Cc Analytics logo

Cc Analytics

Community
serejaris
cc-analytics

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"

Overview

Publisherserejaris
Repositorypersonal-corp-os
Skill namecc-analytics
Stars
232
Forks
26
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by serejaris on GitHub. Read the source before you install it.

Installation

Install the Cc Analytics AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/serejaris/personal-corp-os/tree/main/skills/cc-analytics
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/serejaris/personal-corp-os.git /tmp/personal-corp-os
mkdir -p .claude/skills
cp -r /tmp/personal-corp-os/skills/cc-analytics .claude/skills/cc-analytics
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cc Analytics in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cc Analytics on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cc Analytics is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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
import json
import os
import subprocess
from datetime import datetime, timedelta
from collections import defaultdict

def get_git_info(path):
    if not os.path.isdir(path) or not os.path.exists(os.path.join(path, '.git')):
        return None, 0
    try:
        result = subprocess.run(['git', '-C', path, 'remote', 'get-url', 'origin'],
                                capture_output=True, text=True, timeout=5)
        remote = result.stdout.strip() if result.returncode == 0 else None
        if remote:
            remote = remote.replace('git@github.com:', 'github.com/').replace('.git', '').replace('https://', '')

        week_ago = (datetime.now() - timedelta(days=7)).strftime('%Y-%m-%d')
        result = subprocess.run(['git', '-C', path, 'rev-list', '--count', f'--since={week_ago}', 'HEAD'],
                                capture_output=True, text=True, timeout=5)
        commits = int(result.stdout.strip()) if result.returncode == 0 else 0
        return remote, commits
    except:
        return None, 0

# Parse history
history = []
with open(os.path.expanduser('~/.claude/history.jsonl'), 'r') as f:
    for line in f:
        try:
            history.append(json.loads(line))
        except:
            pass

# Filter last N days (default 7)
days = 7
now = datetime.now()
cutoff = (now - timedelta(days=days)).timestamp() * 1000

projects = defaultdict(lambda: {'prompts': [], 'sessions': set()})
for entry in history:
    ts = entry.get('timestamp', 0)
    if ts >= cutoff:
        project = entry.get('project', 'unknown')
        projects[project]['prompts'].append(entry)
        projects[project]['sessions'].add(datetime.fromtimestamp(ts/1000).strftime('%Y-%m-%d'))

# Collect data
results = []
total_commits = 0
for project, data in projects.items():
    remote, commits = get_git_info(project)
    total_commits += commits
    results.append({
        'name': os.path.basename(project) or project.replace('/Users/ris/', '~/'),
        'folder': project.replace('/Users/ris/', '~/'),
        'remote': remote,
        'prompts': len(data['prompts']),
        'sessions': len(data['sessions']),
        'commits': commits
    })

results.sort(key=lambda x: -x['prompts'])
max_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
<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <title>claude-analytics</title>
  <style>
    body {
      font-family: 'SF Mono', 'Monaco', 'Inconsolata', monospace;
      background: #0d0d0d;
      color: #b0b0b0;
      font-size: 14px;
      line-height: 1.6;
      padding: 24px;
    }
    .container { max-width: 900px; margin: 0 auto; }
    .header { color: #6a9955; margin-bottom: 24px; }
    .dim { color: #555; }
    .bright { color: #e0e0e0; }
    .cyan { color: #4ec9b0; }
    .orange { color: #ce9178; }
    .row {
      display: grid;
      grid-template-columns: 24px 200px 1fr 80px 80px 60px;
      gap: 8px;
      padding: 6px 0;
      border-bottom: 1px solid #1a1a1a;
    }
    .row:hover { background: #141414; }
    a { color: #555; text-decoration: none; }
    a:hover { color: #888; }
    .stat-box { display: inline-block; margin-right: 32px; }
    .stat-value { font-size: 28px; color: #e0e0e0; }
    .stat-label { color: #555; font-size: 12px; }
  </style>
</head>
<body>
  <div class="container">
    <pre class="header">
┌─────────────────────────────────────────────────────────────────┐
│   ██████╗██╗      █████╗ ██╗   ██╗██████╗ ███████╗              │
│  ██╔════╝██║     ██╔══██╗██║   ██║██╔══██╗██╔════╝              │
│  ██║     ██║     ███████║██║   ██║██║  ██║█████╗                │
│  ██║     ██║     ██╔══██║██║   ██║██║  ██║██╔══╝                │
│  ╚██████╗███████╗██║  ██║╚██████╔╝██████╔╝███████╗              │
│   ╚═════╝╚══════╝╚═╝  ╚═╝ ╚═════╝ ╚═════╝ ╚══════╝              │
│   Weekly Analytics Report                                       │
│   {start_date} .. {end_date}                                    │
└─────────────────────────────────────────────────────────────────┘
</pre>
    <!-- Stats, table, chart sections -->
  </div>
</body>
</html>

Bar Chart Generation

python
def make_bar(value, max_val, width=40):
    filled = int((value / max_val) * width)
    return '█' * filled

# Example output:
# cohorts          ████████████████████████████████████████ 194
# 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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cc Analytics AI skill do?

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"

Why use Cc Analytics on TypingMind?

Because you install it once and use it with any model. Cc Analytics is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cc Analytics in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/serejaris/personal-corp-os/tree/main/skills/cc-analytics. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cc Analytics?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cc Analytics?

As many as you like. As long as a model supports skills, you can use Cc Analytics with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cc Analytics AI skill free?

Yes. It is published on GitHub by serejaris under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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