About knowledge-space

Curated technical knowledge base: 785+ dense reference articles across 26 domains. Agent-first format with wiki-links, gotchas, runnable code. Not tutorials — verified references for AI agents and engineers.

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Happyin Knowledge Space

A curated technical reference across 26 domains — Kafka, Python, SQL, ML, security, image generation, and more — written so AI agents and engineers get dense, runnable answers instead of tutorial prose.

We built it because agents kept confidently hallucinating API flags, version-specific behavior, and config options. Point your Claude, Cursor, or any RAG pipeline at this repo and it gets a reliable source to check against.

834+ articles | 26 domains | 3987+ cross-references

What's inside

Domain	Articles	Coverage
`image-generation/`	58	Diffusion models, flow matching, LoRA training, inpainting, tiled inference
`llm-agents/`	57	RAG, fine-tuning, agent frameworks, prompt engineering, multi-agent
`security/`	56	Web security, pentesting, Active Directory, anti-fraud, model protection, CWE
`data-science/`	56	ML, statistics, neural networks, CV, NLP, math foundations
`kafka/`	43	Broker internals, consumers, producers, Streams, KSQL, Connect, replication
`devops/`	38	Docker, Kubernetes, Terraform, CI/CD, monitoring, SRE, observability
`web-frontend/`	36	React, TypeScript, CSS, Figma, bundlers, accessibility, JS async
`data-engineering/`	34	ETL/ELT, Spark, Airflow, data warehouses, streaming, CDC, vector search
`algorithms/`	33	Sorting, graphs, DP, data structures, complexity analysis
`architecture/`	33	Microservices, DDD, system design, API patterns, CQRS
`sql-databases/`	33	PostgreSQL, MySQL, query optimization, migrations, indexing, advanced
`python/`	33	Core language, FastAPI, Django, async, testing, stdlib, web scraping
`ios-mobile/`	31	SwiftUI, Swift, Android/Kotlin fundamentals, mobile ML
`linux-cli/`	27	Shell scripting, filesystem, systemd, permissions, networking
`cpp/`	27	Modern C++, memory, templates, concurrency, cross-platform ML
`java-spring/`	25	Spring Boot, JPA, microservices, Kotlin, Android
`seo-marketing/`	24	Technical SEO, keyword research, link building, AI-driven SEO
`bi-analytics/`	23	Tableau, Power BI, SQL analytics, dashboards, product analytics
`testing-qa/`	23	Selenium, Playwright, API testing, CI integration, browser automation
`rust/`	22	Ownership, lifetimes, async, error handling, unsafe
`nodejs/`	16	Event loop, streams, clusters, performance, design patterns
`php/`	15	Laravel, MVC, ORM, testing, PHP 8 features
`llm-memory/`	13	Memory architectures, session persistence, knowledge graphs
`audio-voice/`	11	TTS, ASR, voice cloning, speech synthesis, TTS fine-tuning
`writing/`	9	Technical article structure, SEO for articles, LLM anti-patterns
`go/`	9	Goroutines, channels, modules, HTTP servers, microservices

For AI agents

Quick access via sandbox

Upload the repo into a ConTree sandbox (or any other isolated environment you prefer) and query it via MCP tools - search, read, and analyze articles:

# Upload to ConTree sandbox
contree upload --path ./docs

# Search across all domains
contree search "kafka consumer rebalancing"

# Read specific article
contree read docs/kafka/consumer-groups.md

Direct file access

Clone and point your agent at it:

git clone https://github.com/AnastasiyaW/knowledge-space.git

Each article is a standalone .md file - easy to index, retrieve, and inject into LLM context. Articles cross-reference each other with [[wiki-links]] forming a navigable knowledge graph.

Article format

Every article follows a consistent structure optimized for machine consumption:

# Consumer Groups

## Key Facts
- Bullets with [[wiki links]]

## Patterns
[Code. Configs. Commands. Runnable.]

## Gotchas
[symptom -> cause -> fix]

## See Also
[Cross-references + official docs]

Freshness policy

Not all knowledge ages equally. Each domain has an update cycle:

Cycle	Domains
Stable (fundamentals)	Algorithms, Architecture, Linux CLI
Yearly	SQL, Kafka, Rust, Java/Spring, PHP, Node.js, Testing, BI, Data Engineering
Every 6 months	Web Frontend, DevOps, LLM/RAG, iOS, Security, SEO
Monthly	Image Generation, Agent Frameworks

Articles include version context where relevant (e.g., "PostgreSQL 17", "React 19").

Contributing

We accept contributions from both AI agents and humans. See CONTRIBUTING.md for the full guide.

Quick version:

Fork the repo
Create/update an article in docs/{domain}/
Follow the article format (dense reference, not tutorial)
Submit a PR

For agents submitting findings

If you're an agent that discovered outdated or missing information:

Branch: update/{domain}/{topic-slug}
Format: follow the article structure above - compress, no filler
PR: include what changed, why, and source links
Forbidden: course names, instructor names, tutorial prose, marketing language

Automated validation checks run on every PR.

License

MIT

knowledge-space