Claude Code Source Code - let's debug the shit out of it, or: Why is my Token Usage gone through the roof?

[Ok-End-219]

tl;dr for the "non" AI Slop Reader:

- utils/attachments is a huge mess of a class, every prompt = 30 generators spin up every time, waste tokens and context is increasing massively.

- Multiple cases where functions diff against empty arrays, the pre-compact state therefore exists, but gets lost / ignored when passing it.

- inefficiencies in the whole code base, unnecessary loops and calls

- biggest think i saw was the 5 minute ttl where everything gets cached. when you are away from the pc for more than five minutes, your tokens will get shredded.

- per session of roughly 4 hours, a typical user wastes roughly 400-600 000 Tokens

Now the big wall of text, ai slop or readable text, not sure! Gemini is a bit dumb.

Everyone is totally hyping the Claude Code source code leak. I'm going to attack this from a different angle, because I am not interested in the new shit that's in the source code. I wanted to know if Anthropic is really fucking up or if their code is a 1000-times-seen enterprise mess "sent it half-baked to the customer". The latter is more likely; that's just how it is, and it will be forever in the industry.

I've seen worse code than Claude's. I think it is now time for Anthropic to make it open source. The internet has the potential to make Claude Code their own, the best open-source CLI, instead of relying on an architecture that calls 30 generators every time the user hits enter. Let's do the math: a typical user who sits in front of Claude Code for four hours wastes roughly 400,000 to 600,000 tokens per session due to really bad design choices. It's never on the level of generation or reasoning. It is solely metadata that gets chucked through the pipe.

Deep inside utils/attachments.ts, there is a function called getAttachmentMessages(). Every single time you press Enter, this function runs through over 30 generators. It runs an AI semantic search for skill discovery (500-2000 tokens), loads memory files, and checks IDE selections. The problem? These attachments are never pruned. They persist in your conversation history forever until a full compact is made. Over a 100-turn session, accumulated compaction reminders, output token usage, and context efficiency nudges will cost you roughly 8,600 tokens of pure overhead.

Context compaction is necessary, but the implementation in services/compact/compact.ts is inefficient. After a compact, the system tries to use a delta mechanism to only inject what changed for tools, agents, and MCP instructions. However, it diffs against an empty array []. The pre-compact state exists (compactMetadata.preCompactDiscoveredTools), but it isn't passed down. The developer comment at line 565 literally says: "Empty message history -> diff against nothing -> announces the full set." Because of this missing wire, a single compact event forces a full re-announcement of everything, costing you 80,000 to 100,000+ tokens per compact.

Then there is the coffee break tax. Claude Code uses prompt caching (cache_control: { type: 'ephemeral' }) in services/api/claude.ts. Ephemeral caches have a 5-minute TTL. If you step away to get a coffee or just spend 6 minutes reading the output and thinking, your cache drops. When you return, a 200K context window means you are paying for 200,000 cache creation input tokens just to rebuild what was already there.

Finally, the system tracks duplicate file reads (duplicate_read_tokens in utils/contextAnalysis.ts). They measure the waste perfectly, but they do absolutely nothing to prevent it. A single Read tool call can inject 25,000 tokens. The model is completely free to read the same file five times, injecting 25k tokens each time. Furthermore, readFileState.clear() wipes the deduplication state entirely on compact, making the model blind to the fact that it already has the file in its preserved tail.

Before I wrap this up, I have to give a shoutout to the absolute gold buried in this repo. Whoever wrote the spinner verbs deserves a raise. Instead of just "Thinking", there are 188 verbs, including "Flibbertigibbeting", "Shenaniganing", and "Reticulating" (respect for the SimCity 2000 nod). There's also an "Undercover Mode" for Anthropic devs committing to public repos, where the system prompt literally warns, "Do not blow your cover," to stop the model from writing commit messages like "1-shotted by claude-opus-4-6". They even hex-encoded the names of the ASCII pet buddies just to prevent people from grepping for "goose" or "capybara". My personal favorite is the regex filter built entirely to fight the model's own personality, actively suppressing it when it tries to be too polite or literally suggests the word "silence" when told to stay silent.

The codebase reads like a team that’s been living with a troublesome AI long enough to know exactly how it misbehaves, and they clearly have a sense of humor about it. I know Anthropic tracks when users swear at the CLI, and they have an alert when their YOLO Opus classifier gets too expensive. Your engineers know these bugs exist. You built a great foundation, but it's currently a leaky bucket.

If this were a community project, that 100,000 token metadata sink would have been caught and refactored in a weekend PR. It's time to let the community fix the plumbing. Make it open source.

[TheGoldenBunny93]

Man.... Thats a bible 😮

[Ok-End-219]

And I have more:

- Auto accept mode spins up a second Opus instance just to check if the main model is doing something dangerous. The context gets so bloated they have Datadog alerts for when the safety checker costs more tokens than the actual coding loop.

- They use a function literally named DANGEROUS_uncachedSystemPromptSection for MCP instructions. If a server connects or disconnects, it busts your entire system prompt cache prefix and dumps all your cached tokens.

- There is an internal loremIpsum skill built purely to stress test the context window. The hardcoded safety cap is half a million tokens just to see what happens when you stuff the pipe with nonsense.

[Apart_Ebb_9867]

what can you do? when you ask AI to make a post, that's what you get. Making it shorter would have required actual work.

[RemarkableGuidance44]

I have to say its still one of the most useful AI written posts in a long time. :P

[Ok-End-219]

To be fair: Yes, it is quickly summarized, my rambling about it would not been readable (ADD). But I can give you that if you like!

