motif-cli 0.2.0

Discover your coding patterns from AI conversations. Generate personalized .cursorrules, CLAUDE.md, and skills.

Motif

How good of a vibe coder are you? Motif generates your personal assessment.

Motif reads your Cursor and Claude Code conversations and turns them into a shareable report — how many sessions you run in parallel, how much you've grown, what your AI personality looks like. It also discovers your recurring workflows and generates personalized CLAUDE.md / .cursorrules / skills files tuned to how you actually work.

No API key needed. No server. Your data stays on your machine.

Install

pip install motif-cli

How It Works

1. Extract conversations from Cursor and/or Claude Code
2. Analyze — Motif prepares your data and your IDE's agent does the analysis (no external LLM calls)
3. Generate — turn analysis into CLAUDE.md, skills, and rules files routed to the right locations

Quick Start

Option A: Agent-driven (recommended)

If you use Cursor, install the Motif skill so your agent handles everything:

motif setup

Then just tell your agent: "analyze my coding patterns" — it handles extraction, analysis, and generation.

Option B: Manual CLI

# Extract conversations from all available sources
motif extract all

# See what was extracted
motif list

# Prepare data for analysis (your agent reads the output)
motif analyze --prepare

# After your agent produces analysis JSON, generate config files
motif rules analysis-output.json

# Generate a summary report
motif report analysis-output.json

# Generate your Vibe Report (no analysis needed)
motif vibe-report --name "Your Name"

Commands

motif extract

Extract conversations from AI coding tools into ~/.motif/conversations/.

motif extract cursor     # Extract from Cursor
motif extract claude     # Extract from Claude Code
motif extract all        # Extract from all sources

motif list

Show all extracted projects with message counts and date ranges.

motif list

motif analyze

Prepare extracted data for pattern analysis. The output is a markdown file containing your conversation data and analysis instructions — your IDE's agent reads it and follows the embedded prompt.

motif analyze --prepare                    # Analyze current project
motif analyze --prepare --project myapp    # Specify project
motif analyze --prepare --budget 50000     # Custom token budget
motif analyze --prepare --preview          # Preview session relevance scores
motif analyze --prepare --no-filter        # Skip relevance filtering
motif analyze --prepare --stats            # Show pipeline stats only

motif rules

Parse analysis JSON output and generate configuration files (CLAUDE.md, skill files, .cursorrules).

motif rules analysis.json              # Generate to ~/.motif/generated/
motif rules analysis.json --dry-run    # Preview what would be generated
motif rules analysis.json --apply      # Deploy to project/user directories

motif report

Generate a summary report from analysis output.

motif report analysis.json                     # Markdown report
motif report analysis.json --output report.md  # Custom output path

motif vibe-report

Generate a shareable HTML vibe report from all extracted conversations — a "Spotify Wrapped" for vibe coding. No analysis step required; works directly from extracted data.

motif vibe-report                              # Generate report to ~/.motif/reports/
motif vibe-report --name "Ada Lovelace"        # Personalized header
motif vibe-report -o my-report.html            # Custom output path
motif vibe-report --analysis analysis.json     # Include archetype from analysis

The report is a self-contained HTML file (dark theme, Chart.js visualizations) you can open in any browser or share directly.

Report sections:

Section	What it shows
Hero Stats	Total messages, sessions, projects, tool calls, autonomy ratio, date range
Agent Concurrency	Peak and average concurrent sessions via sweep-line algorithm, weekly time-series chart
Autonomy Ratio	Agent actions per human message, tracked over time with weekly trend chart
Project Constellation	Galaxy visualization of all projects, sized by message count
Growth Scorecard	First 25% vs last 25% of sessions — specification depth, autonomy, session depth, tool density
Personality	Swear/frustration detection with actual quotes, catchphrases, fun stats (novels typed, longest session, busiest day)

motif setup

Install the motif-analyze Cursor skill for seamless agent integration.

motif setup

What It Extracts

Cursor IDE — Reads state.vscdb, extracts user/assistant dialogue organized by project. Captures messages, file references, tool usage, and model info.

Claude Code — Reads ~/.claude/projects/ session files. Same structured output with session tracking.

Example Output

The following was generated from a real developer's Claude Code history (386 messages across 33 sessions). This developer builds a multiplayer game using AI as their sole engineering tool — they design features and direct the AI, but don't write code themselves.

Discovered Skills

session-startup — triggered 8+ times

User says "refresh yourself", "we're working in [project] today", or "we shall continue"

1. Read project README, STATUS, MEMORY, and recent git log
2. Summarize: current phase, what's working, what's next
3. Wait for user direction before acting — do not propose work

bug-fix-iteration — triggered 30+ times

User pastes error logs, console output, or says "it's still broken"

1. Read the pasted logs carefully — identify the exact error
2. Propose a targeted fix (don't refactor unrelated code)
3. Apply the fix
4. Ask user to test and report back

deploy-production — triggered 8+ times

User says "deploy", "push to production", or "ship it"

1. cd to project root
2. Deploy server to Fly.io with --local-only flag
3. Deploy client from client/ subdirectory to Vercel
4. Verify both deployments succeeded

Identified Rules

Rule	What it enforces	Evidence
no-regressions	Never break existing functionality when adding new features	"you broke the camera switching again"
keep-it-simple	Solve the exact problem stated. Don't add features the user didn't ask for.	"I just wanted to fix the button, not refactor the whole component"
step-by-step	When manual action is required, provide numbered lists with exact commands. Don't explain theory.	"just tell me what to type"
no-log-flooding	Don't make changes that cause console log flooding. Add reconnection limits.	"the logs are going crazy again"

Communication Style

Aspect	Pattern
Brevity	Terse and direct. 1-3 sentences, minimal punctuation, frequent lowercase.
Feedback	Reports results factually. Pastes logs when things break. Says "it works" when things work.
Corrections	Patient but persistent. Will paste logs repeatedly. Pushes back when AI goes in circles.
Proactivity	High. Expects the agent to execute rather than explain options.

Generated CLAUDE.md (excerpt)

## Agent Behavior

### Rules

1. Never break existing functionality when adding new features.
2. Solve the exact problem stated. Don't add features the user didn't ask for.
3. Use refs for values accessed in callbacks/closures, not React state.
4. Never paste secrets in responses or store them insecurely.
5. When manual action is required, provide numbered lists with exact commands.
6. Don't make changes that cause console log flooding.
7. Follow the project's documented deployment process exactly.
8. Provide debug/test buttons for visual features so they can be tested in isolation.

## Workflow Triggers

| When you're... | Load this file |
|---|---|
| User says 'refresh yourself' or 'we shall continue' | session-startup/SKILL.md |
| User pastes error logs or says 'it's still broken' | bug-fix-iteration/SKILL.md |
| User says 'deploy' or 'ship it' | deploy-production/SKILL.md |

Full example output (analysis JSON, generated CLAUDE.md, skill files, report): examples/

Sample Vibe Report

Generated from a real Cursor history — 10,973 sessions across 72 projects over 13 months.

motif extract all
motif vibe-report --name "Your Name"
# Open the HTML file in any browser

License

MIT