feat(index): add explainable auto-categorization in generate_index (#230)
* Add script to generate skills index from markdown files This script generates an index of skills from markdown files in a specified directory, inferring categories and extracting metadata. * chore: sync generated registry files [ci skip] * Add unit tests for category inference functions * chore: sync generated registry files [ci skip] * Add Smart Auto-Categorization Guide Added comprehensive guide for smart auto-categorization of skills, detailing the process, current status, category distribution, and usage instructions. * chore: sync generated registry files [ci skip] * chore: update star history chart --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: sck_0 <samujackson1337@gmail.com>
This commit is contained in:
Munir Abbasi
GitHub
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# 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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`tools/scripts/generate_index.py` now classifies skills at index-build time and writes two explainability fields to every record in `skills_index.json`:
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- `category_confidence` (numeric confidence score)
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- `category_reason` (how the category was selected)
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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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- 11 primary categories
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- Categories sorted by skill count (most first)
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## Category Distribution
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| Category | Count | Examples |
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|----------|-------|----------|
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| Backend | 164 | Node.js, Django, Express, FastAPI |
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| Web Development | 107 | React, Vue, Tailwind, CSS |
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| Automation | 103 | Workflow, Scripting, RPA |
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| DevOps | 83 | Docker, Kubernetes, CI/CD, Git |
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| AI/ML | 79 | TensorFlow, PyTorch, NLP, LLM |
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| Content | 47 | Documentation, SEO, Writing |
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| Database | 44 | SQL, MongoDB, PostgreSQL |
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| Testing | 38 | Jest, Cypress, Unit Testing |
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| Security | 36 | Encryption, Authentication |
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| Cloud | 33 | AWS, Azure, GCP |
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| Mobile | 21 | React Native, Flutter, iOS |
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| Game Dev | 15 | Unity, WebGL, 3D |
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| Data Science | 14 | Pandas, NumPy, Analytics |
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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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When no known keyword category matches, the index builder derives a dynamic category from the skill id tokens. This keeps the system open-ended and allows new categories without maintaining a fixed allow-list.
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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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### Build index with explainable auto-categorization
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```bash
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python tools/scripts/generate_index.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 count: "Backend (164)" "Web Development (107)"
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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. Backend (164)
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3. Web Development (107)
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4. Automation (103)
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5. DevOps (83)
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6. AI/ML (79)
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7. ... more categories ...
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8. Uncategorized (126) ← 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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---
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**Result**: Much cleaner category filter with smart, meaningful organization! 🎉
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284
skill_categorization/tools/scripts/generate_index.py
Normal file
284
skill_categorization/tools/scripts/generate_index.py
Normal file
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import os
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import json
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import re
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import sys
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import yaml
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from _project_paths import find_repo_root
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# Ensure UTF-8 output for Windows compatibility
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if sys.platform == 'win32':
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import io
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sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
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sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8')
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CATEGORY_KEYWORDS = {
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"web-engineering": [
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"react", "vue", "angular", "svelte", "nextjs", "tailwind", "frontend",
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"html", "css", "browser", "web", "dom", "accessibility", "seo",
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],
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"backend": [
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"backend", "api", "server", "fastapi", "django", "flask", "express",
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"spring", "node", "golang", "rust", "php", "laravel",
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],
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"database": [
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"database", "sql", "postgres", "mysql", "mongodb", "redis", "dynamodb",
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"orm", "schema", "query",
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],
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"ai-ml": [
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"llm", "gpt", "ai", "machine learning", "deep learning", "pytorch",
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"tensorflow", "embedding", "rag", "transformer", "model",
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],
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"cloud-devops": [
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"docker", "kubernetes", "k8s", "ci/cd", "github actions", "terraform",
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"ansible", "aws", "azure", "gcp", "deployment", "devops", "serverless",
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],
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"security": [
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"security", "owasp", "audit", "vulnerability", "threat", "penetration",
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"authentication", "authorization", "jwt", "oauth", "compliance",
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],
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"testing-qa": [
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"test", "testing", "pytest", "jest", "cypress", "playwright", "quality",
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"regression", "coverage", "e2e",
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],
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"mobile": [
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"android", "ios", "react native", "flutter", "swift", "kotlin", "mobile",
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],
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"data-engineering": [
