| name | technical-blog-search |
| description | Use when searching for technical blog posts, tutorials, or explanatory articles about a research or engineering topic. Triggers when user asks to find blog posts, tutorials, write-ups, or practical explanations beyond academic papers. |
Technical Blog Search
Search for high-quality technical blog posts and tutorials via web search.
Priority Sources
Search these sources first — they have consistently high technical quality:
| Source | URL Pattern | Best For |
|---|
| Distill.pub | distill.pub | Deep ML explanations |
| Lil'Log | lilianweng.github.io | ML survey posts |
| Hugging Face Blog | huggingface.co/blog | NLP/transformers |
| Google AI Blog | ai.googleblog.com | Google research |
| OpenAI Blog | openai.com/blog | OpenAI research |
| Papers With Code | paperswithcode.com | ML benchmarks |
| Towards Data Science | towardsdatascience.com | Practical ML |
| The Gradient | thegradient.pub | ML commentary |
| Sebastian Ruder | ruder.io | NLP deep dives |
Search Queries
Google Web Search Format
site:lilianweng.github.io [TOPIC]
site:distill.pub [TOPIC]
[TOPIC] tutorial explained site:towardsdatascience.com
[TOPIC] "how it works" -arxiv
[TOPIC] implementation guide python
General Search Patterns
[TOPIC] explained intuitively
[TOPIC] from scratch tutorial
[TOPIC] deep dive blog post
[TOPIC] visual explanation
Evaluation Criteria
| Signal | What to Check |
|---|
| Author credentials | Researcher/engineer at known org |
| Depth | Technical detail, math, code examples |
| Recency | Publication date (prefer <2 years) |
| Engagement | Comments, shares, citations |
| Code samples | Runnable examples increase quality |
Output Format
## Technical Blogs: [Topic]
### Blog 1: [Post Title](URL)
- **Source:** [Site Name] | **Author:** [Name] | **Date:** [Year-Month]
- **Summary:** [2-3 sentences on what it covers]
- **Key insights:** [Main takeaways, unique perspective]
- **Relevance:** [Why useful for the task]
### Blog 2: ...
Search Tips
- Start with known high-quality sources before general search
- Search for "[PAPER TITLE] explained" to find blog summaries of key papers
- Look for "annotated" versions (e.g., "The Annotated Transformer")
- Check author's other posts once you find a good author
- Reddit r/MachineLearning and r/learnmachinelearning often link quality posts
Common Mistakes
- Trusting low-quality Medium posts with no technical depth
- Missing Distill.pub/Lil'Log — these are often the best explanations
- Not checking post date — outdated tutorials can mislead
