Show HN: Rudel – Claude Code Session Analytics

keks0r 128 points 72 comments March 12, 2026
github.com · View on Hacker News

We built rudel.ai after realizing we had no visibility into our own Claude Code sessions. We were using it daily but had no idea which sessions were efficient, why some got abandoned, or whether we were actually improving over time. So we built an analytics layer for it. After connecting our own sessions, we ended up with a dataset of 1,573 real Claude Code sessions, 15M+ tokens, 270K+ interactions. Some things we found that surprised us: - Skills were only being used in 4% of our sessions - 26% of sessions are abandoned, most within the first 60 seconds - Session success rate varies significantly by task type (documentation scores highest, refactoring lowest) - Error cascade patterns appear in the first 2 minutes and predict abandonment with reasonable accuracy - There is no meaningful benchmark for 'good' agentic session performance, we are building one. The tool is free to use and fully open source, happy to answer questions about the data or how we built it.

Discussion Highlights (20 comments)

lau_chan

Does it work for Codex?

cluckindan

Nice. Now, to vibe myself a locally hosted alternative.

marconardus

It might be worthwhile to include some of an example run in your readme. I scrolled through and didn’t see enough to justify installing and running a thing

152334H

is there a reason, other than general faith in humanity, to assume those '1573 sessions' are real? I do not see any link or source for the data. I assume it is to remain closed, if it exists.

ekropotin

> That's it. Your Claude Code sessions will now be uploaded automatically. No, thanks

emehex

For those unaware, Claude Code comes with a built in /insights command...

vova_hn2

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.

blef

Reminds me https://www.agentsview.io/ .

KaiserPister

This is awesome! I’m working on the Open Prompt Initiative as a way for open source to share prompting knowledge.

alyxya

Why does it need login and cloud upload? A local cli tool analyzing logs should be sufficient.

anthonySs

is this observability for your claude code calls or specifically for high level insights like skill usage? would love to know your actual day to day use case for what you built

mentalgear

How diverse is your dataset?

Aurornis

> 26% of sessions are abandoned, most within the first 60 seconds Starting new sessions frequently and using separate new sessions for small tasks is a good practice. Keeping context clean and focused is a highly effective way to keep the agent on task. Having an up to date AGENTS.md should allow for new sessions to get into simple tasks quickly so you can use single-purpose sessions for small tasks without carrying the baggage of a long past context into them.

dmix

I've seen Claude ignore important parts of skills/agent files multiple times. I was running a clean up SKILL.md on a hundred markdown files, manually in small groups of 5, and about half the time it listened and ran the skill as written. The other half it would start trying to understand the codebase looking for markdown stuff for 2min, for no good reason, before reverting back to what the skill said. LLMs are far from consistent.

longtermemory

From session analysis, it would be interesting to understand how crucial the documentation, the level of detail in CLAUDE.md, is. It seems to me that sometimes documentation (that's too long and often out of date) contributes to greater entropy rather than greater efficiency of the model and agent. It seems to me that sometimes it's better and more effective to remove, clean up, and simplify (both from CLAUDE.md and the code) rather than having everything documented in detail. Therefore, from session analysis, it would be interesting to identify the relationship between documentation in CLAUDE.md and model efficiency. How often does the developer reject the LLM output in relation to the level of detail in CLAUDE.md?

mbesto

So what conclusions have you drawn or could a person reasonably draw with this data?

ericwebb

I 100% agree that we need tools to understand and audit these workflows for opportunities. Nice work. TBH, I am very hesitant to upload my CC logs to a third-party service.

dboreham

One potential reason for sessions being abandoned within 60 seconds in my experience is realizing you forgot to set something in the environment: github token missing, tool set for the language not on the path, etc. Claude doesn't provide elegant ways to fix those things in-session so I'll just exit, fix up and start Claude again. It does have the option to continue a previous session but there's typically no point in these "oops I forgot that" cases.

bool3max

Why is the comment calling out the biggest issue with this so heavily downvoted? Privacy is a massive concern with this.

smallerfish

> content, the content or transcript of the agent session Does this include the files being worked on by the agent in the session, or just the chat transcript?

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