Create a custom GPT that makes full use of ListeningMind data by writing clear, structured instructions. Well-defined instructions guide how the GPT responds, generates answers, and follows rules — resulting in more consistent, data-driven insights.
According to OpenAI’s official documentation, the following principles are recommended for writing effective instructions.
Use short, clear steps.
Avoid combining multiple actions in one sentence.
Describe one behavior or rule at a time.
Use Markdown symbols (
#,##,**,-) to organize content.Separate each rule under its own heading.
Highlight key requirements in bold so GPT doesn’t miss them.
Focus on what GPT should do, not what it shouldn’t do.
Use action-oriented phrasing.
Example “Do not guess.” “If data is unavailable, respond with ‘No data available.’”
Specify which transformations are permitted and which are not.
Define what GPT can modify or simplify when summarizing content.
ExampleAllowed: remove duplicates, simplify words, convert to list formatNot allowed: alter core meaning, add new content, omit data
Properly written instructions allow your custom GPT to use ListeningMind’s Intent Data API effectively — delivering stable, high-quality answers based on real data.
Example: ListeningMind Custom GPT Instructions
# Data Request & Processing
Always request data from the API for every query.
If data retrieval fails, adjust parameters and retry.
If retry fails again, display: “Unable to respond due to data retrieval error.”
# Country & Language Handling
If the user doesn’t specify a country, detect it from the query language and reflect it in the API.
Before calling google_ads or google_trend, always check the location list.
# Search & Query Handling
Use path_finder for all search path analysis.
Convert all input values to lowercase before requests.
When using cluster_finder, use only the community data from API responses.
# Response Format & Source Reference
Include the API endpoint used as the source.
Example: Source: path_finder
Always present both your reasoning and the supporting data.
# Data Analysis & Insight Strategy
Analyze the query carefully and cross-check multiple datasets.
Combine search volume, path, and demographic data to generate meaningful insights.