Browse and analyze Claude Code conversation history with this desktop app. Ideal for developers and operations teams to review past interactions, extract insights, and improve workflows. Connects to locally stored conversation data.
git clone https://github.com/jhlee0409/claude-code-history-viewer.githttps://jhlee0409.github.io/claude-code-history-viewer/
["1. Install the Claude Code History Viewer desktop app on your computer.","2. Open the app and connect it to your locally stored Claude conversation data.","3. Use the search function to filter conversations by date range, keywords, or specific topics.","4. Select relevant conversations and use the 'Extract Code' feature to gather all code snippets.","5. For better results, be specific in your search queries and use the prompt template provided to structure your analysis."]
Quickly browse through past Claude Code conversations by project or session.
Analyze token usage and API costs to optimize future interactions.
Search for specific messages across all conversation histories.
Restore previous versions of conversations using the recent edits feature.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/jhlee0409/claude-code-history-viewerCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Review my Claude Code conversation history from [DATE RANGE] and extract all code snippets related to [PROGRAMMING LANGUAGE]. For each snippet, provide: 1) The original context of the conversation, 2) The specific code provided by Claude, 3) Any modifications or improvements I made to the code, and 4) The final outcome or integration status. Format the output as a table with columns for each of these elements.
Here's a summary of your Python-related code conversations from January 1st to January 31st:
| Conversation Context | Claude's Code | Your Modifications | Outcome/Status |
|---------------------|---------------|-------------------|------------------|
| Building a data processing pipeline | ```python
def process_data(data):
cleaned_data = [x for x in data if x is not None]
return cleaned_data
``` | Added error handling and logging: ```python
def process_data(data):
try:
cleaned_data = [x for x in data if x is not None]
logger.info(f'Processed {len(cleaned_data)} items')
return cleaned_data
except Exception as e:
logger.error(f'Error processing data: {str(e)}')
``` | Integrated into main pipeline. Running successfully in production. |
| Debugging API connection issues | ```python
import requests
response = requests.get(api_url)
if response.status_code == 200:
data = response.json()
``` | Added timeout and retry logic: ```python
import requests
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
session = requests.Session()
retry = Retry(total=3, backoff_factor=1, status_forcelist=[500, 502, 503, 504])
adapter = HTTPAdapter(max_retries=retry)
session.mount('http://', adapter)
response = session.get(api_url, timeout=10)
if response.status_code == 200:
data = response.json()
``` | Implemented in staging environment. Testing in progress. |
| Creating a new database schema | ```sql
CREATE TABLE users (
id SERIAL PRIMARY KEY,
username VARCHAR(50) UNIQUE NOT NULL,
email VARCHAR(100) UNIQUE NOT NULL
);
``` | Added additional fields and constraints: ```sql
CREATE TABLE users (
id SERIAL PRIMARY KEY,
username VARCHAR(50) UNIQUE NOT NULL,
email VARCHAR(100) UNIQUE NOT NULL,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
last_login TIMESTAMP,
is_active BOOLEAN DEFAULT TRUE
);
``` | Reviewed with team. Scheduled for deployment next sprint. |AI assistant built for thoughtful, nuanced conversation
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