tldr-stats

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

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Install skill "tldr-stats" with this command: npx skills add parcadei/continuous-claude-v3/parcadei-continuous-claude-v3-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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