risk Assessment
Risk IndicatorAssessmentLevelCode ExecutionPython/R scripts executed locallyMediumNetwork AccessNo external API callsLowFile System AccessRead input files, write output filesMediumInstruction TamperingStandard prompt guidelinesLowData ExposureOutput files saved to workspaceLow
Security Checklist
No hardcoded credentials or API keys No unauthorized file system access (../) Output does not expose sensitive information Prompt injection protections in place Input file paths validated (no ../ traversal) Output directory restricted to workspace Script execution in sandboxed environment Error messages sanitized (no stack traces exposed) Dependencies audited
Prerequisites
# Python dependencies pip install -r requirements.txt
Success Metrics
Successfully executes main functionality Output meets quality standards Handles edge cases gracefully Performance is acceptable
Test Cases
Basic Functionality: Standard input โ Expected output Edge Case: Invalid input โ Graceful error handling Performance: Large dataset โ Acceptable processing time
Lifecycle Status
Current Stage: Draft Next Review Date: 2026-03-06 Known Issues: None Planned Improvements: Performance optimization Additional feature support
Category context
Writing, remixing, publishing, visual generation, and marketing content production.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Config1 Docs1 Scripts1 Files
- SKILL.md
- scripts/main.py
- references/fields.json
- references/journals.json
- references/scoring_weights.json
- requirements.txt