modified	Saturday 9 May 2026

Edited: Saturday 9 May 2026

Hashtags ¶

Hashtags provide flexible, non-hierarchical organization for your knowledge base. Tag pages with topics, themes, or categories, and XLog automatically creates browsable tag collections.

What Are Hashtags? ¶

Hashtags in XLog work like social media tags - prefix any word with # to create a tag:

1This is about #machine-learning and #neural-networks.
2
3I'm exploring #golang and #web-development today.

XLog automatically:

Makes hashtags clickable - Click to see all pages with that tag
Creates tag pages - Aggregate pages by topic
Shows tag counts - See how many pages use each tag

Syntax ¶

Basic Hashtags ¶

Simple one-word tags:

1#python #golang #javascript
2#learning #research #tutorial

Multi-Word Hashtags ¶

Use hyphens for multi-word tags:

1#machine-learning
2#digital-gardening
3#personal-knowledge-management
4#web-development

Spaces don’t work in hashtags - use hyphens instead:

1#knowledge-base  ✅ Works
2#knowledge base  ❌ Only tags "knowledge"

Case Sensitivity ¶

Hashtags are case-insensitive for matching:

1#MachineLearning
2#machine-learning
3#MACHINE-LEARNING

All three are treated as the same tag.

Using Hashtags ¶

In Page Content ¶

Add hashtags anywhere in your markdown:

1# My Research Notes
2
3Today I learned about #transformers in #natural-language-processing.
4
5The #attention-mechanism is key to understanding #bert and #gpt.
6
7Related: #machine-learning #deep-learning

In Frontmatter ¶

You can also define tags in YAML frontmatter:

 1---
 2tags:
 3  - machine-learning
 4  - neural-networks  
 5  - research
 6---
 7
 8# Neural Network Architectures
 9
10Content here...

Both inline hashtags and frontmatter tags work together.

Multiple Tags ¶

Tag with as many topics as relevant:

1# Building a Personal Wiki with XLog
2
3Notes on #xlog #digital-gardening #knowledge-management
4#markdown #static-site-generator #personal-wiki
5
6Tags: #golang #web-development #open-source

Browsing by Tag ¶

Click Any Hashtag ¶

Clicking a hashtag (like #machine-learning) takes you to a tag page showing:

All pages containing that tag
Page titles and excerpts
Tag count (number of tagged pages)

Example tag page:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
#machine-learning (12 pages)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Neural Network Architectures
  Deep learning models for...

Introduction to Transformers
  Attention mechanisms and...

Supervised Learning Basics
  Classification and regression...

Tag Index ¶

XLog can show all tags used across your knowledge base (if configured).

Hashtags vs. Backlinks ¶

Both organize knowledge but serve different purposes:

Aspect	Hashtags	Backlinks
Purpose	Categorization by topic	Connection between specific ideas
Granularity	Broad themes	Specific concepts
Creation	Manual with #	Automatic when mentioning pages
Structure	Flat categories	Network graph
Best for	Finding similar content	Discovering relationships

Example:

1# Attention Mechanisms in Transformers
2
3The [Transformer Architecture](/Transformer_Architecture) uses #attention-mechanisms.
4
5Introduced in [Attention Is All You Need](/Attention_Is_All_You_Need).
6
7Topics: #machine-learning #nlp #deep-learning

Hashtags (machine-learning, nlp) categorize broadly
Backlinks (Transformer Architecture) connect specific concepts

Use Cases ¶

1. Topic Organization ¶

Organize notes by subject:

1# Linear Regression Notes
2
3Basic #statistics and #machine-learning algorithm.
4
5Used for #regression tasks, not #classification.
6
7Learn: #supervised-learning #algorithms

Find all statistics pages, all machine-learning pages, etc.

2. Project Tracking ¶

Track work across projects:

1# API Endpoint Refactoring
2
3Refactor auth endpoints for #project-apollo #backend.
4
5Related work: #api-design #security
6
7Status: #in-progress #Q2-2026

See all project-apollo tasks or all in-progress items.

3. Learning Themes ¶

Track learning areas:

1# React Hooks Deep Dive
2
3Learning about #react #javascript #frontend.
4
5Part of #learning-path-frontend #2026-goals
6
7Difficulty: #intermediate

Browse learning-path-frontend to see your curriculum.

4. Content Type ¶

Mark content types:

1# How to Build a RESTful API
2
3Complete guide to REST APIs.
4
5Type: #tutorial #guide #how-to
6Topics: #api-design #backend #http

Find all tutorial pages or all how-to guides.

5. Status and Workflow ¶

Track page maturity:

1# Neural Network Theory (Draft)
2
3Status: #draft #needs-review #work-in-progress
4
5Once complete: #published #ready

See all draft pages that need finishing.

Organizing Strategies ¶

Multi-Dimensional Tagging ¶

Tag from multiple angles:

1#topic-machine-learning     ← What it's about
2#type-research-note         ← What kind of page
3#status-published           ← Completion status
4#project-thesis             ← Related project
5#difficulty-advanced        ← Complexity level

This creates flexible, multi-faceted organization.

