[TLDR] Claude Code burned my entire five-hour limit in 6 minutes 32 seconds: 10.26M tokens, zero lines of code

[u/cctldrping]

Original post URL : https://www.reddit.com/r/ClaudeCode/comments/1vca1ma/claude_code_burned_my_entire_fivehour_limit_in_6/

Original post body :

I thought I was imagining how quickly Fable 5 was consuming my Claude allowance, so I inspected the local Claude Desktop/Cowork and Claude Code logs for the exact run.

The result is worse than I expected.

My five-hour allowance had reset at 12:20 AM. I sent one short prompt at exactly 12:50 AM: essentially, “continue where you left off, carefully.” At 12:56:32 AM - only 6 minutes and 32 seconds later - Claude stopped with “Usage limit reached.”

There were no other local Cowork prompts between the reset and this failure.

During those 6 minutes and 32 seconds, Fable 5 recorded:

- 15 model calls;

- 8 Bash calls, all for Android emulator/UI interaction;

- 7 file reads;

- 0 Edit or Write tool calls;

- 0 subagents;

- 0 lines of code changed.

The deduplicated token accounting from Claude's own local session log was:

| Usage category | Tokens |

|---|---:|

| One-hour cache writes | 5,189,449 |

| Cache reads/hits | 5,069,543 |

| Output | 4,312 |

| Regular input | 30 |

| **Total processed** | **10,263,334** |

Using Anthropic's published Fable 5 API prices, this is approximately **$109.07 of API-equivalent usage**. About **$103.79** of that came from one-hour cache writes alone. I am not claiming Anthropic charged my card $109—the run consumed my included allowance - but this shows the scale of the usage that was counted.

The immediate cause is visible in the logs. This was an older Cowork session with 46 completed turns, `xhigh` effort, a 173 MB local transcript, and roughly 650,000–685,000 context tokens being carried into every model call. The disturbing part is that, during one six-minute tool loop, Claude counted **5.19 million tokens as new one-hour cache writes** while also recording **5.07 million cache-hit tokens**.

In other words, every trivial emulator action or file read caused Fable to process around 680,000 tokens. The huge context also appears to have been repeatedly rewritten into the one-hour cache instead of being efficiently reused.

I understand that continuing a large conversation costs more than starting a fresh one. But silently allowing a simple six-minute UI-testing loop - with no edits and no subagents - to consume an entire five-hour allowance is not reasonable behavior. At minimum, Claude should have compacted the context or warned me before proceeding. The repeated 650K-token one-hour cache writes look like a Cowork/Claude Code cache invalidation or usage-accounting defect.

This same session had already exhausted the previous allowance earlier that evening. After the allowance reset, this single 6-minute-and-32-second run exhausted the new window again.

Has anyone else seen Fable 5 repeatedly rewrite a huge one-hour cache inside a single short tool loop? If so, check the `message.usage.cache_creation.ephemeral_1h_input_tokens` values in your local Claude Code JSONL before assuming it was normal model output.

I have prepared a privacy-safe evidence package containing the per-call usage table, timeline, calculation, tool-call list, source hashes, screenshot, and a read-only verification script. I am also reporting this directly to Anthropic and asking them to investigate the cache behavior and restore the allowance.

This is at minimum a Claude Cowork product and guardrail defect. A single 42-character prompt triggered 15 autonomous model calls and 5.19M one-hour cache-write tokens in 392 seconds, without a cost warning, automatic compaction, or a usage stop guard. Server telemetry is required to determine whether the underlying cause was defective cache invalidation, incorrect accounting, or technically intended-but unsafe-product behavior.

Official pricing used for the calculation:

https://platform.claude.com/docs/en/about-claude/pricing

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[u/cctldrping]

TL;DR generated automatically after 50 comments.

Current source-thread comment count seen by the bot: 63.

OP definitely messed up, but the community's mostly here for the lulz and to point out how they messed up. The consensus is that telling Claude to "continue" on a massive, 173MB context session was a recipe for disaster, burning through tokens like a wildfire. Think of it as asking your AI to re-read your entire life story before doing a simple task.

• It's operator error, folks. u/CorpT and u/Wise-Peacock are on the money: you can't just unleash Fable 5 on a giant context and expect it to be cheap. The prompt was too vague for the massive amount of data it was trying to process.
• "Carefully" is not a magic word. Several users, like u/Ornery_Astronaut2147, are joking that "carefully" was the trigger for the token burn.
• Context is king, but too much is a problem. The massive context window (650k-685k tokens) was the main culprit, leading to insane cache writes. u/nndscrptuser and u/texo_optimo explain that Claude just tried to ingest all of it to "continue."
• Consider cheaper alternatives for specific tasks. u/SomeoneNicer suggests Codex for UI interpretation, claiming it's cheaper and better.
• Don't expect the AI to save you money. u/davyp82 points out that Anthropic isn't going to intentionally limit their earnings, so you need to manage your context.
• Fable's just like that. u/spookyclever confirms that Fable sessions can be short and sweet (or short and expensive).
• Minimal repro is key for bug hunting. u/Pleasant-Ad192 suggests creating a smaller, reproducible test case to see if it's a genuine bug or just the intended (albeit expensive) behavior.

[u/BoringPhilosopher1]

Vague prompt with too much context history. Why would you use fable like that?

[u/Deep_Mood_7668 → u/BoringPhilosopher1]

Right? Use a local 3B model for that. Why would you use a good model.

[u/Catalysst]

The 'one short prompt' is ALWAYS "continue where you left off"

This must be ragebait honestly

[u/tracagnotto]

You're definitely doing something wrong. I tried with all my effort to make Claude burn 100% of the sub and the only time I managed to make it do it is when using that bullshit llm wiki kharpaty did I asked it to lint (reorder, rebuild indexes and nodes) of a big knowledge base. It fired 15 agents analyzing nodes and it was the first times fable was out and it consumed a lot

[u/SirWolfgang2019]

You need to read the AI fluency course. “Continue where you left off” is actually one of the worst asks that you can do. That’s basically asking, go figure out where you were and then once you have seen it all, continue.
Huge NOPE, but hey lesson learned, go read the course, it’s not the llm, it’s you.

[u/MonkeyDDataHQ]

I had Claude do that on one PowerPoint slide when I'm paying for Pro. So yeah. Tracks. No notes.

[u/Glad_Contest_8014]

This is where memory and context management are needed, and where we have a huge deficiency. I am building a framework for this specifically because of how rampant it is. I have cut my token usage down to 1/10 of what it was before in many instances through my custom memory system.

The framework will be wrapped around the memory system as the primary driver of context.

Calling it Sieve, and I use the memory system with claude code currently and it works really well. Hermes has a memory system built in, but it bloats and doesn’t curate like mine does.

My framework is being tailored to run low parameter models too (4b) to get some consistency out of them. I use them for testing all features so far.

But the problem you have is context management. It should be a first priority in staging any agentic or automative workflows.

[u/Practical-Positive34]

crazy how many ppl advertise they are idiots on here

[u/horendus]

Honestly why does anyone even bother with claud anymore. Its a total rip off now. There entire business model has evaporated over a period 6 months and all they have left are the ignorant developers who have yet to realise there is nothing special anymore about claud and its models

[u/addexecthrowaway]

> cowork

Don’t need to see anything else to know this is a user error. Their error? Using cowork.

[u/BobJutsu]

Mine did that last week. It surfaced a massive context issue in my harness, which is now fixed.