claude-token-analyzer

Claude Token Analyzer

Your Claude Code sessions might be burning tokens you can't see. Diagnoses where your tokens go, why they're wasted, and what to fix first.

Fully local — parses your ~/.claude JSONL files into SQLite. Nothing leaves your machine. No cloud. No telemetry.

English | 繁體中文

Features

• Diagnose token waste — Detects 6 statistical anomaly types (HighCost, LowCacheHitRate, CostInefficient, ExcessiveToolUse, HighTokenUsage, UnusualModelMix) with severity scoring
• Audit costs — Per-session, per-project, and global cost breakdowns with monthly trends
• Forecast spending — Daily/weekly/monthly usage trends with burn-rate projections
• Optimize cache — Identifies sessions with poor cache hit rates that inflate costs
• Prioritize fixes — Severity-scored anomalies so you know what to fix first, not just what's wrong
• Converse naturally — Ask in plain language: "how much did I spend?" or "scan for anomalies"

Quick Start

# Install (binary auto-downloads, no Rust toolchain needed)
claude plugin install claude-token-analyzer

Then just ask in any Claude Code session:

> cta
> how much did I spend this month?
> scan for anomalies
> analyze this project
> show me usage trends

How It Works

~/.claude/projects/**/*.jsonl       Your session logs (never modified)
    → parser.rs                     Extract + deduplicate responses
    → analyzer.rs                   Cost calculation, 10-dimension metrics
    → storage.rs                    Upsert into local SQLite
    → detector.rs                   6-type anomaly detection + severity scoring
    → MCP tools / Skills            You ask, it answers

All processing happens locally. The SQLite database lives in the plugin directory. No network calls, no external dependencies at runtime.

Skills

Skill	Trigger Phrases	What It Does
cta	"cta", "analyze tokens"	Routes to the right sub-skill
cta-health-check	"quick check", "overview", "看看狀況"	One-page usage summary
cta-cost-audit	"monthly costs", "cost report", "這個月花多少"	Monthly cost breakdown with model split
cta-anomaly-hunt	"anomalies", "problems", "有異常嗎"	Statistical anomaly scan with drill-down
cta-project-review	"analyze project", "專案健檢"	Four-dimension project analysis
cta-trend-watch	"trends", "burn rate", "趨勢"	Usage trend analysis with forecasting

MCP Tools

Tool	Purpose
sync_db	Sync JSONL session logs to SQLite
analyze_session	10-dimension session analysis
analyze_project	Project-level aggregation with sorting
analyze_global	Cross-project panoramic view
cost_report	Monthly cost report (daily granularity available)
anomaly_scan	6-type anomaly detection with severity scoring
trend_report	Time-series trends (daily/weekly/monthly)

Configuration

Environment variables (all optional):

Variable	Purpose	Default
CTA_DB_PATH	SQLite database location	${CLAUDE_PLUGIN_ROOT}/data/token-analyzer.db
CTA_PROJECTS_DIR	Session logs directory	~/.claude/projects
CTA_ARCHIVE_DIR	Archive directory	~/.claude/token-analyzer-archive
CTA_PRICING_PATH	Custom pricing TOML	Embedded in binary

Path resolution priority: Environment variable > Plugin mode ($CLAUDE_PLUGIN_ROOT) > Standalone mode ($HOME/.claude/)

Building from Source

git clone https://github.com/li195111/claude-token-analyzer.git
cd claude-token-analyzer
bash scripts/build.sh
# Binary: mcp-server/target/release/cta-mcp-server

# Run tests (98 tests)
cargo test --all-targets --manifest-path mcp-server/Cargo.toml

# Lint
cargo clippy --manifest-path mcp-server/Cargo.toml -- -D warnings

# Launch with plugin loaded
claude --plugin-dir .

Requires: Rust toolchain

Contributing

Issues and PRs welcome! See open issues for starter tasks.

Development setup:

1. Clone the repo and run bash scripts/build.sh
2. Run cargo test --all-targets --manifest-path mcp-server/Cargo.toml to verify
3. Load the plugin locally with claude --plugin-dir .

Rust toolchain required. The project uses cargo clippy -- -D warnings for linting.

License

MIT

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繁體中文

你的 Claude Code 會話可能正在浪費你看不見的 token。 診斷 token 流向、浪費原因，並告訴你該優先修正什麼。

全本地運行 — 解析 ~/.claude JSONL 檔案到 SQLite。資料不離開你的機器。無雲端、無遙測。

功能特色