wiki-deep-dive
Retrieve the full content of a Wikipedia article, broken down by sections, with references and images.
Skill by aymenfurter
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/aymenfurter-wiki-deep-dive
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: writing
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/wiki-deep-dive
What's inside
- Skill name
wiki-deep-dive- Description
- Retrieve the full content of a Wikipedia article, broken down by sections, with references and images. Use when the user says: "full wikipedia article on", "deep dive into", "everything wikipedia knows about", "read me the wikipedia page for"
- License
- MIT
- Metadata
- verb: explore
- Instructions
- 106 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Wikipedia Deep Dive Skill
Fetch the full content of a Wikipedia article and present it in a structured way.
## Steps
### 1. Fetch the Full Page
```bash
python3 -c "
import wikipedia
import json
try:
page = wikipedia.page('TOPIC', auto_suggest=True)
# Split content into sections by heading pattern
import re
sections = re.split(r'\n(== .+ ==)\n', page.content)
result = {
'title': page.title,
'url': page.url,
'sections': [],
'images': page.images[:5],
'references_count': len(page.references),
'links_count': len(page.links)
}
# Parse sections
current_heading = 'Introduction'
current_body = ''
for part in sections:
if re.match(r'^== .+ ==$', part.strip()):
if current_body.strip():
result['sections'].append({'heading': current_heading, 'length': len(current_body.strip())})
current_heading = part.strip().strip('= ')
current_body = ''
else:
current_body += part
if current_body.strip():
result['sections'].append({'heading': current_heading, 'length': len(current_body.strip())})
print(json.dumps(result, indent=2))
except wikipedia.exceptions.DisambiguationError as e:
print(json.dumps({'error': 'disambiguation', 'options': e.options[:10]}, indent=2))
except wikipedia.exceptions.PageError:
print(json.dumps({'error': 'not_found'}, indent=2))
"
```
### 2. Fetch Section Content on Demand
For longer articles, first present the table of contents and then fetch specific sections when the user asks:
```bash
python3 -c "
import wikipedia
import re
page = wikipedia.page('TOPIC', auto_suggest=True)
sections = re.split(r'\n(== .+ ==)\n', page.content)
# Find the requested section
target = 'SECTION_NAME'
current_heading = 'Introduction'
for part in sections:
if re.match(r'^== .+ ==$', part.strip()):
current_heading = part.strip().strip('= ')
elif current_heading.lower() == target.lower():
print(part.strip()[:3000])
break
"
```
### 3. Present the Article Structure
```markdown
## <Article Title>
**URL**: <url>
**Sections**: X | **References**: Y | **Links**: Z
### Table of Contents
1. Introduction (<length> chars)
2. <Section Name> (<length> chars)
3. <Section Name> (<length> chars)
...
### Introduction
<first section content, truncated to reasonable length>
```
### 4. Interactive Follow-up
After presenting the overview, offer the user options:
- "Read section <name>" -- fetch and display a specific section
- "List references" -- show source URLs
- "Related topics" -- show linked Wikipedia articles
- "Save to notes" -- if the Second Brain plugin is enabled, save key points to `/data/notes/topics/<topic>.md`
### 5. Summary
Tell the user the article size, number of sections, and highlight the most substantial sections. Offer to read any section in detail.From aymenfurter/polyclaw, MIT.
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Signals
- Stars
- 87
- Forks
- 19
- Open issues
- 1
- Last commit (this folder)
- Feb 15, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/aymenfurter/polyclaw
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
wiki-deep-dive skill. Agent Mart. https://agentmart.dev/skills/aymenfurter-wiki-deep-dive (last updated 2026-10-24)