Prompts That Make ChatGPT Drop the Disclaimers and Dig Deeper

What it does

ChatGPT AutoExpert is essentially a curated set of system prompts—plus a companion Python script for the coding edition—that you feed into ChatGPT to change its behavior. The standard edition rewrites vague questions, picks an appropriate expert persona, and demands detailed, multi-turn answers with explicit reasoning. The developer edition adds slash commands, session memory export, and a file/symbol tree so ChatGPT’s Advanced Data Analysis mode can write code across multiple turns without forgetting what it was doing.

The interesting bit

The project treats prompt engineering as user-interface design: instead of accepting ChatGPT’s default tendency toward disclaimers and shallow summaries, it instructs the model to auto-select frameworks, generate Google search links to avoid hallucination, and even review its own answers for improvement. For developers, the companion script turns the ephemeral ChatGPT sandbox into a semi-persistent workspace with wheel installation and zip exports.

Key highlights

• Automatically reframes ambiguous questions into precise prompts before answering.
• Injects slash commands like /memory and self-review triggers into the conversation flow.
• Developer edition piggybacks on ChatGPT’s Jupyter kernel to edit longer code samples and maintain a file/symbol tree across turns.
• Explicitly minimizes hand-holding and generic disclaimers while demanding explicit reasoning.
• Non-commercial CC BY-NC-SA 4.0 license, which means no corporate production use without negotiating terms.

Caveats

• The developer edition requires a paid ChatGPT subscription with GPT-4 and Advanced Data Analysis enabled.
• GPT-3.5 still hallucinates the auto-generated Google search links; GPT-4 handles them reliably, according to the README.
• The entire project is a prompt-and-script bundle, not a standalone application, so it lives or dies by OpenAI’s model behavior.

Verdict

Worth a look if you spend hours in ChatGPT and are tired of coaxing it past surface-level answers. Skip it if you need a fully offline, self-hosted tool or want to embed the logic into a commercial product.