shanewei

I get the love letter to text thing, but this is almost too bare. Copy-pasting every URL makes it feel like an unfinished apartment.

I'm trying to understand the edge here. How is this different from using a crawler + LLM to fetch a page and extract the metrics? Is the main value coverage/reliability across sites?

This feels less like a broad market and more like a market structure that favors a small number of sophisticated participants.

That makes sense. Maybe the existing VS Code integration is the place to solve part of this for coding workflows: formatted output, artifacts, and search UI all seem useful next to the editor. The Claude.ai conversation corpus/search seems like the part that may need deeper account integration.

What do you miss from the Desktop app that the CLI doesn’t cover? I’m mostly on Linux too and have just been using the CLI, so I’m curious.

My understanding is that it’s mostly an inference-time knob, not different weights.

OpenAI describes reasoning.effort as controlling how many reasoning tokens get used before the answer. Anthropic’s docs are even more explicit that effort trades off thoroughness vs token efficiency “with a single model”.

So I wouldn’t read the Claude Code cache warning as proof that a different model is being used. It may just mean the thinking/effort setting is part of the cache key.

This matches my experience. I am building a small tool on top of DeepSeek, and the low model cost changes the pace a lot. It makes it easier to keep experimenting without turning every iteration into a budget decision.

Congrats to the MySQL team. Nice to see another LTS release.

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Tried it with a PDF, but after upload I didn’t see any response or output. What kinds of PDFs does it handle best, and what’s the advantage over existing PDF-to-Markdown tools?

I like this direction. Seems hard to get right, though.