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"etl", "pipeline", "airflow", "spark", "warehouse", "analytics", "data",
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],
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"research": [
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"research", "manuscript", "systematic review", "meta-analysis", "grade",
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"consort", "prisma", "study",
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],
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"bioinformatics": [
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"genomics", "proteomics", "rna", "sequencing", "variant", "phylogenetics",
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"biopython", "single-cell", "biomedical",
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],
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"geospatial": [
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"geospatial", "gis", "spatial", "remote sensing", "raster", "vector",
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],
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"finance": [
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"finance", "trading", "portfolio", "risk", "market", "economic", "treasury",
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],
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}
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STOPWORD_TOKENS = {
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"skill", "skills", "tool", "tools", "builder", "expert", "guide", "workflow",
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"workflows", "system", "systems", "analysis", "integration", "development",
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"testing", "management", "engineer", "engineering", "automation", "framework",
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"advanced", "modern", "official", "pro", "expert", "starter", "setup", "patterns",
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"using", "with", "for", "and", "the", "a", "an", "v2", "v3", "ts", "py", "dotnet",
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}
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def normalize_category(value):
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"""Normalize category values to lowercase kebab-case."""
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if value is None:
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return None
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text = str(value).strip().lower()
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if not text:
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return None
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text = text.replace("_", "-")
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text = re.sub(r"\s+", "-", text)
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text = re.sub(r"[^a-z0-9-]", "", text)
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text = re.sub(r"-+", "-", text).strip("-")
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return text or None
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def infer_dynamic_category(skill_id):
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"""
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Infer a category dynamically from skill id tokens.
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This allows new categories without a fixed allow-list.
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"""
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raw_tokens = [
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token for token in re.split(r"[^a-z0-9]+", skill_id.lower()) if token
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]
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tokens = [token for token in raw_tokens if token not in STOPWORD_TOKENS and len(token) >= 3]
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if len(tokens) >= 2 and tokens[0] in {
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"azure", "aws", "google", "github", "gitlab", "slack", "discord", "shopify",
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"wordpress", "odoo", "notion", "expo", "react", "nextjs", "kubernetes",
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}:
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category = normalize_category(f"{tokens[0]}-{tokens[1]}")
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if category:
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return category, 0.42, f"derived-from-id-prefix:{tokens[0]}-{tokens[1]}"
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if tokens:
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category = normalize_category(tokens[-1])
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if category:
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return category, 0.34, f"derived-from-id-token:{tokens[-1]}"
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return "general", 0.20, "fallback:general"
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def infer_category(skill_info, metadata, body_text):
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"""Infer category, confidence, and reason with deterministic priority rules."""
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explicit_category = normalize_category(metadata.get("category"))
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parent_category = normalize_category(skill_info.get("category"))
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if explicit_category and explicit_category != "uncategorized":
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return explicit_category, 1.0, "frontmatter:category"
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if parent_category and parent_category != "uncategorized":
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return parent_category, 0.95, "path:folder"
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combined_text = " ".join(
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[
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str(skill_info.get("id", "")),
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str(skill_info.get("name", "")),
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str(skill_info.get("description", "")),
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body_text,
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]
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).lower()
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best_category = None
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best_score = 0
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best_hits = []
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for category, keywords in CATEGORY_KEYWORDS.items():
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score = 0
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hits = []
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for keyword in keywords:
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if re.search(r"\\b" + re.escape(keyword) + r"\\b", combined_text):
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score += 3
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hits.append(keyword)
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elif len(keyword) >= 5 and keyword in combined_text:
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score += 1
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hits.append(keyword)
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if score > best_score:
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best_category = category
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best_score = score
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best_hits = hits
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if best_category and best_score > 0:
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confidence = min(0.92, 0.45 + (0.05 * best_score))
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reason_hits = ",".join(best_hits[:3]) if best_hits else "keyword-match"
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return best_category, round(confidence, 2), f"keyword-match:{reason_hits}"
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return infer_dynamic_category(str(skill_info.get("id", "")))
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def parse_frontmatter(content):
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"""
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Parses YAML frontmatter, sanitizing unquoted values containing @.
