What kind of recommendations does the analyzer provide?

It suggests specific Claude skills to use, scripts for automation, and improvements for request clarity based on your historical data.

How far back does the analysis go?

By default, the skill analyzes the most recent 200 conversations to provide findings that are relevant to your current workflow.

How does the skill access my conversation history?

The skill securely parses your local history file located at ~/.claude/history.jsonl using an included Python analysis script.

Is my conversation data sent to an external server?

No. All analysis is performed entirely on your local machine, ensuring your code and conversation history remain private.

Can I run this analysis independently of Claude?

Yes, the underlying Python script can be executed as a standalone tool directly from the plugin's scripts directory.

Conversation Analyzer

Name: Conversation Analyzer
Author: mhattingpete

bymhattingpete

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126

生产力与工作流

Analyzes Claude Code conversation history to identify usage patterns, recurring errors, and specific workflow optimization opportunities.

关于

The Conversation Analyzer provides deep insights into your interaction patterns with Claude Code by parsing local history logs to identify bottlenecks, repetitive manual tasks, and areas for improvement. By categorizing request types and highlighting project-specific trends, it delivers actionable, prioritized recommendations that help developers refine their prompting strategies, reduce back-and-forth, and automate frequent coding workflows.

主要功能

Identifies repetitive tasks and manual commands suitable for automation
Generates structured reports with prioritized workflow improvements
Categorizes request distributions across bug fixes, features, and refactoring
Detects vague requests and multi-step tasks lacking proper planning
Analyzes project-specific activity to track where development time is spent
126 GitHub stars

使用场景

Optimizing developer productivity by identifying and automating recurring CLI patterns
Auditing engineering focus areas to understand project-level time distribution
Improving prompt engineering quality by reviewing instances of inefficient back-and-forth

关于

主要功能

Identifies repetitive tasks and manual commands suitable for automation
Generates structured reports with prioritized workflow improvements
Categorizes request distributions across bug fixes, features, and refactoring
Detects vague requests and multi-step tasks lacking proper planning
Analyzes project-specific activity to track where development time is spent
126 GitHub stars

使用场景

Optimizing developer productivity by identifying and automating recurring CLI patterns
Auditing engineering focus areas to understand project-level time distribution
Improving prompt engineering quality by reviewing instances of inefficient back-and-forth