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

v1.0.0
GitHub

About this Skill

Perfect for Python Analysis Agents needing advanced Claude Code usage analytics and HTML report generation capabilities. cc-analytics AIエージェント是一种代码分析和优化工具，帮助开发者提高代码质量和性能

serejaris serejaris
[0]
[0]
Updated: 2/24/2026

Agent Capability Analysis

The cc-analytics skill by serejaris is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Perfect for Python Analysis Agents needing advanced Claude Code usage analytics and HTML report generation capabilities.

Core Value

Empowers agents to parse `~/.claude/history.jsonl` files, leveraging Git data to generate comprehensive HTML reports with ASCII art headers, summary statistics, and bar charts, utilizing Python scripting for automation.

↓ Capabilities Granted for cc-analytics

Generating HTML reports of Claude Code usage for project analysis
Analyzing commit counts and project activity from Git data
Creating visualizations of Claude Code usage patterns with ASCII bar charts

! Prerequisites & Limits

  • Requires access to `~/.claude/history.jsonl` files
  • Needs Git data for remote URLs and commit counts
  • Python scripting environment required for report generation
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

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
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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

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?

Perfect for Python Analysis Agents needing advanced Claude Code usage analytics and HTML report generation capabilities. cc-analytics AIエージェント是一种代码分析和优化工具，帮助开发者提高代码质量和性能

How do I install cc-analytics?

Run the command: npx killer-skills add serejaris/ris-claude-code. 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: Generating HTML reports of Claude Code usage for project analysis, Analyzing commit counts and project activity from Git data, Creating visualizations of Claude Code usage patterns with ASCII bar charts.

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?

Requires access to `~/.claude/history.jsonl` files. Needs Git data for remote URLs and commit counts. Python scripting environment required for report generation.

↓ 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. 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.

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