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Handles single values and comma-separated lists by quoting the entire line.
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"""
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fm_match = re.search(r'^---\s*\n(.*?)\n---', content, re.DOTALL)
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if not fm_match:
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return {}
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yaml_text = fm_match.group(1)
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# Process line by line to handle values containing @ and commas
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sanitized_lines = []
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for line in yaml_text.splitlines():
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# Match "key: value" (handles keys with dashes like 'package-name')
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match = re.match(r'^(\s*[\w-]+):\s*(.*)$', line)
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if match:
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key, val = match.groups()
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val_s = val.strip()
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# If value contains @ and isn't already quoted, wrap the whole string in double quotes
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if '@' in val_s and not (val_s.startswith('"') or val_s.startswith("'")):
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# Escape any existing double quotes within the value string
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safe_val = val_s.replace('"', '\\"')
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line = f'{key}: "{safe_val}"'
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sanitized_lines.append(line)
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sanitized_yaml = '\n'.join(sanitized_lines)
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try:
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return yaml.safe_load(sanitized_yaml) or {}
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except yaml.YAMLError as e:
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print(f"⚠️ YAML parsing error: {e}")
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return {}
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def generate_index(skills_dir, output_file):
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print(f"🏗️ Generating index from: {skills_dir}")
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skills = []
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for root, dirs, files in os.walk(skills_dir):
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# Skip .disabled or hidden directories
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dirs[:] = [d for d in dirs if not d.startswith('.')]
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if "SKILL.md" in files:
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skill_path = os.path.join(root, "SKILL.md")
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dir_name = os.path.basename(root)
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parent_dir = os.path.basename(os.path.dirname(root))
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# Default values
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rel_path = os.path.relpath(root, os.path.dirname(skills_dir))
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# Force forward slashes for cross-platform JSON compatibility
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skill_info = {
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"id": dir_name,
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"path": rel_path.replace(os.sep, '/'),
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"category": parent_dir if parent_dir != "skills" else None, # Will be overridden by frontmatter if present
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"category_confidence": None,
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"category_reason": None,
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"name": dir_name.replace("-", " ").title(),
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"description": "",
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"risk": "unknown",
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"source": "unknown",
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"date_added": None
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}
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try:
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with open(skill_path, 'r', encoding='utf-8') as f:
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content = f.read()
