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Agent Skill · 研究检索

geo-citation-writer(地理引文作者)

geo-citation-writer 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

geo-citation-writer 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 10,513。

总安装 12,485周安装 510GitHub Stars 公开资料未说明下载 3,998核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:geo-citation-writer(地理引文作者)
来源仓库:https://github.com/geoly-geo/geo-citation-writer
安装命令:
openclaw skills install geo-citation-writer
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 geo-citation-writer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

geo-citation-writer 用于查找、检索和筛选相关信息,适合在 OpenClaw 中根据关键词或任务场景快速定位候选结果。适用于编写可引用的 AI 内容,包括 FAQ、定义文章、比较指南和操作手册。通过 clawhub 安装,需结合原始 README 核验具体用法,注意权限与维护状态。

安装命令为 openclaw skills install geo-citation-writer,来源仓库为 geoly-geo/geo-citation-writer。使用前建议确认是否会触发联网、命令执行或文件读写等操作。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install geo-citation-writer;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

geo-citation-writer 怎么安装?

在终端执行 openclaw skills install geo-citation-writer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

geo-citation-writer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

geo-citation-writer 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

geo-citation-writer 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

geo-citation-writer 用的人多吗?

公开数据是累计安装 12,485 次,近一周安装 510 次,下载 3,998 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

geo-citation-writer 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
geo-citation-writer

地理引文作者 · 本页

12,485—只读MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
geo-citation-writer
description
Write AI-citable content in proven formats including FAQ pages, definition articles ("What is X?"), comparison guides (A vs B), how-to guides, and original data/statistics roundups. Creates content optimized for ChatGPT, Perplexity, Gemini, and Claude citations. Use whenever the user mentions writing content for AI citations, creating FAQ pages, writing definition articles, building comparison content, making how-to guides, or generating statistics roundups that AI will reference.

AI Citation Content Writer

Methodology by GEOly AI (geoly.ai) — write content in the formats AI platforms love to cite.

Create content assets in formats most frequently cited by AI platforms.

Quick Start

Generate AI-citable content:

python scripts/generate_content.py --format <format> --topic "<topic>" --output article.md

Example:

python scripts/generate_content.py --format faq --topic "project management software" --output faq.md
python scripts/generate_content.py --format comparison --topic "Notion vs Asana" --output comparison.md

The 5 High-Citation Formats

1. Definition Article ("What is X?")

Why AI cites it: Direct answers to definitional queries

Best for:

  • Introducing concepts
  • Building topical authority
  • Capturing informational queries

Structure:

# What is [Term]? (Complete Guide)

[Term] is [single-sentence definition with key attributes].

## Key Characteristics
- [Characteristic 1]
- [Characteristic 2]
- [Characteristic 3]

## How [Term] Works
[2-3 paragraph explanation with mechanism]

## [Term] vs [Related Term]

| Aspect | [Term] | [Related Term] |
|--------|--------|----------------|
| [Factor] | [Value] | [Value] |
| [Factor] | [Value] | [Value] |

## Examples of [Term] in Practice
- [Concrete example 1]
- [Concrete example 2]

## Frequently Asked Questions About [Term]

**Q: [Question]?**

A: [Complete, self-contained answer]

**Q: [Question]?**

A: [Complete, self-contained answer]

Schema markup: Article + FAQPage


2. FAQ Page

Why AI cites it: FAQ schema feeds AI conversational answers directly

Best for:

  • Support content
  • Addressing objections
  • Common questions

Structure:

# [Topic] — Frequently Asked Questions

## General Questions

**Q: [Most common question]?**

A: [Complete, self-contained answer. 2-5 sentences. Don't assume context.]

