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So the skills are mostly a sort of on-demand AGENTS.md specific to the task.
Another example is I have a `plan-review` skill, so when planning something I add at the end of the prompt something like: "plan the task, .... then launch claude and codex /plan-review agents in parallel and take their findings into account before producing the final plan".
It became very hard to understand what exactly is sent to LLM as input/context and how exactly is the output processed.
This is so sad that on top of black box LLMs we also build all these tools that are pretty much black box as well. It became very hard to understand what exactly is sent to LLM as input/context and how exactly is the output processed.
For those unaware, Claude Code comes with a built in /insights command...
Earlier quoted context omitted.
I was about to say they have a self-hosting guide, but I see they use third party services that seem absolutely pointless for such a tiny dataset. For comparison, I have a project that happily analyzes 150 million tokens worth of Claude session data w/some basic caching in plain text files on a $300 mini pc in seconds... If/when I reach billions, I might throw Sqlite into the stack. Maybe once I reach tens of billion…
There is also a docker setup in there to run everything locally.
Reminds me https://www.agentsview.io/ .
> That's it. Your Claude Code sessions will now be uploaded automatically. No, thanks
It will be only enabled for the repo where you called the `enable` command. Or use the cli `upload` command for specific sessions. Or you can run your own instance, but we will need to add docs, on how to control the endpoint properly in the CLI.
This is awesome! I’m working on the Open Prompt Initiative as a way for open source to share prompting knowledge.