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except Exception as e:
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print(f"⚠️ Error reading {skill_path}: {e}")
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continue
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# Parse Metadata
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metadata = parse_frontmatter(content)
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body = content
|
||||
fm_match = re.search(r'^---\s*\n(.*?)\n---', content, re.DOTALL)
|
||||
if fm_match:
|
||||
body = content[fm_match.end():].strip()
|
||||
|
||||
# Merge Metadata (frontmatter takes priority)
|
||||
if "name" in metadata: skill_info["name"] = metadata["name"]
|
||||
if "description" in metadata: skill_info["description"] = metadata["description"]
|
||||
if "risk" in metadata: skill_info["risk"] = metadata["risk"]
|
||||
if "source" in metadata: skill_info["source"] = metadata["source"]
|
||||
if "date_added" in metadata: skill_info["date_added"] = metadata["date_added"]
|
||||
|
||||
# Category: prefer frontmatter, then folder structure, then default
|
||||
inferred_category, confidence, reason = infer_category(skill_info, metadata, body)
|
||||
skill_info["category"] = inferred_category or "uncategorized"
|
||||
skill_info["category_confidence"] = confidence
|
||||
skill_info["category_reason"] = reason
|
||||
|
||||
# Fallback for description if missing in frontmatter (legacy support)
|
||||
if not skill_info["description"]:
|
||||
# Simple extraction of first non-header paragraph
|
||||
lines = body.split('\n')
|
||||
desc_lines = []
|
||||
for line in lines:
|
||||
if line.startswith('#') or not line.strip():
|
||||
if desc_lines: break
|
||||
continue
|
||||
desc_lines.append(line.strip())
|
||||
|
||||
if desc_lines:
|
||||
skill_info["description"] = " ".join(desc_lines)[:250].strip()
|
||||
|
||||
skills.append(skill_info)
|
||||
|
||||
# Sort validation: by name
|
||||
skills.sort(key=lambda x: (x["name"].lower(), x["id"].lower()))
|
||||
|
||||
with open(output_file, 'w', encoding='utf-8', newline='\n') as f:
|
||||
json.dump(skills, f, indent=2)
|
||||
|
||||
print(f"✅ Generated rich index with {len(skills)} skills at: {output_file}")
|
||||
return skills
|
||||
|
||||
if __name__ == "__main__":
|
||||
base_dir = str(find_repo_root(__file__))
|
||||
skills_path = os.path.join(base_dir, "skills")
|
||||
output_path = os.path.join(base_dir, "skills_index.json")
|
||||
generate_index(skills_path, output_path)
|
||||
@@ -0,0 +1,59 @@
|
||||
#!/usr/bin/env python3
|
||||
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
sys.path.append(str(Path(__file__).resolve().parents[1]))
|
||||
|
||||
from generate_index import infer_category, normalize_category
|
||||
|
||||
|
||||
def assert_equal(actual, expected, label):
|
||||
assert actual == expected, f"{label}: expected={expected!r} actual={actual!r}"
|
||||
|
||||
|
||||
def run_tests():
|
||||
category = normalize_category("Cloud DevOps")
|
||||
assert_equal(category, "cloud-devops", "normalize category")
|
||||
|
||||
skill_info = {
|
||||
"id": "secure-api-gateway",
|
||||
"category": "uncategorized",
|
||||
"name": "secure-api-gateway",
|
||||
"description": "Harden OAuth and JWT authentication flows for APIs.",
|
||||
}
|
||||
metadata = {"category": "security"}
|
||||
category, confidence, reason = infer_category(skill_info, metadata, "")
|
||||
assert_equal(category, "security", "frontmatter category")
|
||||
assert_equal(confidence, 1.0, "frontmatter confidence")
|
||||
assert reason.startswith("frontmatter:"), reason
|
||||
|
||||
skill_info = {
|
||||
"id": "kubernetes-rollout-checker",
|
||||
"category": "uncategorized",
|
||||
"name": "kubernetes-rollout-checker",
|
||||
"description": "Validate container rollouts and deployment health.",
|
||||
}
|
||||
metadata = {}
|
||||
category, confidence, reason = infer_category(skill_info, metadata, "")
|
||||
assert_equal(category, "cloud-devops", "keyword category")
|
||||
assert confidence >= 0.5, confidence
|
||||
assert reason.startswith("keyword-match:"), reason
|
||||
|
||||
skill_info = {
|
||||
"id": "vendorx-hyperflux",
|
||||
"category": "uncategorized",
|
||||
"name": "vendorx-hyperflux",
|
||||
"description": "Internal helper without known taxonomy keywords.",
|
||||
}
|
||||
metadata = {}
|
||||
category, confidence, reason = infer_category(skill_info, metadata, "")
|
||||
assert_equal(category, "hyperflux", "dynamic category")
|
||||
assert confidence > 0.0, confidence
|
||||
assert reason.startswith("derived-from-id-token:"), reason
|
||||
|
||||
print("ok")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
run_tests()
|
||||
Reference in New Issue
Block a user