Hi everyone,
I’m working on a ChatGPT App with several tools that help users with travel-related tasks, such as:
- comparing travel insurance options
- finding eSIM/mobile data plans for a destination
- checking visa or entry requirements
- finding airport lounges or VIP lounge access
I’m trying to understand how much we can improve tool discovery through metadata and prompt-style descriptions.
For example, if a user says:
“Do I need internet for Japan?”
“Can I wait comfortably at Madrid airport?”
“Do I need a visa for Canada with an Argentine passport?”
I want ChatGPT to correctly infer the relevant installed App/tool, even when the user does not mention the exact tool category directly.
Questions:
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How much does ChatGPT rely on the app description, tool names, tool descriptions, and parameter descriptions when deciding whether to call a tool from an installed App?
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Is it recommended to write tool descriptions using explicit intent patterns like “Use this when the user wants…”?
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Should tool descriptions include indirect examples such as “internet abroad”, “mobile data in Europe”, “airport lounge access”, or “entry requirements”?
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Is there a risk of adding too many synonyms or examples and making the tool appear too broad?
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What is the best way to test precision and recall for tool discovery?
For example, should we create a prompt set with:- direct prompts
- indirect prompts
- negative prompts where the tool should not be called
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For purchase-related flows, is it better to separate browsing tools from checkout tools?
Example:- one tool to browse eSIM plans
- another tool only when the user chooses a specific plan or clearly asks to purchase
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Are there any current best practices for improving installed App/tool discovery without making metadata look like keyword stuffing?
Any guidance, examples, or documentation references would be appreciated.