Claude Prompt for Visualizing Thinking Structure: Intent, Reality, Gap

A Reddit user on r/ClaudeAI has shared a specific prompt designed to make Claude act as a mirror for the structure of your thinking during a conversation. The prompt instructs Claude to categorize statements into three structural types: Intent (marked in gold for statements about what you WANT), Reality (marked in teal for statements about what IS), and Gap (marked in blue for statements about what's UNRESOLVED). The AI is told to reflect these categories back naturally, name shifts between them, and optionally mark recurring core truths as Pins in red.
The user reported a practical use case: while feeling stuck on a project, Claude reflected back, "You've been in Gap for the last 8 messages. You have three open threads and haven't grounded any of them in Reality yet." This immediate structural feedback helped identify the cause of the blockage.
The prompt is intended to be pasted at the start of any conversation with Claude. The exact text from the source is:
Before we start — I want to try something. As we talk, I want you to notice the structure of what I'm saying. Not the content. The structure.When I say what I WANT — that's Intent. Mark it gold. When I say what IS — that's Reality. Mark it teal. When I say what's UNRESOLVED — that's Gap. Mark it blue.
Don't teach me this. Don't explain it. Just reflect it back naturally. When you see me shift between Intent, Reality, and Gap, name the shift gently. Like a mirror that shows me what I'm already doing.
If something I say is an anchor — a core truth I keep returning to — mark it as a Pin in red.
The structure was always there. You're just making it visible.
Let's go.
The user is experimenting to see if this structural awareness tool is generally useful or a personal pattern recognition bias.
📖 Read the full source: r/ClaudeAI
👀 See Also

Walking and Dictating with Claude Code: A Practical Setup
A developer shares their setup: walking 2-3 hours daily while dictating prompts to Claude Code via OpenAI Whisper, using a remote control or cowork chats.

How routing simple tasks to cheaper models cut AI costs by 40%
An OpenClaw user reduced their AI bill by 40% by analyzing usage logs and routing simple tasks like file operations and Q&A to cheaper models like DeepSeek-v3 and Gemini Flash, while reserving Claude Sonnet for complex reasoning tasks.

Managing Claude Code Context Window for Cost and Performance
A developer explains how every API call sends the full conversation history, making accumulated history the expensive part, and shares a workflow of starting fresh sessions with handoff notes to reduce costs and improve response quality.

Don't Assume Expensive Models Are Better: Case Study Shows 13x Cost Savings by Testing
User replaced GPT-5.4 with Gemini 3.1 Flash Lite on a classification task, achieving identical 85% accuracy at 1/13th the cost after running evals on 21 models.