Tldr Stats
- 457 installs
- 3.9k repo stars
- Updated January 26, 2026
- parcadei/continuous-claude-v3
tldr-stats is a Claude Code skill that runs a Python dashboard script to report session token usage, API costs, TLDR savings, and hook activity for developers who need to audit Continuous-Claude-v3 compression and spend.
About
tldr-stats is a diagnostic skill in the parcadei/continuous-claude-v3 stack that executes python3 $CLAUDE_PROJECT_DIR/.claude/scripts/tldr_stats.py and returns a formatted dashboard the agent must paste into chat. The output breaks down dollars spent, input and output tokens, cached reuse, TLDR before/after compression, file-read compression ratios, cache hit rates, active model, hook activity, and a history sparkline across recent sessions. Cost estimates reference published Claude pricing tiers such as Opus $15/1M, Sonnet $3/1M, and Haiku $0.25/1M tokens. Developers reach for tldr-stats when validating whether TLDR hooks are firing, comparing savings before and after enabling compression, or debugging unexpectedly high session spend during long agent runs.
- tldr-stats
Tldr Stats by the numbers
- 457 all-time installs (skills.sh)
- +2 installs in the week ending Aug 4, 2026 (Skillselion tracking)
- Ranked #910 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 457 |
|---|---|
| repo stars | ★ 3.9k |
| Last updated | January 26, 2026 |
| Repository | parcadei/continuous-claude-v3 ↗ |
How do you measure TLDR token savings in Claude Code?
Use tldr-stats for development tasks
Who is it for?
Developers running Continuous-Claude-v3 with TLDR compression who need a quick session cost指標 of API cost and hook effectiveness.
Skip if: Developers without the Continuous-Claude-v3 TLDR daemon and tldr_stats.py script installed in their project should skip tldr-stats.
When should I use this skill?
User asks about session token usage, TLDR savings, API costs, hook activity, or whether TLDR compression is working.
What you get
Formatted dashboard with session spend, token breakdown, TLDR savings, cache metrics, model name, and hook activity
- Session stats dashboard output
- TLDR savings breakdown
- Hook activity report
By the numbers
- Cost estimates use Opus $15/1M, Sonnet $3/1M, and Haiku $0.25/1M tokens
- Executes python3 $CLAUDE_PROJECT_DIR/.claude/scripts/tldr_stats.py
Files
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.
1. Run the stats script:
python3 $CLAUDE_PROJECT_DIR/.claude/scripts/tldr_stats.py2. 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 sessionsUnderstanding 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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Pick tldr-stats over generic billing pages when you need in-session TLDR compression metrics tied to Continuous-Claude hooks rather than account-wide invoices.
FAQ
What command does tldr-stats run?
tldr-stats instructs the agent to run python3 $CLAUDE_PROJECT_DIR/.claude/scripts/tldr_stats.py and paste the full terminal dashboard into the chat so token usage, costs, and TLDR savings are visible.
What metrics does the tldr-stats dashboard show?
The tldr-stats dashboard reports session dollars spent, input/output/cached tokens, TLDR savings versus uncompressed reads, file compression ratios, cache hit rates, active model, hook activity, and a recent-session sparkline.
When should developers invoke tldr-stats?
Developers invoke tldr-stats before or after long Claude Code sessions to verify TLDR hooks are active, compare compression savings in dollar terms, and debug unexpected API spend.