🔍 Extract and analyze your Claude Code conversation history to discover usage patterns, generate insights, and create custom slash commands from your prompting style.

The sorta-descriptive Python script takes a text file of image descriptions generated by MidJourney and sorts them into nine columns in a CSV file.

Local Python analyzer for Claude session transcripts with token usage reports and prompt insights.

A new package designed to facilitate the extraction of structured insights from user prompts related to the domain of autonomous AI agents and their potential vulnerabilities. Given an input text desc

A prompt-engineering framework that analyzes naïve prompts using a six-component Prompt Composition Framework (C1–C6), computes a Prompt Quality Score (PQS), transforms prompts into fully structured versions, and compares prompt quality through deterministic evaluation and LLM execution.

A recipe for any AI agent to build a self-improving theory-of-mind model of its user from interaction logs (feedback precognition). What you mind is what you get.