Listsome

A platform for sharing DIY projects and recipes with the maker community.

Introduction
Project Goals & Values
Architectural Overview
Content Sharing Pipeline
Federation Model
Technical Implementation
Development Roadmap

Introduction

Listsome is a content sharing and documentation platform designed for indie web makers and creators. Instead of being “listless” (without energy or purpose), you’re “listsome” - actively documenting and sharing the things you create. Whether it’s a woodworking project, a new recipe, or an electronics build, Listsome helps you share what you’ve done so others can learn from your experience.

Think of it as:

A recipe box for all your DIY projects, not just food
A portfolio for makers who build things
A how-to wiki written by people who actually did the thing
Your project’s documentation that others can follow

Project Goals & Values

Core Values

Indie Web First

Content creators maintain ownership and control of their work
No platform lock-in - content lives on creator’s own sites
Support for indie web standards (microformats, WebMention, etc.)
Respect for creator autonomy and data sovereignty

Anti-Big Tech

Avoid dependency on FAANG services (AWS, GCP, etc.)
Use open source alternatives wherever possible
Support self-hosting and homelab deployment
Build with privacy-first principles

Accessibility & Inclusion

Deployable on modest hardware (Raspberry Pi, old laptops)
Low resource requirements for participation
Support for creators with limited technical resources
Progressive enhancement for all users

Community-Driven

Open source development model
Community curation and moderation
Transparent algorithms and processes
Collaborative improvement of discovery mechanisms

Primary Goals

Enhance Discoverability: Help indie web creators reach new audiences without leaving their platforms
Preserve Creator Control: Aggregate and enhance without appropriating or displacing original content
Build Community: Foster connections between makers, learners, and creators across the indie web
Democratize Access: Make sophisticated content discovery accessible to anyone with basic hardware
Support Federation: Enable multiple hub instances to work together while maintaining independence

Architectural Overview

High-Level Architecture

The Listsome platform operates as a content sharing and documentation service with three primary layers:

Discovery Layer: Finds and ingests content from distributed sources
Processing Layer: Parses, enriches, and curates discovered content
Distribution Layer: Provides enhanced discovery interfaces and federation capabilities

Technology Stack

Core Runtime

Language: Rust (performance, safety, single-binary deployment)
Web Framework: Axum (async, composable, well-maintained)
Database: SQLite (currently), PostgreSQL (planned)
Search: Full-text search (planned, Tantivy)

Frontend

Framework: Leptos (Rust-based, SSR)
Styling: Plain CSS
Markdown: Integrated editor with live preview (planned)

Content Processing (Planned)

Microformats: h-recipe, h-entry parsing
JSON-LD: Schema.org HowTo/Recipe structured data

Federation & Standards

ActivityPub: ActivityPub endpoints (partial)
WebFinger: Instance discovery (partial)
RSS/Atom: Feed generation and consumption

Deployment

Containerization: Docker with multi-arch builds (x86_64, ARM64) (planned)
Single Binary: Embedded assets, SQLite database, zero dependencies
CI/CD: Codeberg Actions (planned)

System Components

Content Discovery

WebMention endpoint for indie web integration
RSS/Atom feed crawler with intelligent scheduling
ActivityPub listener for fediverse content
Manual submission interface for community curation
Microformats parser for structured content detection

Content Processing Pipeline

Multi-stage parsing (structured → semi-structured → unstructured)
Confidence scoring for parsing quality assessment
Content enrichment (difficulty, time estimates, tags)
Duplicate detection and content deduplication
Image extraction and optimization

Data Storage

Metadata database (PostgreSQL/SQLite)
Full-text search index (Tantivy)
Content cache (summaries, images, metadata)
Analytics database (privacy-friendly, aggregated only)

User Interfaces

Web discovery interface (browse, search, filter)
RSS/JSON feeds (filtered streams, custom collections)
Embed widgets (for integration with other sites)
Mobile PWA (offline reading, responsive design)

Federation Network

ActivityPub server (share discoveries, follow creators)
WebHook system (real-time notifications)
Bridge integrations (Discord, Slack, etc.)
Hub-to-hub federation (distributed network)

Content Discovery Pipeline

Discovery Methods

WebMention Integration

Creators send webmentions when publishing new content
Automatic validation and processing of mentioned content
Support for indie web reply/like/repost interactions
Backfeed social interactions to original content

RSS/Atom Crawling

Intelligent scheduling based on publication frequency
Support for full-content and summary feeds
Automatic discovery of new feeds through OPML and link following
Respect for robots.txt and rate limiting

ActivityPub Listening

Monitor fediverse hashtags (#diy, #maker, #tutorial)
Process shared links and content from Mastodon, Lemmy, etc.
Federate discoveries back to the network
Support for ActivityPub collections and featured content

Manual Submission

Community-driven content submission
Verification and quality control processes
Batch processing for content creators
API for programmatic submission

Content Parsing Strategy

Tier 1: Structured Data (90-95% confidence)

#![allow(unused)]
fn main() {
// Microformats (h-recipe, h-entry)
<article class="h-entry">
  <h1 class="p-name">Project Title</h1>
  <div class="e-content">...</div>
</article>

// JSON-LD Schema.org
{
  "@type": "HowTo",
  "name": "Project Title",
  "instruction": [...]
}
}

Tier 2: Semi-Structured HTML (60-80% confidence)

Common blog patterns and CSS selectors
Numbered lists and heading hierarchies
Content area detection algorithms
Heuristic-based extraction

Tier 3: Unstructured Content (30-50% confidence)

Regex pattern matching for steps, materials, tools
Natural language processing for content classification
Machine learning for difficulty and time estimation
Requires human review for quality assurance

Content Enhancement

Automatic Enrichment

Difficulty level assessment based on tools and complexity
Time estimation from step analysis and historical data
Tag generation using content analysis and ML
Image extraction, optimization, and caching
Tool and material standardization

Community Enhancement

Quality voting and community feedback
Collaborative tagging and categorization
Content correction and improvement suggestions
Moderation and spam detection

Federation Model

Hub-to-Hub Federation

Distributed Network

Multiple independent hub instances
Shared content discovery and curation
Distributed moderation decisions
Resilient to single points of failure

ActivityPub Integration

Standard federation protocol
Interoperability with Mastodon, Lemmy, etc.
Custom activity types for instructional content
Rich metadata sharing between instances

Content Syndication

RSS/JSON feed sharing between hubs
Webhook notifications for new discoveries
Collaborative filtering and recommendation
Respect for creator preferences and licensing

Creator Benefits

Increased Discoverability

Content appears in federated timeline
Cross-instance search and discovery
Community-driven promotion and sharing
Analytics on content performance

Maintained Control

Content remains on creator’s platform
Full attribution and backlinks
Creator can request removal at any time
No platform lock-in or content migration

Community Engagement

Cross-platform comments and discussions
Collaborative improvement suggestions
Skill-based networking and connections
Project remixes and derivatives tracking

Technical Implementation

Core Architecture Decisions

Single Binary Deployment

#![allow(unused)]
fn main() {
// Embedded assets and database
// Zero external dependencies
// Configurable via environment variables
// Graceful degradation for limited resources
}

Resource Efficiency