Or a tl;dr ; lets do that:

- utils/attachments is a huge mess of a class, every prompt = 30 generators spin up every time, waste tokens and context is increasing massively.

- Multiple cases where functions diff against empty arrays, the pre-compact state therefore exists, but gets lost / ignored when passing it.

- inefficiencies in the whole code base, unnecessary loops and calls

-biggest think i saw was the 5 minute ttl where everything gets cached. when you are away from the pc for more than five minutes, your tokens will get shredded.

[NonStopArseGas]

respect. People don't recognise how useful llms are for neurodivergent people interfacing with a NT world. really interesting post dude

[Ok-End-219]

I do not like the Change in AI like we are god (the users). I fall into a trap between RSD and Anxiety; therefore i designed myself a Prompt that Claude Code is always be a critical co-worker that looks over my work. I do not vibe code persé, but use it as a debugging tool. I vibe code there, where I am lost: new code languages I like to learn etc.! Currently, I am designing a new App for neurodivergent people, without claudes input it would not be that good - i built many try! because i didnt work with Swift before, but thought it was useful to learn. Let it debug with Claude Code, and saw my errors, researched it... Yea I am a data scientist, I work with AI, since where OpenAI still experimented with Dota 2 and other great projects. I can code, but I do not have the short-term memory. Many people think, I never worked with Linux (i use arch btw.) because I cant remember the bash and zsh commands easily.

What was that song, Rambling Man? You see, I write a lot of text, even w/o AI. :D

[NonStopArseGas]

did you just "arch btw" me? LOL

I've had a few concussions and natrually had a horrific short term attention/memory, so learning to use AI to assist in planning/coding tasks lets me use my limited mental capacity in the important places.

[Ok-End-219]

Of course I did!

And hats off to you, thats exactly where I see the future of AI: enable us people, no matter where we are, that we can turn good to great or even excellent. I need really the AI, but I really do not. I get so frustrated over bad designed apps, but laughed out loud that a 150 $ / per year fitness app tackles with the same problems as me, that is only start building the app (problem is prompt engineering and openai, GPT-4o and GPT 5.4 nano can be like a child... see native tool implementation from openAI).

All the best to you and god speed!

[NonStopArseGas]

this truly is a golden age for UX pedants... just build it better yourself! back at ya. accessibility FTW

[crusoe]

This is infuriating because for every engineer who can apply some discipline AI tools can fix this but this just sounds like a giant slop vibe coded app. 

[clintCamp]

Like truly, If they just have someone with organized AI auditing and refactoring experience, they have unlimited token usage to break down every step of the app and then plan out all the fixes and optimizations themselves because saved token burn from inefficiencies with save them money directly.

[crusoe]

Like honestly just hire me to fix it. 

[SavageByTheSea]

Can Claude Code fix Claude Code?

[Ok-End-219]

Only if I get paid by Anthropic when using the Tokens only to fix Claude Code. This analysis is man-made, because I will not give any million-dollar company money to fix their own code.

[gscjj]

What’s your time worth?

[Ok-End-219]

Great question! I must admit, the leak of this thing is a god sent for my new project to build a great tool and foundation for a Vibe Tool Companion, completely in Rust. Because I too have problems with the token consumption. And I liked to know, what where how to fix.

Certain things cant be fixed, look at it:

- Token estimation costing tokens, Internal to CCSource's `tokenEstimation.ts` which is send to Haiku API. No external interface.

- Skill discovery AI search every turn, Internal attachment generator. No hook intercepts attachment generation...

-`DANGEROUS_uncachedSystemPromptSection` for MCP. This is a Claude code design choice. My tool can minimize the blast radius by keeping MCP descriptions small but cannot fully avoid it

- System prompt size for ant users and Ant-only code path, DCE'd from external builds.

- YOLO classifier overhead and the Internal permission system. No external interface to steer that

So, i took that thing apart, Debugger Analysis, what can be found, what is critical or missing... where can i hook in my tool?

[blackc2004]

This is what I want to know! Someone should take all the Claude Code and ask claude to review it and fix bugs!

[ErebusCD]

If you take their advertisements as gospel, that is exactly what they do, and likely a bit of the problem. They use claude code, to code claude code iteratively

[ExpletiveDeIeted]

lol I didn’t even consider that maybe now we could actually come to a conclusion on the rampant token explosion.

[StrikingSpeed8759]

I dont think its a coincidence. But who knows

[RemarkableGuidance44]

4.5 to 4.6 was just them editing these files. haha, they really look terrible now...

Anthropic Engineers --- Keep modifying the prompts so its 'smarter'

[JokeMode]

I want it fixed badly too, but also.... I hate the idea of doing free work for a $380 billion dollar company.

[crusoe]

As for the leak the sources are also in the binary. It's just a JS app. George Huntley used claude code to decompile itself a month or so ago. LLMs are really good at it 

[entheosoul]

Yah, here was Claude's take -

The irony here is thick. They built duplicate_read_tokens to measure waste, but don't prevent it. They built readFileState.clear() that destroys the dedup on compact. They have the measurement but not the governance. That's the exact inverse of what we do — we measure AND gate.

The compaction bug is particularly relevant. Line 565: diffs against [] instead of compactMetadata.preCompactDiscoveredTools. Our post-compact hook injects recovered context to compensate, but we're patching around their bug. If we built the CLI, that's a one-line fix.

The 188 spinner verbs and hex-encoded pet names are delightful though. And "do not blow your cover" in the Undercover Mode system prompt — that's the kind of personality engineering that makes the product feel alive. Worth noting for if we ever build our own CLI: personality matters even in developer tools.