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

CODEBLOCK0

Parameters

Parameter	Type	Required	Default	Description
INLINECODE0	str	Yes	-	Paper abstract text to analyze
INLINECODE1

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

CODEBLOCK1

How It Works

1. 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
• Algorithm: TF-IDF + cosine similarity for scope matching

References

• - references/journals.json - Journal database with impact factors and scopes
• INLINECODE7 - Research field classifications
• INLINECODE8 - 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 Indicator	Assessment	Level
Code Execution	Python/R scripts executed locally	Medium
Network Access

No external API calls | Low | | File System Access | Read input files, write output files | Medium | | Instruction Tampering | Standard prompt guidelines | Low | | Data Exposure | Output files saved to workspace | Low |

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

CODEBLOCK2

Evaluation Criteria

Success Metrics

• - [ ] Successfully executes main functionality
• [ ] Output meets quality standards
• [ ] Handles edge cases gracefully
• [ ] Performance is acceptable

Test Cases

1. 1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• - Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:

- Performance optimization - Additional feature support