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Agent skill

Conversation Analyzer

by mhattingpete in mhattingpete/claude-skills-marketplace

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

Apache-2.0Auto-check passedDevelopment

Install Conversation Analyzer

skills CLI
$ npx skills add mhattingpete/claude-skills-marketplace --skill conversation-analyzer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mhattingpete/claude-skills-marketplace conversation-analyzer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mhattingpete/claude-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/productivity-skills-plugin/skills/conversation-analyzer .claude/skills/conversation-analyzer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
conversation-analyzer
GitHub stars
680
Token cost
~1k tokens
SKILL.md length
348 words
Files
2 (incl. scripts)
Skills in repo
16
Repo updated
First seen
Licence
Apache-2.0

At a glance

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

  • Works in 6 steps: Request Type Distribution → Project Activity → Time Patterns → …
  • User wants to understand usage patterns
  • SKILL.md covers When to Use, What It Analyzes, Analysis Scope and Methodology, plus 7 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Conversation Analyzer is an agent skill from mhattingpete/claude-skills-marketplace. 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.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/analyze_history.py`).

It sits in Development. The repository describes itself as: Claude Code Skills for software engineering workflows - Git automation, testing, and code review. The licence is Apache-2.0.

When your agent uses it

  • User wants to understand usage patterns
  • Optimize workflow
  • Identify automation opportunities
  • Check if theyre following best practices

Example prompts

  • “Use the conversation-analyzer skill to analyz your Claude Code conversation history to identify patterns, common mistakes, and opportunities for…”
  • “/conversation-analyzer”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Request Type Distribution
  2. Project Activity
  3. Time Patterns
  4. Common Mistakes
  5. Error Analysis
  6. Automation Opportunities

What it can do on your machine

Read from SKILL.md and the folder at commit b5b34bc. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Conversation Analyzer loads about 1k tokens when it runs. Until then it costs about 75 tokens; SKILL.md has 348 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~75
When it runs · the whole SKILL.md, loaded when a task matches
~1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mhattingpete/claude-skills-marketplace at commit b5b34bc, republished under its Apache-2.0 licence (© mhattingpete). 348 words, ~1,034 tokens.

Download SKILL.mdSave it as .claude/skills/conversation-analyzer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
conversation-analyzer
description
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.

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

  1. Request type distribution (bug fixes, features, refactoring, queries, testing)
  2. Most active projects
  3. Common error keywords
  4. Time-of-day patterns
  5. Repetitive tasks (automation opportunities)
  6. Vague requests causing back-and-forth
  7. Complex tasks attempted without planning
  8. 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:

bash
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.

© mhattingpete, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in productivity-skills-plugin/skills/conversation-analyzer of mhattingpete/claude-skills-marketplace.

  • SKILL.md
  • scripts/analyze_history.py

Open the folder on GitHubat commit b5b34bc

Compare with similar skills

Conversation Analyzer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Conversation Analyzer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Conversation Analyzer this skillmhattingpete/claude-skills-marketplace680—~1kAutomated safety check: PassApache-2.0
Vercel Composition Patternssupabase/supabase111k58 repos~726Automated safety check: PassMIT
Finishing a Development Branchobra/superpowers297k5 repos~1.9kAutomated safety check: PassMIT
Typescript Advanced Typesrolling-scopes/rsschool-app10k25 repos~4.2kAutomated safety check: PassMPL-2.0
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT

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Categories

Questions about Conversation Analyzer

What does Conversation Analyzer do?

Analyzes your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement. Conversation Analyzer is an agent skill from mhattingpete/claude-skills-marketplace. Analyzes your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement.

When should I use Conversation Analyzer?

Conversation Analyzer fits situations like: user wants to understand usage patterns; optimize workflow; identify automation opportunities; check if theyre following best practices.

How do I install Conversation Analyzer in Claude Code?

Run `npx skills add mhattingpete/claude-skills-marketplace --skill conversation-analyzer -a claude-code`. Or copy the skill folder (productivity-skills-plugin/skills/conversation-analyzer in mhattingpete/claude-skills-marketplace) into .claude/skills/conversation-analyzer in your project. Claude Code loads it when a task matches its description.

How do I install Conversation Analyzer in Codex?

Run `npx skills add mhattingpete/claude-skills-marketplace --skill conversation-analyzer -a codex`. Or copy the skill folder (productivity-skills-plugin/skills/conversation-analyzer in mhattingpete/claude-skills-marketplace) into .agents/skills/conversation-analyzer in your project. Codex loads it when a task matches its description.

Can I use Conversation Analyzer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mhattingpete/claude-skills-marketplace --skill conversation-analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/conversation-analyzer, .gemini/skills/conversation-analyzer, .github/skills/conversation-analyzer and .opencode/skills/conversation-analyzer in your project.

What does Conversation Analyzer need to run?

Going by SKILL.md and its folder, Conversation Analyzer needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Conversation Analyzer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Conversation Analyzer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Conversation Analyzer use?

Conversation Analyzer is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Conversation Analyzer use?

About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Conversation Analyzer?

Skills that share tags, products or a category with Conversation Analyzer: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 297k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Conversation Analyzer?

mhattingpete (a GitHub user) maintains it in mhattingpete/claude-skills-marketplace, which has 680 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on July 25, 2026.

Source: mhattingpete/claude-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.