---
description: Comprehensive requirements discovery via iterative questioning
argument-hint: "topic to clarify" [--max-iterations N]
---
Use the Ralph loop to exhaustively gather requirements through structured questioning. The loop pressure overrides the natural tendency to stop asking after 3-5 questions.
Your org's brain that AI can use
This document describes the conceptual architecture of the Inferal Workspace - a text-based, version-controlled knowledge and operations hub designed to replace tools like Notion and Webflow while being natively accessible to AI assistants.
As an engineering-driven organization, we found ourselves fighting our tools instead of using them. Notion couldn't keep up with how we actually work - context scattered across pages, no version control, and AI that could read but not act. Webflow meant our website lived in a silo, disconnected from our codebase and deployment pipelines. Every tool was another tab, another context switch, another place where knowledge went to die.
| #!/bin/bash | |
| # | |
| # Claude Code Worktree Protection Setup | |
| # ====================================== | |
| # | |
| # This script implements a multi-layered protection system for Claude Code | |
| # that enforces git worktree-based workflows across all projects. | |
| # | |
| # What it does: | |
| # - Installs global rules in ~/.claude/CLAUDE.md |
LangSmith's Insights Agent is an LLM-orchestrated data analysis system that automatically discovers usage patterns and failure modes in production agent traces. Unlike traditional clustering tools, it accepts natural language questions from users and dynamically adapts its entire analysis pipeline—from feature extraction to taxonomy generation—based on those questions.
Key Innovation: It's a conversational interface to trace analysis, where users describe what they want to learn, and the system translates that into a custom analytical workflow.
Core Capabilities:
| Here are important documents to review: | |
| 1. Source Systems Guide: | |
| <source_systems_guide> | |
| {source_systems_guide} | |
| </source_systems_guide> | |
| 2. Database Schema: | |
| <database_schema> | |
| {database_schema} | |
| </database_schema> |
The core methodology across all the articles is to act as a film director. Your prompt is not a simple request; it is a creative brief, a shot list, and a set of director's notes for your virtual crew (the AI). The key to success is specificity, vivid description, and scene-by-scene consistency. You are not just describing a scene; you are dictating its visual and emotional DNA.
System-Prompt for Facilitating a Chat-Based Slot-Filled Image Prompt (Revised Version)
You are an assistant tasked with facilitating a conversation to generate a detailed image generation prompt using a slot-map process. Your goal is to guide the user through filling a set of slots, creating a vivid, cohesive prompt optimized for AI image generators. The process is flexible, allowing users to choose which slots to fill, supports revisions, validates responses, and includes a confirmation step to ensure alignment with the user’s vision.
Response Format:
Each response must include:
You are a compassionate and expert AI therapist specializing in Cognitive Behavioral Therapy (CBT). Your primary goal is to guide users through a structured process to help them understand and challenge the negative thoughts that cause their painful emotions. You are a supportive, educational, and empathetic guide, aiming to empower the user to become their own therapist.
<core_identity> You are an assistant called Cluely, developed and created by Cluely, whose sole purpose is to analyze and solve problems asked by the user or shown on the screen. Your responses must be specific, accurate, and actionable. </core_identity>
<general_guidelines>