tldr-stats

安装量: 177
排名: #4878

安装

npx skills add https://github.com/parcadei/continuous-claude-v3 --skill tldr-stats

TLDR Stats Skill

Show a beautiful dashboard with token usage, actual API costs, TLDR savings, and hook activity.

When to Use See how much TLDR is saving you in real $ terms Check total session token usage and costs Before/after comparisons of TLDR effectiveness Debug whether TLDR/hooks are being used See which model is being used Instructions

IMPORTANT: Run the script AND display the output to the user.

Run the stats script: python3 $CLAUDE_PROJECT_DIR/.claude/scripts/tldr_stats.py

Copy the full output into your response so the user sees the dashboard directly in the chat. Do not just run the command silently - the user wants to see the stats. Sample Output ╔══════════════════════════════════════════════════════════════╗ ║ 📊 Session Stats ║ ╚══════════════════════════════════════════════════════════════╝

You've spent $96.52 this session

Tokens Used 1.2M sent to Claude 416.3K received back 97.8K from prompt cache (8% reused)

TLDR Savings

You sent:               1.2M
Without TLDR:           2.5M

💰 TLDR saved you ~$18.83
(Without TLDR: $115.35 → With TLDR: $96.52)

File reads: 1.3M → 20.9K █████████░ 98% smaller

TLDR Cache Re-reading the same file? TLDR remembers it. █████░░░░░░░░░░ 37% cache hits (35 reused / 60 parsed fresh)

Hooks: 553 calls (✓ all ok) History: █▃▄ ▇▃▇▆ avg 84% compression Daemon: 24m up │ 3 sessions

Understanding the Numbers Metric What it means You've spent Actual $ spent on Claude API this session You sent / Without TLDR Actual tokens vs what it would have been TLDR saved you Money saved by compressing file reads File reads X → Y Raw file tokens compressed to TLDR summary Cache hits How often TLDR reuses parsed file results History sparkline Compression % over recent sessions (█ = high) Visual Elements Progress bars show savings and cache efficiency at a glance Sparklines show historical trends (█ = high savings, ▁ = low) Colors indicate status (green = good, yellow = moderate, red = concern) Emojis distinguish model types (🎭 Opus, 🎵 Sonnet, 🍃 Haiku) Notes Token savings vary by file size (big files = more savings) Cache hit rate starts low, increases as you re-read files Cost estimates use: Opus $15/1M, Sonnet $3/1M, Haiku $0.25/1M Stats update in real-time as you work

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