Handling Large Documentation Sites (10K+ Pages)

Complete guide for scraping and managing large documentation sites with Skill Seeker.

When to Split Documentation
Split Strategies
Quick Start
Detailed Workflows
Best Practices
Examples
Troubleshooting

When to Split Documentation

Size Guidelines

Documentation Size	Recommendation	Strategy
< 5,000 pages	One skill	No splitting needed
5,000 - 10,000 pages	Consider splitting	Category-based
10,000 - 30,000 pages	Recommended	Router + Categories
30,000+ pages	Strongly recommended	Router + Categories

Why Split Large Documentation?

Benefits:

✅ Faster scraping (parallel execution)
✅ More focused skills (better Claude performance)
✅ Easier maintenance (update one topic at a time)
✅ Better user experience (precise answers)
✅ Avoids context window limits

Trade-offs:

⚠️ Multiple skills to manage
⚠️ Initial setup more complex
⚠️ Router adds one extra skill

Split Strategies

1. No Split (One Big Skill)

Best for: Small to medium documentation (< 5K pages)

# Just use the config as-is
python3 cli/doc_scraper.py --config configs/react.json

Pros: Simple, one skill to maintain Cons: Can be slow for large docs, may hit limits

2. Category Split (Multiple Focused Skills)

Best for: 5K-15K pages with clear topic divisions

# Auto-split by categories
python3 cli/split_config.py configs/godot.json --strategy category

# Creates:
# - godot-scripting.json
# - godot-2d.json
# - godot-3d.json
# - godot-physics.json
# - etc.

Pros: Focused skills, clear separation Cons: User must know which skill to use

3. Router + Categories (Intelligent Hub) ⭐ RECOMMENDED

Best for: 10K+ pages, best user experience

# Create router + sub-skills
python3 cli/split_config.py configs/godot.json --strategy router

# Creates:
# - godot.json (router/hub)
# - godot-scripting.json
# - godot-2d.json
# - etc.

Pros: Best of both worlds, intelligent routing, natural UX Cons: Slightly more complex setup

4. Size-Based Split

Best for: Docs without clear categories

# Split every 5000 pages
python3 cli/split_config.py configs/bigdocs.json --strategy size --target-pages 5000

# Creates:
# - bigdocs-part1.json
# - bigdocs-part2.json
# - bigdocs-part3.json
# - etc.

Pros: Simple, predictable Cons: May split related topics

Quick Start

Option 1: Automatic (Recommended)

# 1. Create config
python3 cli/doc_scraper.py --interactive
# Name: godot
# URL: https://docs.godotengine.org
# ... fill in prompts ...

# 2. Estimate pages (discovers it's large)
python3 cli/estimate_pages.py configs/godot.json
# Output: ⚠️  40,000 pages detected - splitting recommended

# 3. Auto-split with router
python3 cli/split_config.py configs/godot.json --strategy router

# 4. Scrape all sub-skills
for config in configs/godot-*.json; do
  python3 cli/doc_scraper.py --config $config &
done
wait

# 5. Generate router
python3 cli/generate_router.py configs/godot-*.json

# 6. Package all
python3 cli/package_multi.py output/godot*/

# 7. Upload all .zip files to Claude

Option 2: Manual Control

# 1. Define split in config
nano configs/godot.json

# Add:
{
  "split_strategy": "router",
  "split_config": {
    "target_pages_per_skill": 5000,
    "create_router": true,
    "split_by_categories": ["scripting", "2d", "3d", "physics"]
  }
}

# 2. Split
python3 cli/split_config.py configs/godot.json

# 3. Continue as above...

Detailed Workflows

Workflow 1: Router + Categories (40K Pages)

Scenario: Godot documentation (40,000 pages)

Step 1: Estimate

python3 cli/estimate_pages.py configs/godot.json

# Output:
# Estimated: 40,000 pages
# Recommended: Split into 8 skills (5K each)

Step 2: Split Configuration

python3 cli/split_config.py configs/godot.json --strategy router --target-pages 5000

