tldr-stats

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Original

English

🇨🇳

Translation

Chinese

TLDR Stats Skill

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

展示一个美观的仪表盘，包含token使用情况、实际API成本、TLDR节省金额以及hook活动。

When to Use

使用场景

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

查看TLDR在实际资金方面为你节省了多少
查看会话总token使用量和成本
对比TLDR启用前后的效果
排查TLDR/hooks是否正在被使用
查看当前使用的模型

Instructions

使用说明

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

Run the stats script:

bash

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.

重要提示： 运行脚本并将结果展示给用户。

运行统计脚本：

bash

python3 $CLAUDE_PROJECT_DIR/.claude/scripts/tldr_stats.py

将完整输出复制到回复中，让用户可以直接在聊天中查看仪表盘。不要静默运行命令——用户希望看到统计数据。

Sample Output

示例输出

╔══════════════════════════════════════════════════════════════╗
║  📊 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

╔══════════════════════════════════════════════════════════════╗
║  📊 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

数据解读

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)

指标	含义
You've spent	本次会话中使用Claude API的实际花费
You sent / Without TLDR	实际发送的token数量 vs 未使用TLDR时的预计数量
TLDR saved you	通过压缩文件读取节省的资金
File reads X → Y	原始文件token被压缩为TLDR摘要后的数量
Cache hits	TLDR复用已解析文件结果的频率
History sparkline	近期会话的压缩率（█表示高压缩率）

Visual Elements

可视化元素

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)

进度条：直观展示节省情况和缓存效率
迷你折线图（Sparklines）：展示历史趋势（█表示高节省率，▁表示低节省率）
颜色：表示状态（绿色=良好，黄色=中等，红色=需关注）
表情符号：区分模型类型（🎭 Opus, 🎵 Sonnet, 🍃 Haiku）

Notes

注意事项

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

Token节省量因文件大小而异（文件越大，节省越多）
缓存命中率初始较低，随着重复读取文件会逐渐提高
成本估算采用以下标准：Opus $15/1M token，Sonnet $3/1M token，Haiku $0.25/1M token
统计数据会随着你的操作实时更新