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citation-formatter-1引文格式器 1

Agent Skill

citation-formatter-1 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,916

周安装

124

GitHub Stars

公开资料未说明

下载量

1,022
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:citation-formatter-1(引文格式器 1)
来源仓库:https://github.com/aipoch-ai/citation-formatter-1
安装命令:
openclaw skills install citation-formatter-1
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install citation-formatter-1

简介

引文格式器 1 实现在不同学术引用样式间的智能转换与排版优化。

  • 适合在 OpenClaw 中处理论文、书籍章节等内容的参考文献标准化任务。
  • 通过 clawhub 安装,支持批量导入与导出 BibTeX 格式数据。
  • 安装前建议测试小样本数据以确保兼容性与准确性。
  • 注意:复杂引用关系仍需人工干预调整。citation-formatter-1 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
citation-formatter
description
Use when formatting references for journal submission, converting between citation styles (APA, MLA, Vancouver, Chicago), generating bibliographies for manuscripts, or ensuring consistent reference formatting. Automatically formats citations and bibliographies in 1000+ academic styles. Ensures reference accuracy, completeness, and compliance with journal requirements. Supports batch conversion and integration with reference managers.
license
MIT
skill-author
AIPOCH

Academic Citation Style Formatter and Converter

When to Use

  • Use this skill when the task needs Use when formatting references for journal submission, converting between citation styles (APA, MLA, Vancouver, Chicago), generating bibliographies for manuscripts, or ensuring consistent reference formatting. Automatically formats citations and bibliographies in 1000+ academic styles. Ensures reference accuracy, completeness, and compliance with journal requirements. Supports batch conversion and integration with reference managers.
  • 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

  • Scope-focused workflow aligned to: Use when formatting references for journal submission, converting between citation styles (APA, MLA, Vancouver, Chicago), generating bibliographies for manuscripts, or ensuring consistent reference formatting. Automatically formats citations and bibliographies in 1000+ academic styles. Ensures reference accuracy, completeness, and compliance with journal requirements. Supports batch conversion and integration with reference managers.
  • 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

  • Python: 3.10+. Repository baseline for current packaged skills.
  • Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.

Example Usage

cd "20260318/scientific-skills/Academic Writing/citation-formatter"
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.

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.

python -m py_compile scripts/main.py
python scripts/main.py --help
python scripts/main.py --input "Audit validation sample with explicit symptoms, history, assessment, and next-step plan." --format json

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.

When to Use This Skill

  • formatting references for journal submission
  • converting between citation styles (APA, MLA, Vancouver, Chicago)
  • generating bibliographies for manuscripts
  • ensuring consistent reference formatting
  • checking reference completeness and accuracy
  • preparing grant proposal reference sections

Quick Start

from scripts.main import CitationFormatter

# Initialize the tool
tool = CitationFormatter()

from scripts.citation_formatter import CitationFormatter

formatter = CitationFormatter()

# Format references for specific journal
formatted_refs = formatter.format_references(
    references=raw_references,
    target_style="Nature Medicine",
    output_format="docx"
)

# Convert between styles
converted = formatter.convert_style(
    bibliography=apa_bibliography,
    from_style="APA 7th",
    to_style="Vancouver",
    include_doi=True,
    include_pmids=True
)

# Validate reference completeness
validation = formatter.validate_references(
    references=reference_list,
    required_fields=["authors", "title", "journal", "year", "volume", "pages", "doi"]
)

print(f"Validation results:")
print(f"  Complete: {validation.complete_count}")
print(f"  Missing fields: {validation.incomplete_count}")
print(f"  Invalid DOIs: {len(validation.invalid_dois)}")

# Generate in-text citations
in_text = formatter.generate_in_text_citations(
    citations=[
        {"author": "Smith", "year": 2023, "type": "paren"},
        {"author": "Jones et al.", "year": 2022, "type": "narrative"}
    ],
    style="APA"
)

# Batch process multiple documents
batch_results = formatter.batch_format(
    files=["chapter1.docx", "chapter2.docx"],
    style="AMA",
    output_dir="formatted/"
)

Core Capabilities

1. Format citations in 1000+ academic styles


# Format functionality
result = tool.execute(data)

2. Convert seamlessly between citation formats


# Convert functionality
result = tool.execute(data)

3. Validate reference completeness and accuracy


# Validate functionality
result = tool.execute(data)

4. Batch process large reference collections


# Batch functionality
result = tool.execute(data)

Command Line Usage

python scripts/main.py --input references.bib --from-style APA --to-style Vancouver --output formatted.docx --validate

Best Practices

  • Always validate DOIs and URLs before submission
  • Check journal-specific requirements beyond standard style
  • Maintain original reference database for updates
  • Review formatting of special cases (websites, preprints)

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: 625 | Version: 1.0 | License: MIT

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

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.

Input Validation

This skill accepts requests that match the documented purpose of citation-formatter 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:

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

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.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

95.88%
按下载量换算980

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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