# Creates:
# configs/godot.json (router)
# configs/godot-scripting.json (5K pages)
# configs/godot-2d.json (8K pages)
# configs/godot-3d.json (10K pages)
# configs/godot-physics.json (6K pages)
# configs/godot-shaders.json (11K pages)

Step 3: Scrape Sub-Skills (Parallel)

# Open multiple terminals or use background jobs
python3 cli/doc_scraper.py --config configs/godot-scripting.json &
python3 cli/doc_scraper.py --config configs/godot-2d.json &
python3 cli/doc_scraper.py --config configs/godot-3d.json &
python3 cli/doc_scraper.py --config configs/godot-physics.json &
python3 cli/doc_scraper.py --config configs/godot-shaders.json &

# Wait for all to complete
wait

# Time: 4-8 hours (parallel) vs 20-40 hours (sequential)

Step 4: Generate Router

python3 cli/generate_router.py configs/godot-*.json

# Creates:
# output/godot/SKILL.md (router skill)

Step 5: Package All

python3 cli/package_multi.py output/godot*/

# Creates:
# output/godot.zip (router)
# output/godot-scripting.zip
# output/godot-2d.zip
# output/godot-3d.zip
# output/godot-physics.zip
# output/godot-shaders.zip

Step 6: Upload to Claude Upload all 6 .zip files to Claude. The router will intelligently direct queries to the right sub-skill!

Workflow 2: Category Split Only (15K Pages)

Scenario: Vue.js documentation (15,000 pages)

No router needed - just focused skills:

# 1. Split
python3 cli/split_config.py configs/vue.json --strategy category

# 2. Scrape each
for config in configs/vue-*.json; do
  python3 cli/doc_scraper.py --config $config
done

# 3. Package
python3 cli/package_multi.py output/vue*/

# 4. Upload all to Claude

Result: 5 focused Vue skills (components, reactivity, routing, etc.)

Best Practices

1. Choose Target Size Wisely

# Small focused skills (3K-5K pages) - more skills, very focused
python3 cli/split_config.py config.json --target-pages 3000

# Medium skills (5K-8K pages) - balanced (RECOMMENDED)
python3 cli/split_config.py config.json --target-pages 5000

# Larger skills (8K-10K pages) - fewer skills, broader
python3 cli/split_config.py config.json --target-pages 8000

2. Use Parallel Scraping

# Serial (slow - 40 hours)
for config in configs/godot-*.json; do
  python3 cli/doc_scraper.py --config $config
done

# Parallel (fast - 8 hours) ⭐
for config in configs/godot-*.json; do
  python3 cli/doc_scraper.py --config $config &
done
wait

3. Test Before Full Scrape

# Test with limited pages first
nano configs/godot-2d.json
# Set: "max_pages": 50

python3 cli/doc_scraper.py --config configs/godot-2d.json

# If output looks good, increase to full

4. Use Checkpoints for Long Scrapes

# Enable checkpoints in config
{
  "checkpoint": {
    "enabled": true,
    "interval": 1000
  }
}

# If scrape fails, resume
python3 cli/doc_scraper.py --config config.json --resume

Examples

Example 1: AWS Documentation (Hypothetical 50K Pages)

# 1. Split by AWS services
python3 cli/split_config.py configs/aws.json --strategy router --target-pages 5000

# Creates ~10 skills:
# - aws (router)
# - aws-compute (EC2, Lambda)
# - aws-storage (S3, EBS)
# - aws-database (RDS, DynamoDB)
# - etc.

# 2. Scrape in parallel (overnight)
# 3. Upload all skills to Claude
# 4. User asks "How do I create an S3 bucket?"
# 5. Router activates aws-storage skill
# 6. Focused, accurate answer!

