219 lines
6.0 KiB
Markdown
219 lines
6.0 KiB
Markdown
# Smart Auto-Categorization Guide
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## Overview
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The skill collection now uses intelligent auto-categorization to eliminate "uncategorized" and organize skills into meaningful categories based on their content.
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## Current Status
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✅ Current repository indexed through the generated catalog
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- Most skills are in meaningful categories
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- A smaller tail still needs manual review or better keyword coverage
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- `skills_index.json` is the source of truth for current category labels and counts
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- Category filters should be derived from the generated index at build time
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## Category Distribution
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Do not copy fixed counts into user-facing docs. To inspect the current distribution, generate it from the index:
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```bash
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node - <<'NODE'
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const fs = require('fs');
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const skills = JSON.parse(fs.readFileSync('skills_index.json', 'utf8'));
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const counts = new Map();
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for (const skill of skills) {
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const category = skill.category || 'uncategorized';
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counts.set(category, (counts.get(category) || 0) + 1);
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}
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console.log(`skills=${skills.length} categories=${counts.size}`);
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for (const [category, count] of [...counts.entries()].sort((a, b) => b[1] - a[1]).slice(0, 12)) {
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console.log(`${category}: ${count}`);
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}
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NODE
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```
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## How It Works
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### 1. **Keyword-Based Analysis**
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The system analyzes skill names and descriptions for keywords:
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- **Backend**: nodejs, express, fastapi, django, server, api, database
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- **Web Dev**: react, vue, angular, frontend, css, html, tailwind
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- **AI/ML**: ai, machine learning, tensorflow, nlp, gpt
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- **DevOps**: docker, kubernetes, ci/cd, deploy
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- And more...
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### 2. **Priority System**
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Frontmatter category > Detected Keywords > Fallback (uncategorized)
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If a skill already has a category in frontmatter, that's preserved.
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### 3. **Scope-Based Matching**
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- Exact phrase matches weighted 2x higher than partial matches
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- Uses word boundaries to avoid false positives
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## Using the Auto-Categorization
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### Run on Uncategorized Skills
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```bash
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python tools/scripts/auto_categorize_skills.py
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```
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### Preview Changes First (Dry Run)
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```bash
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python tools/scripts/auto_categorize_skills.py --dry-run
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```
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### Output
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```
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======================================================================
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AUTO-CATEGORIZATION REPORT
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======================================================================
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Summary:
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✅ Categorized: 776
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⏭️ Already categorized: 46
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❌ Failed to categorize: 124
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📈 Total processed: full repository
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Sample changes:
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• 3d-web-experience
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uncategorized → web-development
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• ab-test-setup
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uncategorized → testing
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• agent-framework-azure-ai-py
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uncategorized → backend
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```
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## Web App Improvements
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### Category Filter
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**Before:**
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- Unordered list including "uncategorized"
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- No indication of category size
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**After:**
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- Categories sorted by skill count (most first, "uncategorized" last)
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- Shows counts from the generated index instead of hard-coded documentation numbers
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- Much easier to browse
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### Example Dropdowns
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**Sorted Order:**
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1. All Categories
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2. Highest-count generated category
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3. Next generated category
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4. ... more generated categories ...
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5. Uncategorized, if present, at the end
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## For Skill Creators
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### When Adding a New Skill
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Include category in frontmatter:
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```yaml
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---
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name: my-skill
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description: "..."
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category: web-development
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date_added: "2026-03-06"
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---
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```
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### If You're Not Sure
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The system will automatically categorize on next index regeneration:
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```bash
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python tools/scripts/generate_index.py
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```
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## Keyword Reference
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Available auto-categorization keywords by category:
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**Backend**: nodejs, node.js, express, fastapi, django, flask, spring, java, python, golang, rust, server, api, rest, graphql, database, sql, mongodb
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**Web Development**: react, vue, angular, html, css, javascript, typescript, frontend, tailwind, bootstrap, webpack, vite, pwa, responsive, seo
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**Database**: database, sql, postgres, mysql, mongodb, firestore, redis, orm, schema
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**AI/ML**: ai, machine learning, ml, tensorflow, pytorch, nlp, llm, gpt, transformer, embedding, training
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**DevOps**: docker, kubernetes, ci/cd, git, jenkins, terraform, ansible, deploy, container, monitoring
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**Cloud**: aws, azure, gcp, serverless, lambda, storage, cdn
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**Security**: encryption, cryptography, jwt, oauth, authentication, authorization, vulnerability
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**Testing**: test, jest, mocha, pytest, cypress, selenium, unit test, e2e
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**Mobile**: mobile, react native, flutter, ios, android, swift, kotlin
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**Automation**: automation, workflow, scripting, robot, trigger, integration
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**Game Development**: game, unity, unreal, godot, threejs, 2d, 3d, physics
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**Data Science**: data, analytics, pandas, numpy, statistics, visualization
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## Customization
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### Add Custom Keywords
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Edit [`tools/scripts/auto_categorize_skills.py`](../../tools/scripts/auto_categorize_skills.py):
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```python
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CATEGORY_KEYWORDS = {
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'your-category': [
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'keyword1', 'keyword2', 'exact phrase', 'another-keyword'
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],
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# ... other categories
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}
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```
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Then re-run:
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```bash
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python tools/scripts/auto_categorize_skills.py
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python tools/scripts/generate_index.py
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```
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## Troubleshooting
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### "Failed to categorize" Skills
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Some skills may be too generic or unique. You can:
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1. **Manually set category** in the skill's frontmatter:
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```yaml
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category: your-chosen-category
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```
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2. **Add keywords** to CATEGORY_KEYWORDS config
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3. **Move to folder** if it fits a broader category:
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```
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skills/backend/my-new-skill/SKILL.md
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```
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### Regenerating Index
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After making changes to SKILL.md files:
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```bash
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python tools/scripts/generate_index.py
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```
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This will:
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- Parse frontmatter categories
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- Fallback to folder structure
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- Generate new skills_index.json
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- Copy to apps/web-app/public/skills.json
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## Next Steps
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1. **Test in web app**: Try the improved category filter
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2. **Add missing keywords**: If certain skills are still uncategorized
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3. **Organize remaining uncategorized skills**: Either auto-assign or manually review
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4. **Monitor growth**: Use reports to track new vs categorized skills
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---
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**Result**: Much cleaner category filter with smart, meaningful organization! 🎉
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