Overview

On April 1, 2026, a developer using the Claude Code Max 20 plan ($200/month) burned through 100% of their usage in roughly 70 minutes during a normal coding session. JSONL log analysis revealed an average cache read ratio of 36.1% (minimum 21.1%) — far below the 90%+ that should be expected. Every token was billed at full price.

That incident gave rise to ArkNill/claude-code-cache-analysis: a community-driven investigation that grew from personal debugging into a systematic, proxy-measured analysis confirming 7 bugs across 5 layers.

Background: A Plan Drained in 70 Minutes

The immediate workaround was downgrading from v2.1.89 to v2.1.68 (npm). Cache read immediately recovered to 97.6% average (119 entries), confirming the regression was v2.1.89-specific.

A transparent monitoring proxy (cc-relay) was then configured using the ANTHROPIC_BASE_URL environment variable to capture per-request data. Combined with reports from 91+ related GitHub issues and contributors including @Sn3th, @rwp65, and a dozen others, the scattered findings were consolidated into structured, measured analysis.

The 7 Confirmed Bugs (as of v2.1.91)

flowchart TD
    A["Claude Code Request"] --> B{"Version Check"}
    B -->|"v2.1.89 standalone"| C["B1: Sentinel <br/> Cache prefix corruption <br/> → 4-17% cache read"]
    B -->|"--resume flag"| D["B2: Resume <br/> Full context replayed uncached <br/> → 20x cost per resume"]
    B -->|"v2.1.91"| E["Cache normal: 95-99%"]
    E --> F{"Still active bugs"}
    F --> G["B3: False RL <br/> Fake rate limit error <br/> 0 API calls made"]
    F --> H["B4: Microcompact <br/> Tool results silently cleared <br/> mid-session"]
    F --> I["B5: Budget Cap <br/> 200K aggregate limit <br/> → truncated to 1-41 chars"]
    F --> J["B8: Log Inflation <br/> JSONL entry duplication <br/> → 2.87x local inflation"]

Key Bug Deep Dives

B1: Sentinel Bug (Fixed)

Claude Code ships in two forms. The standalone binary is a single ELF 64-bit executable (~228MB) with an embedded Bun runtime. It contained a Sentinel replacement mechanism (cch=00000) that corrupted cache prefixes — causing dramatically low cache read rates.

The npm package (cli.js, ~13MB, executed by Node.js) does not contain this logic and was immune to Bug 1.

In v2.1.91, routing stripAnsi through Bun.stripANSI appears to have closed the Sentinel gap. Both npm and standalone now achieve identical 84.7% cold-start cache read.

B2: Resume Bug (Fixed)

Using --resume caused the entire conversation context to be sent as billable input with no cache benefit — up to 20x the expected cost per resume. Fixed in v2.1.91’s transcript chain break patch, but avoiding --resume and --continue entirely is still the recommended approach.

B3: False Rate Limiting (Unfixed)

The client generates “Rate limit reached” errors locally without ever making an API call. Measured across 151 entries / 65 sessions. The session appears throttled while the API has not been contacted at all.

B4 & B5: Microcompact and Budget Cap (Unfixed)

Tool results are silently deleted mid-session (327 events detected), and a 200K aggregate limit causes older file read results to be truncated to 1-41 characters. After approximately 15-20 tool uses, earlier context is effectively gone without any warning.

Cache TTL (Not a Bug)

Idle gaps of 13+ hours cause a full cache rebuild on resume. Cache write costs $3.75/M versus read at $0.30/M — a 12.5x difference. Shorter gaps (5-26 minutes) maintain 96%+ cache. This is by design (5-minute TTL), not a bug — but worth understanding.

npm vs Standalone: v2.1.90 Benchmark

In v2.1.91, the sub-agent cold start gap is also closed. Both achieve 84.7% cold-start cache read identically.

Anthropic’s Official Position

Lydia Hallie from Anthropic posted on X (April 2):

“Peak-hour limits are tighter and 1M-context sessions got bigger, that’s most of what you’re feeling. We fixed a few bugs along the way, but none were over-charging you.”

She recommended using Sonnet as default, lowering effort level, starting fresh instead of resuming, and capping context with CLAUDE_CODE_AUTO_COMPACT_WINDOW=200000.

The analysis agrees that the cache bugs are fixed, but identifies five additional active mechanisms that Anthropic’s statement does not address.

What You Can Do Right Now

1. Update to v2.1.91 — fixes the cache regression responsible for the worst drain
2. npm and standalone are equivalent on v2.1.91 — either install method is fine
3. Do not use --resume or --continue — replays full context as billable input
4. Start fresh sessions periodically — the 200K tool result cap (B5) means older file reads silently truncate after ~15-20 tool uses
5. Avoid /dream and /insights — silent background API calls that consume quota

// ~/.claude/settings.json — disable auto-update
{
  "env": {
    "DISABLE_AUTOUPDATER": "1"
  }
}

Closing Thoughts

This analysis is a strong example of community-driven debugging at its best. A simple transparent proxy via ANTHROPIC_BASE_URL, combined with systematic testing across v2.1.89 through v2.1.91, produced measured evidence behind phenomena reported across 91+ GitHub issues.

The cache bugs (B1, B2) are fixed in v2.1.91. The remaining five bugs are still active. For Max plan users, applying the practical mitigations above and pinning a validated version with DISABLE_AUTOUPDATER is the most reliable defensive posture until Anthropic addresses the remaining issues.

Source repository: ArkNill/claude-code-cache-analysis