Tag Prefixes ¶

Use prefixes for clarity:

 1#lang-python
 2#lang-javascript
 3#lang-go
 4
 5#topic-algorithms
 6#topic-databases
 7#topic-networking
 8
 9#status-draft
10#status-published
11#status-archived

Prefixes group related tags and make browsing easier.

Hierarchical Tags (Optional) ¶

While hashtags are flat, you can simulate hierarchy with naming:

1#programming
2#programming-languages
3#programming-languages-python
4#programming-languages-python-async

Not enforced by XLog, but useful for personal organization.

Best Practices ¶

1. Be Consistent ¶

Pick tag names and stick with them:

1#machine-learning    ← Consistent
2#ml                  ← Don't mix abbreviations
3#MachineLearning     ← Different case okay, but pick one style

2. Not Too Many, Not Too Few ¶

Too few tags:

1#notes  ← Too broad, not useful

Too many tags:

1#machine #learning #neural #networks #deep #learning #ai #ml #dl
2← Too granular, redundant

Just right:

1#machine-learning #neural-networks #deep-learning
2← Specific enough to be useful

3. Use Tags for Discovery ¶

Tag content you’ll want to find again:

1# Solution to CORS Issues
2
3Quick fix for #troubleshooting #cors #web-development.
4
5Bookmark: #reference #solutions

Later, browse troubleshooting for debugging help.

4. Combine with Backlinks ¶

Use both for powerful organization:

1# React Context API
2
3Discusses [React](/React) state management via #context-api.
4
5Related patterns: [Redux](/Redux), [MobX](/MobX)
6
7Topics: #react #state-management #frontend

Backlinks connect to specific libraries
Hashtags categorize by theme

5. Review and Refactor Tags ¶

Periodically review your tags:

Merge similar tags (ml → machine-learning)
Rename for clarity (proj1 → project-apollo)
Delete unused tags

Tag Performance ¶

Hashtags are lightweight:

Indexed during page rendering
Fast lookup even with thousands of tags
No performance impact on large knowledge bases

Configuration ¶

Hashtags are provided by the hashtags extension (enabled by default).

To disable hashtags:

1xlog -disabled-extensions "hashtags"

(Not recommended - hashtags are essential for organization)

Examples ¶

Personal Wiki ¶

1# Database Indexing Strategies
2
3Exploring #database #performance #optimization techniques.
4
5Types: #b-tree #hash-index #bitmap-index
6
7Related: [SQL Optimization](/SQL_Optimization) [Query Planning](/Query_Planning)
8
9Topics: #postgresql #mysql #database-design

Research Notes ¶

1# Paper: Attention Is All You Need
2
3Seminal #research-paper on #transformers.
4
5Authors: [Vaswani et al.](/Vaswani_et_al.)
6
7Topics: #nlp #deep-learning #attention-mechanisms
8Year: #2017 #papers-2017
9Impact: #highly-cited #foundational

Learning Journal ¶

1# 2026-05-07 - Learning Log
2
3Today: #golang #concurrency #goroutines
4
5Completed: #tutorial #effective-go
6
7Next: #channels #context #patterns
8
9Status: #learning-in-public #100-days-of-code

Project Documentation ¶

1# Authentication Service Architecture
2
3Component: #backend #microservices #authentication
4
5Stack: #golang #jwt #oauth2
6
7Project: #main-platform #api-gateway
8
9Status: #production #v2.0

Tag Naming Conventions ¶

Technical Content ¶

1#lang-python        ← Programming languages
2#tool-docker        ← Tools and software
3#concept-oop        ← Concepts and theory
4#pattern-singleton  ← Design patterns

Personal Knowledge ¶

1#book-atomic-habits     ← Books
2#course-cs50            ← Courses  
3#video-mit-ocw          ← Video series
4#podcast-lex-fridman    ← Podcasts

Status and Workflow ¶

1#todo              ← Action items
2#doing             ← In progress
3#done              ← Completed
4#blocked           ← Waiting on something
5#someday-maybe     ← Backlog

Limitations ¶

No Tag Hierarchy ¶

XLog treats all tags as flat. These aren’t parent-child:

1#programming
2#programming-languages
3#programming-languages-python

You can name them hierarchically, but XLog doesn’t enforce relationships.

No Tag Aliases ¶

Each tag is independent:

1#ml                  ← Different tag
2#machine-learning    ← Different tag

Pick one and be consistent.

No Tag Descriptions ¶

Tags are just labels - no descriptions or metadata. Document tag meanings in an index page:

1# Tag Index
2
3## Project Tags
4- **#project-apollo** - Main web platform
5- **#project-beta** - Mobile app project
6
7## Status Tags
8- **#draft** - Work in progress
9- **#published** - Ready for sharing

Advanced Usage ¶

Create tag navigation pages:

 1# Topic Index
 2
 3## Programming
 4- [#golang](/tags/golang)
 5- [#python](/tags/python)  
 6- [#javascript](/tags/javascript)
 7
 8## Concepts
 9- [#algorithms](/tags/algorithms)
10- [#data-structures](/tags/data-structures)

Dynamic Tag Pages ¶

Tag pages are generated automatically. Bookmark frequently-used ones:

1# Quick Links
2
3- [Machine Learning Notes](/tags/machine-learning)
4- [Ongoing Projects](/tags/in-progress)
5- [Reference Material](/tags/reference)