Hasn't this been largely solved by auto-caching introduced recently by Anthropic, where you pass "cache_control": {"type": "ephemeral"} in your request and it puts breakpoints automatically? https://platform.claude.com/docs/en/build-with-claude/prompt...

Looking at my own usage with claude code out of the box and nothing special around caching set up. For this month according to ccusage I have in tokens 0.2M input, 0.6M output, 10M cache create, 311M cache read for 322M total tokens. Seems to me that it caches out of the box quite heavily, but if I can trim my usage somehow with these kind of tools I'd love to know.

This is not about caching things for stuff that others built, it’s solely to modify code that you’re writing that will use Anthropic’s API endpoints.

Yes, it has, this is a non-problem, and even if it was a problem, an MCP server would most definitely be one of the worst ways to fix it.

It is answered in the FAQ.

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There are was a Kaggle competition on Defences against Adversarial attacks by Google Brain for NIPS 2017 https://www.kaggle.com/c/nips-2017-defense-against-adversari...

For nice looking basic statistics of your dataset the pandas-profiling library will do the trick https://github.com/JosPolfliet/pandas-profiling

For nice looking basic statistics of your dataset the pandas-profiling library will do the trick https://github.com/JosPolfliet/pandas-profiling