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Authorship Credit Gen

by @googolme

Use when determining author order on research manuscripts, assigning CRediT contributor roles for transparency, documenting individual contributions to colla...

Versionv0.1.0
Downloads447
TERMINAL
clawhub install authorship-credit-gen

πŸ“– About This Skill


name: authorship-credit-gen description: Use when determining author order on research manuscripts, assigning CRediT contributor roles for transparency, documenting individual contributions to collaborative projects, or resolving authorship disputes in multi-institutional research. Generates fair and transparent authorship assignments following ICMJE guidelines and CRediT taxonomy. Helps research teams document contributions, resolve disputes, and ensure equitable credit distribution in academic publications. allowed-tools: "Read Write Bash Edit" license: MIT metadata: skill-author: AIPOCH version: "1.0"

Research Authorship and Contributor Credit Generator

When to Use This Skill

  • determining author order on research manuscripts
  • assigning CRediT contributor roles for transparency
  • documenting individual contributions to collaborative projects
  • resolving authorship disputes in multi-institutional research
  • preparing contributor statements for journal submissions
  • evaluating contribution equity in research teams
  • Quick Start

    from scripts.main import AuthorshipCreditGen

    Initialize the tool

    tool = AuthorshipCreditGen()

    from scripts.authorship_credit import AuthorshipCreditGenerator

    generator = AuthorshipCreditGenerator(guidelines="ICMJEv4")

    Document contributions

    contributions = { "Dr. Sarah Chen": [ "Conceptualization", "Methodology", "Writing - Original Draft", "Supervision" ], "Dr. Michael Roberts": [ "Data Curation", "Formal Analysis", "Writing - Review & Editing" ], "Dr. Lisa Zhang": [ "Investigation", "Resources", "Validation" ] }

    Generate fair authorship order

    authorship = generator.determine_order( contributions=contributions, criteria=["intellectual_input", "execution", "writing", "supervision"], weights={"intellectual_input": 0.4, "execution": 0.3, "writing": 0.2, "supervision": 0.1} )

    print(f"First author: {authorship.first_author}") print(f"Corresponding: {authorship.corresponding_author}") print(f"Author order: {authorship.ordered_list}")

    Generate CRediT statement

    credit_statement = generator.generate_credit_statement( contributions=contributions, format="journal_submission" )

    Check for disputes

    dispute_check = generator.check_equity_issues(authorship) if dispute_check.has_issues: print(f"Recommendations: {dispute_check.recommendations}")

    Core Capabilities

    1. Generate Fair Authorship Orders

    Analyze contributions using weighted criteria to determine equitable author ranking.

    # Define weighted contribution criteria
    weights = {
        "conceptualization": 0.25,
        "methodology_design": 0.20,
        "data_collection": 0.15,
        "analysis": 0.15,
        "manuscript_writing": 0.15,
        "supervision": 0.10
    }

    Calculate contribution scores

    scores = tool.calculate_contribution_scores( contributions=team_contributions, weights=weights )

    Generate ordered author list

    authorship_order = tool.generate_author_order(scores) print(f"Recommended order: {authorship_order}")

    2. Assign CRediT Roles

    Map contributions to official CRediT (Contributor Roles Taxonomy) categories.

    # Map contributions to CRediT roles
    credit_roles = tool.assign_credit_roles(
        contributions=contributions,
        version="CRediT_2021"
    )

    Generate CRediT statement for journal

    statement = tool.generate_credit_statement( roles=credit_roles, format="JATS_XML" )

    Validate role assignments

    validation = tool.validate_credit_roles(credit_roles) if validation.is_valid: print("CRediT roles properly assigned")

    3. Detect Contribution Inequities

    Identify potential authorship disputes before submission.

    # Analyze contribution distribution
    equity_analysis = tool.analyze_equity(
        contributions=contributions,
        thresholds={"min_substantial": 0.15}
    )

    Flag potential issues

    if equity_analysis.has_inequities: for issue in equity_analysis.issues: print(f"Warning: {issue.description}") print(f"Recommendation: {issue.recommendation}")

    Generate equity report

    report = tool.generate_equity_report(equity_analysis)

    4. Generate Journal-Ready Statements

    Create formatted contributor statements for various journal requirements.

    # Generate for Nature-style statement
    nature_statement = tool.generate_contributor_statement(
        style="Nature",
        include_competing_interests=True
    )

    Generate for Science-style statement

    science_statement = tool.generate_contributor_statement( style="Science", include_author_contributions=True )

    Export in multiple formats

    tool.export_statement( statement=nature_statement, formats=["docx", "pdf", "txt"] )

    Command Line Usage

    python scripts/main.py --contributions contributions.json --guidelines ICMJE --output authorship_order.json
    

    Best Practices

  • Discuss authorship expectations at project inception
  • Document contributions continuously throughout project
  • Review and agree on author order before submission
  • Include non-author contributors in acknowledgments
  • Quality Checklist

    Before using this skill, ensure you have:

  • [ ] Clear understanding of your objectives
  • [ ] Necessary input data prepared and validated
  • [ ] Output requirements defined
  • [ ] Reviewed relevant documentation
  • After using this skill, verify:

  • [ ] Results meet your quality standards
  • [ ] Outputs are properly formatted
  • [ ] Any errors or warnings have been addressed
  • [ ] Results are documented appropriately
  • References

  • references/guide.md - Comprehensive user guide
  • references/examples/ - Working code examples
  • references/api-docs/ - Complete API documentation

  • Skill ID: 766 | Version: 1.0 | License: MIT

    πŸ’‘ Examples

    from scripts.main import AuthorshipCreditGen

    Initialize the tool

    tool = AuthorshipCreditGen()

    from scripts.authorship_credit import AuthorshipCreditGenerator

    generator = AuthorshipCreditGenerator(guidelines="ICMJEv4")

    Document contributions

    contributions = { "Dr. Sarah Chen": [ "Conceptualization", "Methodology", "Writing - Original Draft", "Supervision" ], "Dr. Michael Roberts": [ "Data Curation", "Formal Analysis", "Writing - Review & Editing" ], "Dr. Lisa Zhang": [ "Investigation", "Resources", "Validation" ] }

    Generate fair authorship order

    authorship = generator.determine_order( contributions=contributions, criteria=["intellectual_input", "execution", "writing", "supervision"], weights={"intellectual_input": 0.4, "execution": 0.3, "writing": 0.2, "supervision": 0.1} )

    print(f"First author: {authorship.first_author}") print(f"Corresponding: {authorship.corresponding_author}") print(f"Author order: {authorship.ordered_list}")

    Generate CRediT statement

    credit_statement = generator.generate_credit_statement( contributions=contributions, format="journal_submission" )

    Check for disputes

    dispute_check = generator.check_equity_issues(authorship) if dispute_check.has_issues: print(f"Recommendations: {dispute_check.recommendations}")

    πŸ“‹ Tips & Best Practices

  • Discuss authorship expectations at project inception
  • Document contributions continuously throughout project
  • Review and agree on author order before submission
  • Include non-author contributors in acknowledgments