POST https://api.zatomic.ai/v1/prompts/balance
Zatomic API
- Introduction
- Versioning
- Authentication
- Workspaces
- Status codes and errors
- Token usage
- Expanding objects
- OpenAPI spec
- Prompts
- The Prompt object
- Creating a prompt
- Updating a prompt
- Deleting a prompt
- Retrieving a prompt
- Retrieving all prompts
- Generating a prompt
- Versions
- The Version object
- Creating a version
- Updating a version
- Deleting a version
- Retrieving a version
- Retrieving all versions
- Retrieving a version score
- Calculating a version score
- Retrieving a version risk
- Analyzing a version risk
- Retrieving a version balance
- Analyzing a version balance
- Retrieving a version heatmap
- Generating a version heatmap
- Improving a version
- Scoring Criteria
- The Scoring Criteria object
- The Scoring Criterion object
- Creating scoring criteria
- Updating a scoring criteria
- Deleting a scoring criteria
- Retrieving a scoring criteria
- Retrieving all scoring criteria
- Generating scoring criteria
- Creating a scoring criterion
- Updating a scoring criterion
- Deleting a scoring criterion
- Retrieving a scoring criterion
- Scoring Criteria Results
- The Scoring Criteria Results object
- Scoring
- The Scoring object
- Calculating a prompt score
- Risk
- The Risk object
- Analyzing prompt risk
- Balance
- The Balance object
- Analyzing prompt balance
- Heatmaps
- The Heatmap object
- Generating a prompt heatmap
Balance
Balance refers to the overall effectiveness of the structure and makeup of a prompt version. When the balance of a prompt version is analyzed, the prompt's content is broken down into meaningful phrases, which are then categorized to determine the balance of the prompt.
Balance analysis can be performed and retrieved on individual prompt versions using their specific balance endpoints. You can also analyze the balance for prompts without a version stored in the system by using the non-version specific endpoint.
Prompt phrases are put into one of the following categories:
| Phrase Category | Description |
|---|---|
| Instruction | Tells AI models what needs to be done. Ideal distribution is 20% - 35%. |
| Entity | Gives AI models context and specificity. Ideal distribution is 20% - 35%. |
| Concept | Defines themes and abstract ideas for AI models to consider. Ideal distribution is 15% - 30%. |
| Detail | Supporting context to help refine AI responses. Ideal distribution is 15% - 30%. |
The categories are then analyzed to determine their distribution, as one of the following:
| Category Distribution | Description |
|---|---|
| Balanced | The prompt has the right amount of phrases in that category to ensure high-quality AI responses. |
| Overused | There are too many phrases in that category that could lead to overly complex, unfocused output. |
| Underused | There aren't enough phrases in that category for the AI model to produce meaningful results. |
Endpoints