Example 2: Microsoft Docs (100K+ Pages)

# Too large even with splitting - use selective categories

# Only scrape key topics
python3 cli/split_config.py configs/microsoft.json --strategy category

# Edit configs to include only:
# - microsoft-azure (Azure docs only)
# - microsoft-dotnet (.NET docs only)
# - microsoft-typescript (TS docs only)

# Skip less relevant sections

Troubleshooting

Issue: "Splitting creates too many skills"

Solution: Increase target size or combine categories

# Instead of 5K per skill, use 8K
python3 cli/split_config.py config.json --target-pages 8000

# Or manually combine categories in config

Issue: "Router not routing correctly"

Solution: Check routing keywords in router SKILL.md

# Review router
cat output/godot/SKILL.md

# Update keywords if needed
nano output/godot/SKILL.md

Issue: "Parallel scraping fails"

Solution: Reduce parallelism or check rate limits

# Scrape 2-3 at a time instead of all
python3 cli/doc_scraper.py --config config1.json &
python3 cli/doc_scraper.py --config config2.json &
wait

python3 cli/doc_scraper.py --config config3.json &
python3 cli/doc_scraper.py --config config4.json &
wait

Summary

For 40K+ Page Documentation:

✅ Estimate first: python3 cli/estimate_pages.py config.json
✅ Split with router: python3 cli/split_config.py config.json --strategy router
✅ Scrape in parallel: Multiple terminals or background jobs
✅ Generate router: python3 cli/generate_router.py configs/*-*.json
✅ Package all: python3 cli/package_multi.py output/*/
✅ Upload to Claude: All .zip files

Result: Intelligent, fast, focused skills that work seamlessly together!

Questions? See:

LARGE_DOCUMENTATION.md 9.5 KB

История Исходник

Handling Large Documentation Sites (10K+ Pages)

Table of Contents

When to Split Documentation

Size Guidelines

Why Split Large Documentation?

Split Strategies

1. No Split (One Big Skill)

2. Category Split (Multiple Focused Skills)

3. Router + Categories (Intelligent Hub) ⭐ RECOMMENDED

4. Size-Based Split

Quick Start

Option 1: Automatic (Recommended)

Option 2: Manual Control

Detailed Workflows

Workflow 1: Router + Categories (40K Pages)

Workflow 2: Category Split Only (15K Pages)

Best Practices

1. Choose Target Size Wisely

2. Use Parallel Scraping

3. Test Before Full Scrape

4. Use Checkpoints for Long Scrapes

Examples

Example 1: AWS Documentation (Hypothetical 50K Pages)

Example 2: Microsoft Docs (100K+ Pages)

Troubleshooting

Issue: "Splitting creates too many skills"

Issue: "Router not routing correctly"

Issue: "Parallel scraping fails"

Summary

LARGE_DOCUMENTATION.md 9.5 KB История Исходник

Handling Large Documentation Sites (10K+ Pages)

Table of Contents

When to Split Documentation

Size Guidelines

Why Split Large Documentation?

Split Strategies

1. No Split (One Big Skill)

2. Category Split (Multiple Focused Skills)

3. Router + Categories (Intelligent Hub) ⭐ RECOMMENDED

4. Size-Based Split

Quick Start

Option 1: Automatic (Recommended)

Option 2: Manual Control

Detailed Workflows

Workflow 1: Router + Categories (40K Pages)

Workflow 2: Category Split Only (15K Pages)

Best Practices

1. Choose Target Size Wisely

2. Use Parallel Scraping

3. Test Before Full Scrape

4. Use Checkpoints for Long Scrapes

Examples

Example 1: AWS Documentation (Hypothetical 50K Pages)

Example 2: Microsoft Docs (100K+ Pages)

Troubleshooting

Issue: "Splitting creates too many skills"

Issue: "Router not routing correctly"

Issue: "Parallel scraping fails"

Summary

LARGE_DOCUMENTATION.md 9.5 KB

История Исходник