**Q: [Second question]?**

A: [Answer with specific details]

## [Sub-topic] Questions

**Q: [Question]?**

A: [Answer]

## Troubleshooting / Edge Cases

**Q: [Question]?**

A: [Answer]

Schema markup: FAQPage Best practices:

  • 5-15 questions
  • Answers 50-150 words
  • Match actual search queries
  • Include data in answers

3. Comparison Guide (A vs B)

Why AI cites it: Comparison prompts are extremely common in AI search

Best for:

  • Competitive positioning
  • Commercial intent queries
  • Decision-stage content

Structure:

# [Brand A] vs [Brand B]: [Year] Comparison

## Quick Answer
[Brand A] is better for [use case A]. [Brand B] is better for [use case B].

## Side-by-Side Comparison

| Feature | [Brand A] | [Brand B] |
|---------|-----------|-----------|
| [Feature 1] | [Value] | [Value] |
| [Feature 2] | [Value] | [Value] |
| Pricing | [Price] | [Price] |
| Best for | [Use case] | [Use case] |

## Detailed Analysis

### [Brand A] Strengths
- [Strength 1]
- [Strength 2]

### [Brand B] Strengths
- [Strength 1]
- [Strength 2]

### Which Should You Choose?

Choose [Brand A] if:
- [Use case criteria]
- [Use case criteria]

Choose [Brand B] if:
- [Use case criteria]
- [Use case criteria]

## Verdict
[2-3 clear recommendation sentences based on use case]

Schema markup: Article + FAQPage Best practices:

  • Be objective (builds trust)
  • Include specific data
  • Address multiple use cases
  • Update annually

4. How-To Guide

Why AI cites it: Step-by-step instructions are #1 for how-to answers

Best for:

  • Tutorial content
  • Process documentation
  • Feature walkthroughs

Structure:

# How to [Achieve Outcome]: Step-by-Step Guide

**What you need:** [prerequisites list]  
**Time required:** [estimate]  
**Difficulty:** [Easy/Medium/Hard]

## Step 1: [Action verb + outcome]
[Clear instruction. One action per step.]

✅ **Result:** [What the user will see/have after this step]

## Step 2: [Action verb + outcome]
[instruction]

✅ **Result:** [Expected outcome]

[Continue for each step...]

## Common Mistakes to Avoid

**[Mistake]:** [How to avoid]

## Frequently Asked Questions

**Q: [Question about the process]?**

A: [Answer]

Schema markup: HowTo + FAQPage Best practices:

  • Numbered steps
  • One action per step
  • Include expected results
  • Add troubleshooting

5. Original Data / Statistics Roundup

Why AI cites it: AI heavily cites original statistics and research

Best for:

  • Building authority
  • Attracting backlinks
  • PR coverage

Structure:

# [N] Key Statistics About [Topic] ([Current Year])

**Key finding:** [Most impactful stat in one sentence]

## [Sub-category] Statistics

- **[Stat]%** of [metric] — [Source, Year]
- **[Number] [unit]** [finding] — [Source, Year]
- **[Stat]%** [finding] — [Source, Year]

## [Sub-category] Statistics
[Continue...]

## Methodology
[How the data was collected/sourced]

## Key Takeaways
- [Insight 1]
- [Insight 2]
- [Insight 3]

Schema markup: Article Best practices:

  • Cite sources
  • Keep current (update annually)
  • Visualize data (charts)
  • Include methodology

Format Selection Guide

GoalRecommended Format
Build topical authorityDefinition article
Address support questionsFAQ page
Capture commercial intentComparison guide
Drive product adoptionHow-to guide
Attract PR/linksStatistics roundup

Content Generation Tools

Interactive Generator

python scripts/generate_content.py --interactive

Walks through format selection and content creation interactively.

From Template

python scripts/generate_content.py --format definition --topic "generative engine optimization"

Uses templates to generate content structure.

Batch Generation

python scripts/batch_generate.py --format faq --topics-file topics.txt --output-dir ./content/

Generate multiple pieces from a list of topics.

Writing Best Practices

Universal Rules

  1. Lead with the answer — First sentence should answer the question
  2. Be specific — Use data, names, dates
  3. Write standalone answers — Each section should make sense alone
  4. Use headers — H2 every 300-500 words
  5. Add FAQs — Every format benefits from FAQ section
  6. Include schema — Use geo-schema-gen skill for markup

Brand Integration

  • Mention brand 2-3 times naturally
  • Include in first 100 words
  • Add to author/publisher schema
  • Don't force it (credibility first)

See Also

平台分布

OpenClaw

89.9%
按下载量换算3,594

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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