cc-analytics — community cc-analytics, ris-claude-code, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0

Об этом навыке

Идеально подходит для Агентов анализа Python, которым необходимы расширенная аналитика использования Claude Code и возможности генерации HTML-отчетов. Use when user asks for Claude Code usage stats, weekly analytics, project activity summary, or wants to see what projects were worked on. Triggers on аналитика, статистика claude, cc stats, weekly report, что делал

serejaris serejaris
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Updated: 3/12/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 9/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
9/11
Quality Score
51
Canonical Locale
ru
Detected Body Locale
ru

Идеально подходит для Агентов анализа Python, которым необходимы расширенная аналитика использования Claude Code и возможности генерации HTML-отчетов. Use when user asks for Claude Code usage stats, weekly analytics, project activity summary, or wants to see what projects were worked on. Triggers on аналитика, статистика claude, cc stats, weekly report, что делал

Зачем использовать этот навык

Позволяет агентам генерировать комплексные HTML-отчеты об использовании Claude Code из ~/.claude/history.jsonl, используя данные Git для расширенной аналитики и предоставляя аналитику через заголовки с ASCII-артом, сводную статистику и таблицы проектов со ссылками на удаленные репозитории.

Подходит лучше всего

Идеально подходит для Агентов анализа Python, которым необходимы расширенная аналитика использования Claude Code и возможности генерации HTML-отчетов.

Реализуемые кейсы использования for cc-analytics

Генерация HTML-отчетов об использовании Claude Code
Анализ аналитики проекта с интеграцией данных Git
Визуализация ASCII-гистограмм для подсчета коммитов

! Безопасность и ограничения

  • Требуется доступ к ~/.claude/history.jsonl
  • Требуется выполнение Python-скрипта
  • Для расширенной аналитики необходима доступность данных Git

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is cc-analytics?

Идеально подходит для Агентов анализа Python, которым необходимы расширенная аналитика использования Claude Code и возможности генерации HTML-отчетов. Use when user asks for Claude Code usage stats, weekly analytics, project activity summary, or wants to see what projects were worked on. Triggers on аналитика, статистика claude, cc stats, weekly report, что делал

How do I install cc-analytics?

Run the command: npx killer-skills add serejaris/ris-claude-code/cc-analytics. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for cc-analytics?

Key use cases include: Генерация HTML-отчетов об использовании Claude Code, Анализ аналитики проекта с интеграцией данных Git, Визуализация ASCII-гистограмм для подсчета коммитов.

Which IDEs are compatible with cc-analytics?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for cc-analytics?

Требуется доступ к ~/.claude/history.jsonl. Требуется выполнение Python-скрипта. Для расширенной аналитики необходима доступность данных Git.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add serejaris/ris-claude-code/cc-analytics. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use cc-analytics immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Imported Repository Instructions

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Supporting Evidence

cc-analytics

Install cc-analytics, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly
Imported Repository Instructions
The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.
Supporting Evidence

Claude Code Analytics

Generate HTML report of Claude Code usage from ~/.claude/history.jsonl.

Data Sources

  • History: ~/.claude/history.jsonl — prompts with timestamps and project paths
  • Git: Remote URLs and commit counts per project

Output

Single HTML file with terminal aesthetic:

  • ASCII art header
  • Summary stats (projects, prompts, commits, days)
  • Project table with remote links
  • ASCII bar chart

Generation Script

Run this Python script to generate the report:

python
1import json 2import os 3import subprocess 4from datetime import datetime, timedelta 5from collections import defaultdict 6 7def get_git_info(path): 8 if not os.path.isdir(path) or not os.path.exists(os.path.join(path, '.git')): 9 return None, 0 10 try: 11 result = subprocess.run(['git', '-C', path, 'remote', 'get-url', 'origin'], 12 capture_output=True, text=True, timeout=5) 13 remote = result.stdout.strip() if result.returncode == 0 else None 14 if remote: 15 remote = remote.replace('git@github.com:', 'github.com/').replace('.git', '').replace('https://', '') 16 17 week_ago = (datetime.now() - timedelta(days=7)).strftime('%Y-%m-%d') 18 result = subprocess.run(['git', '-C', path, 'rev-list', '--count', f'--since={week_ago}', 'HEAD'], 19 capture_output=True, text=True, timeout=5) 20 commits = int(result.stdout.strip()) if result.returncode == 0 else 0 21 return remote, commits 22 except: 23 return None, 0 24 25# Parse history 26history = [] 27with open(os.path.expanduser('~/.claude/history.jsonl'), 'r') as f: 28 for line in f: 29 try: 30 history.append(json.loads(line)) 31 except: 32 pass 33 34# Filter last N days (default 7) 35days = 7 36now = datetime.now() 37cutoff = (now - timedelta(days=days)).timestamp() * 1000 38 39projects = defaultdict(lambda: {'prompts': [], 'sessions': set()}) 40for entry in history: 41 ts = entry.get('timestamp', 0) 42 if ts >= cutoff: 43 project = entry.get('project', 'unknown') 44 projects[project]['prompts'].append(entry) 45 projects[project]['sessions'].add(datetime.fromtimestamp(ts/1000).strftime('%Y-%m-%d')) 46 47# Collect data 48results = [] 49total_commits = 0 50for project, data in projects.items(): 51 remote, commits = get_git_info(project) 52 total_commits += commits 53 results.append({ 54 'name': os.path.basename(project) or project.replace('/Users/ris/', '~/'), 55 'folder': project.replace('/Users/ris/', '~/'), 56 'remote': remote, 57 'prompts': len(data['prompts']), 58 'sessions': len(data['sessions']), 59 'commits': commits 60 }) 61 62results.sort(key=lambda x: -x['prompts']) 63max_prompts = results[0]['prompts'] if results else 1

