conversation-analyzer

Q: How do I install conversation-analyzer?

Run npx skills add https://github.com/mhattingpete/claude-skills-marketplace --skill conversation-analyzer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/conversation-analyzer/ (personal) or .claude/skills/conversation-analyzer/ (project).

by mhattingpeteProductivity & Automation

Analyzes your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement. Use when user wants to understand usage patterns, optimize workflow, identify automation opportunities, or check if they're following best practices.

Installs: 245
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/mhattingpete/claude-skills-marketplace --skill conversation-analyzer

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads conversation-analyzer automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Conversation Analyzer

Analyzes your Claude Code conversation history to identify patterns, common mistakes, and workflow improvement opportunities.

When to Use

"analyze my conversations"
"review my Claude Code history"
"what patterns do you see in my usage"
"how can I improve my workflow"
"am I using Claude Code effectively"

What It Analyzes

Request type distribution (bug fixes, features, refactoring, queries, testing)
Most active projects
Common error keywords
Time-of-day patterns
Repetitive tasks (automation opportunities)
Vague requests causing back-and-forth
Complex tasks attempted without planning
Recurring bugs/errors

Analysis Scope

Default: Last 200 conversations for recency and relevance.

Methodology

1. Request Type Distribution

Categorizes by: bug fixes, feature additions, refactoring, information queries, testing, other.

2. Project Activity

Tracks which projects consume most time, identifies project-specific patterns.

3. Time Patterns

Hour-of-day usage distribution, identifies peak productivity times.

4. Common Mistakes

Vague requests: Initial requests lacking context vs. acceptable follow-ups
Repeated fixes: Same issues occurring multiple times
Complex tasks: Multi-step requests without planning
Repetitive commands: Manual tasks that could be automated

5. Error Analysis

Frequency of error-related requests, common error keywords, recurring problems.

6. Automation Opportunities

Identifies repeated exact requests, suggests skills, slash commands, or scripts.

Output

Structured report with:

Statistics: Request types, active projects, timing patterns
Patterns: Common tasks, repetitive commands, complexity indicators
Issues: Specific problems with examples
Recommendations: Prioritized, actionable improvements

Tools Used

Read: Load history file (~/.claude/history.jsonl)
Write: Create analysis reports if requested
Bash: Execute Python analysis script
Direct analysis: Parse JSON programmatically

Analysis Script

Uses scripts/analyze_history.py for comprehensive analysis:

Capabilities:

Loads and parses ~/.claude/history.jsonl
Analyzes patterns across multiple dimensions
Identifies common mistakes and inefficiencies
Generates actionable recommendations
Outputs detailed reports

Usage within skill: Runs automatically when user requests analysis.

Standalone usage:

cd ~/.claude/plugins/*/productivity-skills/conversation-analyzer/scripts
python3 analyze_history.py

Outputs:

conversation_analysis.txt - Detailed pattern analysis
recommendations.txt - Specific improvement suggestions

Example Output

Analyzed last 200 conversations:
- 60% general tasks, 15% bug fixes, 13% feature additions
- Project "ultramerge" dominates 58% of activity
- Same test-fixing request made 8 times
- 19 multi-step requests without planning
- Peak productivity: 13:00-15:00

Recommendations:
- Use test-fixing skill for recurring test failures
- Create project-specific utilities for ultramerge
- Use feature-planning skill for complex requests
- Add tests to prevent recurring bugs
- Schedule complex work during peak hours

Success Criteria

User understands usage patterns
Concrete, actionable recommendations
Specific examples from history
Prioritized by impact (quick wins vs long-term)
User can immediately apply improvements

Integration

feature-planning: Implement recommended improvements
test-fixing: Address recurring test failures
git-pushing: Commit workflow improvements

Privacy Note

All analysis happens locally. Conversation history never leaves user's machine.

FAQ

What does the conversation-analyzer skill do?

How do I install conversation-analyzer?

Run npx skills add https://github.com/mhattingpete/claude-skills-marketplace --skill conversation-analyzer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/conversation-analyzer/ (personal) or .claude/skills/conversation-analyzer/ (project).

Which AI agents can use conversation-analyzer?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is conversation-analyzer safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains conversation-analyzer?

It is published by mhattingpete in mhattingpete/claude-skills-marketplace. It has 245 recorded installs.