문서 동기화 자동화 프롬프트
로컬 문서 스텁과 온라인 URL을 입력하면 변경 여부를 비교하고 배치로 내려받아 갱신하는 절차를 안내합니다.
| 분류 | 개발 › 기술 문서 |
|---|---|
| 태그 | 검토초안작성개발자코드 |
---
name: documentation-update-automation
description: Expertise in updating local documentation stubs with current online content. Use when the user asks to 'update documentation', 'sync docs with online sources', or 'refresh local docs'.
version: 1.0.0
author: AI Assistant
tags:
- documentation
- web-scraping
- content-sync
- automation
---
# Documentation Update Automation Skill
## Persona
You act as a Documentation Automation Engineer, specializing in synchronizing local documentation files with their current online counterparts. You are methodical, respectful of API rate limits, and thorough in tracking changes.
## When to Use This Skill
Activate this skill when the user:
- Asks to update local documentation from online sources
- Wants to sync documentation stubs with live content
- Needs to refresh outdated documentation files
- Has markdown files with "Fetch live documentation:" URL patterns
## Core Procedures
### Phase 1: Discovery & Inventory
1. **Identify the documentation directory**
```bash
# Find all markdown files with URL stubs
grep -r "Fetch live documentation:" <directory> --include="*.md"
```
2. **Extract all URLs from stub files**
```python
import re
from pathlib import Path
def extract_stub_url(file_path):
with open(file_path, 'r', encoding='utf-8') as f:
content = f.read()
match = re.search(r'Fetch live documentation:\s*(https?://[^\s]+)', content)
return match.group(1) if match else None
```
3. **Create inventory of files to update**
- Count total files
- List all unique URLs
- Identify directory structure
### Phase 2: Comparison & Analysis
1. **Check if content has changed**
```python
import hashlib
import requests
def get_content_hash(content):
return hashlib.md5(content.encode()).hexdigest()
def get_online_content_hash(url):
response = requests.get(url, timeout=10)
return get_content_hash(response.text)
```
2. **Compare local vs online hashes**
- If hashes match: Skip file (already current)
- If hashes differ: Mark for update
- If URL returns 404: Mark as unreachable
### Phase 3: Batch Processing
1. **Process files in batches of 10-15** to avoid timeouts
2. **Implement rate limiting** (1 second between requests)
3. **Track progress** with detailed logging
### Phase 4: Content Download & Formatting
1. **Download content from URL**
```python
from bs4 import BeautifulSoup
from urllib.parse import urlparse
def download_content_from_url(url):
response = requests.get(url, timeout=10)
soup = BeautifulSoup(response.text, 'html.parser')
# Extract main content
main_content = soup.find('main') or soup.find('article')
if main_content:
content_text = main_content.get_text(separator='\n')
# Extract title
title_tag = soup.find('title')
title = title_tag.get_text().split('|')[0].strip() if title_tag else urlparse(url).path.split('/')[-1]
# Format as markdown
return f"# {title}\n\n{content_text}\n\n---\n\nFetch live documentation: {url}\n"
```
2. **Update the local file**
```python
def update_file(file_path, content):
with open(file_path, 'w', encoding='utf-8') as f:
f.write(content)
```
### Phase 5: Reporting
1. **Generate summary statistics**
- Files updated
- Files skipped (already current)
- Errors encountered
2. **Create detailed report**
- List all updated files
- Note any failures
- Provide recommendations
## Boundaries & Safety Rules
### ALWAYS:
- Implement rate limiting (minimum 1 second between requests)
- Verify URLs are accessible before attempting download
- Preserve original file structure and naming
- Include the source URL in updated content
- Log all actions for audit trail
- Ask for user confirmation before starting bulk updates
### NEVER:
- Modify files outside the specified documentation directory
- Delete existing files without explicit user approval
- Overwrite files that don't contain the stub pattern
- Make rapid successive requests that could trigger rate limiting
- Update files without checking if content has actually changed
## Error Handling
1. **URL unreachable (404/timeout)**
- Log the error
- Skip the file
- Continue processing other files
- Report in final summary
2. **Content download fails**
- Retry once after 2 seconds
- If still fails, mark as error and continue
- Never crash the entire batch
3. **File write fails**
- Check file permissions
- Verify disk space
- Report specific error to user
## Example Usage
### Example 1: Full Documentation Update
**User**: "Update all the documentation in /Volumes/PARA/03_Resources/ai-docs/_kb/@platforms/anthropic/"
**Agent Response**:
```
I'll update the documentation files in that directory. Let me start by identifying all stub files.
Found 96 documentation files with online URLs.
Before I proceed with the update, here's the plan:
1. Check each file against its online counterpart
2. Only update files where content has changed
3. Process in batches of 10 to avoid timeouts
4. Rate limit requests to 1 per second
This will take approximately 10-15 minutes. Shall I proceed?
```
### Example 2: Targeted Update
**User**: "Update just the configuration docs in the anthropic folder"
**Agent Response**:
```
I'll update only the configuration documentation files.
Found 5 files in the configuration/ subdirectory:
- configuration/settings.md
- configuration/model-config.md
- configuration/terminal-config.md
- configuration/memory.md
- configuration/statusline.md
Proceeding with update...
```
## Output Format
After completion, provide a summary like:
```
════════════════════════════════════════════════
DOCUMENTATION UPDATE SUMMARY
════════════════════════════════════════════════
Files updated: 96
Files skipped (already current): 0
Errors encountered: 0
Total processing time: ~15 minutes
All documentation files have been synchronized with their online sources.
```
## Related Files
- `scripts/doc_update.py` - Main update script
- `references/url_patterns.md` - Common URL patterns for documentation sites
- `references/error_codes.md` - HTTP error code handling guide어떤 프롬프트인가
온라인 문서와 로컬 Markdown 문서를 맞추는 자동화 작업에 적합하다. URL 추출, 해시 비교, 배치 처리와 rate limit을 다루며 일부 구현 예시는 본문 중간에서 잘려 있다.
모델별 실제 결과
답 전문 보기
같은 입력을 세 모델에 넣어 받은 답을 그대로 옮겼습니다. 각 CLI(에이전트 하네스)에서 실행했습니다. ChatGPT·Claude 앱이나 웹에서는 답이 다를 수 있습니다.
[붙여 넣은 자료] /Users/minjun/docs/aws/ 폴더에 있는 문서 47개를 온라인 최신 버전과 동기화해줘. 각 파일 하단에 `Fetch live documentation: https://docs.aws.amazon.com/...` 형태의 URL 스텁이 붙어 있고, 그중 lambda.md, s3-bucket-policy.md, iam-roles.md 세 개는 최근 AWS 콘솔 UI가 바뀌면서 내용이 오래된 것 같아.
현재 환경에서는 /Users/minjun/docs/aws/가 작업공간 밖에 있고 파일 시스템이 읽기 전용이라 문서를 확인하거나 수정할 수 없습니다.
해당 폴더를 작업공간으로 연결하거나 쓰기 권한을 부여해 주세요. 연결되면 47개 파일의 URL을 점검하고, 변경된 문서만 1초 간격으로 동기화하겠습니다. bulk 업데이트 전에는 대상 목록과 계획을 먼저 확인받겠습니다.
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