HTML Template

Use terminal aesthetic with:

  • Monospace system fonts: 'SF Mono', 'Monaco', 'Inconsolata', monospace
  • Dark background: #0d0d0d
  • Muted colors: #b0b0b0 (text), #555 (dim), #4ec9b0 (cyan), #ce9178 (orange)
  • ASCII box-drawing for header
  • $ command --flags style section headers
  • ASCII bar chart using characters
html
1<!DOCTYPE html> 2<html lang="en"> 3<head> 4 <meta charset="UTF-8"> 5 <title>claude-analytics</title> 6 <style> 7 body { 8 font-family: 'SF Mono', 'Monaco', 'Inconsolata', monospace; 9 background: #0d0d0d; 10 color: #b0b0b0; 11 font-size: 14px; 12 line-height: 1.6; 13 padding: 24px; 14 } 15 .container { max-width: 900px; margin: 0 auto; } 16 .header { color: #6a9955; margin-bottom: 24px; } 17 .dim { color: #555; } 18 .bright { color: #e0e0e0; } 19 .cyan { color: #4ec9b0; } 20 .orange { color: #ce9178; } 21 .row { 22 display: grid; 23 grid-template-columns: 24px 200px 1fr 80px 80px 60px; 24 gap: 8px; 25 padding: 6px 0; 26 border-bottom: 1px solid #1a1a1a; 27 } 28 .row:hover { background: #141414; } 29 a { color: #555; text-decoration: none; } 30 a:hover { color: #888; } 31 .stat-box { display: inline-block; margin-right: 32px; } 32 .stat-value { font-size: 28px; color: #e0e0e0; } 33 .stat-label { color: #555; font-size: 12px; } 34 </style> 35</head> 36<body> 37 <div class="container"> 38 <pre class="header"> 39┌─────────────────────────────────────────────────────────────────┐ 40│ ██████╗██╗ █████╗ ██╗ ██╗██████╗ ███████╗ │ 41│ ██╔════╝██║ ██╔══██╗██║ ██║██╔══██╗██╔════╝ │ 42│ ██║ ██║ ███████║██║ ██║██║ ██║█████╗ │ 43│ ██║ ██║ ██╔══██║██║ ██║██║ ██║██╔══╝ │ 44│ ╚██████╗███████╗██║ ██║╚██████╔╝██████╔╝███████╗ │ 45│ ╚═════╝╚══════╝╚═╝ ╚═╝ ╚═════╝ ╚═════╝ ╚══════╝ │ 46│ Weekly Analytics Report │ 47│ {start_date} .. {end_date} │ 48└─────────────────────────────────────────────────────────────────┘ 49</pre> 50 <!-- Stats, table, chart sections --> 51 </div> 52</body> 53</html>

Bar Chart Generation

python
1def make_bar(value, max_val, width=40): 2 filled = int((value / max_val) * width) 3 return '█' * filled 4 5# Example output: 6# cohorts ████████████████████████████████████████ 194 7# ai-whisper █████████████████████████████████████▋ 183

Usage

  1. User asks for analytics: "покажи статистику cc", "weekly report", "что делал за неделю"
  2. Run Python script to collect data
  3. Generate HTML with template
  4. Save to ~/claude-analytics.html
  5. Open in browser: open ~/claude-analytics.html

Customization

  • Period: Change days = 7 to desired range
  • Output path: Change save location
  • Colors: Adjust CSS variables
  • Columns: Add/remove metrics in grid

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