SkillsAdd

parcadei/continuous-claude-v3

tldr-stats

Show full session token usage, costs, TLDR savings, and hook activity

First seen Jan 24, 2026

Installation

$ npx skills add parcadei/continuous-claude-v3 --skill tldr-stats
View on skills.sh ↗ GitHub repository ↗

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

caveman-stats Similar name
juliusbrussee/caveman

Show real token usage and estimated savings for the current session, read from the session log.…

288.9K installs
huawei-cloud-obs-stats Similar name
huaweicloud/huaweicloud-skills

Query Huawei Cloud OBS (Object Storage Service) statistics: list buckets with capacity and obje…

5.9K installs
genshijin-stats Similar name
interfacex-co-jp/genshijin

現セッションのリアルトークン使用量と推定削減量を表示。Claude Code セッションログから直接読込 — …

5.6K installs
kosis-stats Similar name
nomadamas/k-skill

국가데이터처가 운영하는 KOSIS(국가통계포털, kosis.kr) Open API로 한국 공식 통계표를 검색하고 메…

2.8K installs
quick-stats Similar name
marketcalls/vectorbt-backtesting-skills

Quickly fetch data and print key backtest stats for a symbol with a default EMA crossover strat…

1.8K installs
statsmodels Similar name
k-dense-ai/scientific-agent-skills

Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixe…

1.5K installs

Also in this package

Other skills from parcadei/continuous-claude-v3 · top by installs.

npx skills add parcadei/continuous-claude-v3
discovery-interview 4.1K math 857 premortem 841 github-search 712 dead-code 690 refactor 612 graceful-degradation 592 explore 565 agentic-workflow 561 modular-code 555

Browse all from parcadei/continuous-claude-v3

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Also listed on

Alternate registries and mirrors of this skill.

Repository health

Stars 3.9K
License LICENSE
Default branch main
Open issues 30
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,015 B
  • docs SUMMARY.md 87 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 469 installs

SKILL.md

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.py
  1. 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