Prompt
Troubleshoot prompt output formatting after a prompt change
Latest observation
Sure — I can help troubleshoot that.
To pinpoint the formatting issue after the prompt change, please share:
- The old prompt and the new prompt
- A sample input
- The expected output format
- The actual output format
- What model/runtime you’re using (if relevant)
If you want, paste them in this template:
Old prompt:
...
New prompt:
...
Input:
...
Expected output:
...
Actual output:
...
Once I have that, I can help identify whether the issue is:
- prompt wording causing the model to ignore structure,
- a delimiter / formatting mismatch,
- the model drifting from schema,
- or a post-processing/parsing issue in your app.
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
Want this interpreted for your brand?
Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.