TLDR Stats - Claude AI 令牌使用监控与成本节省分析仪表盘工具

tldr-stats by parcadei/continuous-claude-v3

198 周安装量

3,600 GitHub Stars

GitHub

安装命令

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

AI/机器学习数据分析性能优化

🇨🇳中文介绍

TLDR Stats Skill

显示一个美观的仪表盘，展示令牌使用情况、实际 API 成本、TLDR 节省金额以及钩子活动。

使用场景

查看 TLDR 实际为您节省了多少美元
检查会话总令牌使用量和成本
TLDR 效果的前后对比
调试 TLDR/钩子是否正在被使用
查看正在使用的模型

使用说明

重要提示： 运行脚本并将输出显示给用户。

运行统计脚本：

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

将完整输出复制到您的回复中，以便用户直接在聊天中看到仪表盘。不要只是静默地运行命令——用户希望看到统计数据。

示例输出

╔══════════════════════════════════════════════════════════════╗
║  📊 会话统计                                                 ║
╚══════════════════════════════════════════════════════════════╝

  本次会话您已花费  $96.52

  使用的令牌
        1.2M 发送给 Claude
      416.3K 接收返回
       97.8K 来自提示缓存 (8% 被复用)

  TLDR 节省

    您发送了：               1.2M
    若无 TLDR：              2.5M

    💰 TLDR 为您节省了约 $18.83
    (若无 TLDR：$115.35 → 使用 TLDR：$96.52)

    文件读取：1.3M → 20.9K █████████░ 缩小了 98%

  TLDR 缓存
    重新读取同一文件？TLDR 会记住它。
    █████░░░░░░░░░░ 37% 缓存命中率
    (35 个复用 / 60 个重新解析)

  钩子：553 次调用 (✓ 全部正常)
  历史记录：█▃▄ ▇▃▇▆ 平均压缩率 84%
  守护进程：运行 24m │ 3 个会话

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指标	含义
您已花费	本次会话在 Claude API 上的实际美元支出
您发送 / 若无 TLDR	实际令牌数 vs 若无 TLDR 时的令牌数
TLDR 为您节省	通过压缩文件读取节省的金额
文件读取 X → Y	原始文件令牌数压缩为 TLDR 摘要
缓存命中率	TLDR 复用已解析文件结果的频率
历史记录 sparkline	近期会话的压缩百分比 (█ = 高)

🇺🇸English

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

Weekly Installs

198

Repository

parcadei/contin…laude-v3

GitHub Stars

3.6K

First Seen

Jan 24, 2026

Security Audits

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Installed on

opencode188

codex187

gemini-cli186

cursor183

github-copilot183

amp180

TLDR Stats - Claude AI 令牌使用监控与成本节省分析仪表盘工具

🇨🇳中文介绍

TLDR Stats Skill

使用场景

使用说明

示例输出

相关 Skills

理解数据指标

视觉元素

注意事项

🇺🇸English

TLDR Stats Skill

When to Use

Instructions

Sample Output

Understanding the Numbers

Visual Elements

Notes

最新 Skills