Reference Style Sync

One-click synchronization and standardization of reference formats in literature management tools, intelligently fixing metadata errors.

One-click synchronization and standardization of reference formats in literature management tools, intelligently fixing metadata errors.

When to Use

• Use this skill when the task needs One-click synchronization and standardization of reference formats in literature management tools, intelligently fixing metadata errors.
• Use this skill for academic writing tasks that require explicit assumptions, bounded scope, and a reproducible output format.
• Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.

Key Features

See ## Features above for related details.

• Scope-focused workflow aligned to: One-click synchronization and standardization of reference formats in literature management tools, intelligently fixing metadata errors.
• Packaged executable path(s): scripts/main.py.
• Reference material available in references/ for task-specific guidance.
• Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

See ## Prerequisites above for related details.

• Python: 3.10+. Repository baseline for current packaged skills.
• dataclasses: unspecified. Declared in requirements.txt.

Example Usage

See ## Usage above for related details.

bash

cd "20260318/scientific-skills/Academic Writing/reference-style-sync"
python -m py_compile scripts/main.py
python scripts/main.py --help

Example run plan:

1. Confirm the user input, output path, and any required config values.
2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
3. Run python scripts/main.py with the validated inputs.
4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

• Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
• Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
• Primary implementation surface: scripts/main.py.
• Reference guidance: references/ contains supporting rules, prompts, or checklists.
• Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
• Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

bash

python -m py_compile scripts/main.py

Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

bash

python -m py_compile scripts/main.py
python scripts/main.py --help
python scripts/main.py -h

Workflow

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Overview

Reference Style Sync can:

• Automatically detect and fix erroneous metadata scraped in Zotero/EndNote
• Unify literature formats to standard citation styles (APA, MLA, AMA, Vancouver, etc.)
• Batch process entire literature libraries
• Intelligently complete missing fields (DOI, page numbers, volume/issue, etc.)
• Detect duplicate entries and merge them

Supported Literature Management Tools

• Zotero: Supports RDF, BibTeX, CSL JSON, RIS format export
• EndNote: Supports XML, RIS, BibTeX format export
• Universal Formats: BibTeX, RIS, CSV, JSON

Features

🔧 Metadata Repair

• Author name format standardization
• Journal name abbreviation/full name unification
• DOI format validation and completion
• Page number format normalization
• Date format unification

🎨 Format Sync

• Batch conversion to target citation format
• Field order standardization
• Punctuation unification
• Case normalization

🔍 Quality Check

• Missing field detection
• Duplicate entry identification
• Invalid DOI/URL marking
• Journal name spell checking

Usage

Command Line Interface

text

# Process single file
python scripts/main.py --input library.bib --output fixed.bib --style apa

# Fix metadata and convert to AMA format
python scripts/main.py --input zotero.rdf --output fixed.ris --style ama --fix-metadata

# Batch processing and duplicate detection
python scripts/main.py --input library.json --output cleaned.json --deduplicate --style vancouver

# Quality check only
python scripts/main.py --input library.bib --check-only

Python API

python

from scripts.main import ReferenceSync

# Initialize
sync = ReferenceSync()

# Load library
sync.load('library.bib')

# Fix metadata
sync.fix_metadata()

# Convert to target format
sync.convert_style(target_style='apa')

# Export
sync.export('output.bib')

Parameter Description

Parameter	Type	Default	Description
--input	str	Required	Input file path (.bib, .ris, .json, .xml)
--output	str	Required	Output file path
--style	str	ama	Target format: apa, mla, ama, vancouver, chicago
--fix-metadata	bool	False	Enable metadata repair
--deduplicate	bool	False	Detect and merge duplicate entries
--check-only	bool	False	Check only, no output
--format	str	auto	Input format auto-detect or specify

Repair Rules

Author Names

python

# Before repair
Smith, John, Doe, Jane M.
Smith J., Doe J.M.

# After repair (AMA)
Smith J, Doe JM.

Journal Names

python

# Before repair
journal of the american medical association
J. Am. Med. Assoc.

# After repair
JAMA

DOI

python

# Before repair
www.doi.org/10.1234/example
doi:10.1234/example
10.1234/example

# After repair
doi:10.1234/example

Page Numbers

python

# Before repair
123-127
123 -- 127
123–127

# After repair
123-127

Output Example

Before Repair (Zotero Export)

text

@article{smith2020,
  author = {Smith, John and Doe, Jane M.},
  title = {A Study of Something},
  journal = {journal of clinical medicine},
  year = {2020},
  volume = {15},
  pages = {123-127},
  doi = {10.1234/example}
}

After Repair (AMA Format)

text

@article{smith2020,
  author = {Smith J, Doe JM},
  title = {A Study of Something},
  journal = {J Clin Med},
  year = {2020},
  volume = {15},
  pages = {123-127},
  doi = {doi:10.1234/example}
}

Technical Details

Difficulty: Medium
Dependencies: Python 3.8+, regex, titlecase
Data Processing: Supports 10000+ entries batch processing

Supported Citation Formats

• AMA: American Medical Association (11th Edition)
• APA: American Psychological Association (7th Edition)
• MLA: Modern Language Association (9th Edition)
• Vancouver: ICMJE Recommended Format
• Chicago: Chicago Manual of Style (17th Edition)
• IEEE: Institute of Electrical and Electronics Engineers

Error Handling

• If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
• If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
• If scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
• Do not fabricate files, citations, data, search results, or execution outcomes.

Notes

1. It is recommended to backup the original library before processing
2. Metadata repair is based on built-in rule library; complex cases may require manual review
3. Journal abbreviations follow ISO 4 standard
4. DOI validation uses regex patterns, does not actually resolve and verify

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

text

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

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

Test Cases

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

Output Requirements

Every final response should make these items explicit when they are relevant:

• Objective or requested deliverable
• Inputs used and assumptions introduced
• Workflow or decision path
• Core result, recommendation, or artifact
• Constraints, risks, caveats, or validation needs
• Unresolved items and next-step checks

Input Validation

This skill accepts requests that match the documented purpose of reference-style-sync and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

reference-style-sync only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

References

• references/audit-reference.md - Supported scope, audit commands, and fallback boundaries

Response Template

Use the following fixed structure for non-trivial requests:

1. Objective
2. Inputs Received
3. Assumptions
4. Workflow
5. Deliverable
6. Risks and Limits
7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.