Prompt Configurations

Prompt Configurations allow administrators to customize the AI prompts used across TestPlanIt's LLM-powered features. By defining different prompt configurations, you can fine-tune how AI generates test cases, parses markdown imports, selects test cases, and assists with writing.

Overview

Each prompt configuration contains prompts for the following AI features:

• Test Case Generation — Controls how AI generates test cases from requirements and documents
• Markdown Test Case Parsing — Controls how AI maps markdown content to test case fields during import
• Smart Test Case Selection — Controls how AI selects relevant test cases when building test runs
• Editor Writing Assistant — Controls how AI assists with writing and improving content in rich text editors
• LLM Connection Test — A simple prompt used to verify the AI provider connection is working

Prompt Resolution

When an AI feature is invoked, TestPlanIt resolves which prompt to use in the following order:

1. Project-specific — If the project has a prompt configuration assigned, that configuration's prompt is used
2. System default — If no project-specific configuration exists, the system default prompt configuration is used
3. Hard-coded fallback — If no database configurations exist, built-in fallback prompts are used as a safety net

This resolution chain ensures AI features always work, even before any prompt configurations are created.

Managing Prompt Configurations

Accessing the Page

Navigate to Administration → Prompt Configurations in the admin menu (under the Tools & Integrations section).

Creating a Configuration

1. Click the Add Prompt Configuration button
2. Fill in the configuration details:
   • Name — A unique name for this configuration (required)
   • Description — Optional description of the configuration's purpose
   • Is Default — Whether this should be the system-wide default configuration
   • Is Active — Whether this configuration is available for use
3. Configure prompts for each feature using the accordion sections:
   • LLM Integration — Optionally assign a specific LLM integration to this prompt (see Per-Prompt LLM Assignment below)
   • Model Override — Optionally override the model used by the selected LLM integration
   • System Prompt — Instructions that set the AI's behavior and context (required)
   • User Prompt — The template sent with each request, supporting {{variable}} placeholders
   • Temperature — Controls randomness (0 = deterministic, 2 = most creative, default: 0.7)
   • Max Output Tokens — Maximum length of AI responses (default: 2048)
4. Click Save to create the configuration

Default prompts are pre-filled for each feature when creating a new configuration.

Editing a Configuration

Click the edit icon on any configuration row to modify its settings. All fields can be updated, including individual feature prompts.

Setting a Default

Use the Default toggle in the table to set a configuration as the system default. Only one configuration can be the default at a time. Setting a new default automatically:

• Removes the default flag from the previous default
• Forces the new default to be active

The default configuration cannot be deleted.

Deleting a Configuration

Click the delete icon to remove a configuration. Deletion is a soft delete — the configuration is marked as deleted but retained in the database. Any projects using a deleted configuration will fall back to the system default.

Per-Prompt LLM Assignment

Each prompt within a configuration can optionally use a different LLM integration and model, allowing teams to optimize cost, speed, and quality per AI feature. For example, you might assign a fast, low-cost model to connection tests and a powerful model to test case generation — all within the same prompt configuration.

How to Configure

1. Open the prompt config editor by clicking Add Prompt Configuration or the edit icon on an existing configuration
2. Expand any feature accordion (Test Case Generation, Markdown Parsing, etc.)
3. At the top of each accordion, two selectors are available:
   • LLM Integration — A dropdown listing all active LLM integrations. Select an integration to assign it to this specific prompt. Choose Project Default (clear) to remove the assignment and fall back to the project's default integration.
   • Model Override — A dropdown listing models available from the selected integration. This selector is disabled until an integration is chosen. Choose Integration Default (clear) to remove the model override and use the integration's default model.
4. Repeat for any other feature accordions you want to customize
5. Click Save to persist the configuration

Behavior Notes

• Clearing the LLM Integration also clears the Model Override, preventing a stale model value from persisting against a different integration
• When no per-prompt integration is assigned, the resolution chain falls back to the next level (see below)
• The prompt configuration table shows an LLM column with one of three states:
  • Project Default — No prompts in this configuration have a per-prompt assignment
  • Integration name — All prompts use the same integration
  • N LLMs badge — Prompts use different integrations across features

See LLM Resolution Chain for how TestPlanIt determines which LLM is used when multiple levels of configuration exist.

Project Assignment

Prompt configurations can be assigned to individual projects:

1. Go to Project Settings → AI Models
2. In the Prompt Configuration section, select the desired configuration from the dropdown
3. Choose Use system default to inherit the system default, or select a specific configuration

This allows different projects to use different AI behaviors — for example, a security-focused project might use prompts that emphasize security test scenarios.

Prompt Variables

User prompts can include {{variable}} placeholders that are replaced at runtime with actual values. The available variables depend on the feature:

Feature	Common Variables
Test Case Generation	{{sourceContent}}, {{fields}}, {{numberOfCases}}
Markdown Parsing	{{markdownContent}}, {{fields}}
Smart Test Case Selection	{{testCases}}, {{context}}
Editor Writing Assistant	{{content}}, {{instruction}}

Best Practices

• Start with defaults — The built-in prompts are well-tested. Create custom configurations only when you need specific behavior.
• Test before deploying — After creating a new configuration, assign it to a test project first to verify the AI output quality.
• Use descriptive names — Name configurations based on their purpose (e.g., "Security Testing Focus", "API Testing Optimized").
• Keep one default — Always maintain a system default configuration as a reliable fallback.
• Document your changes — Use the description field to explain what makes each configuration different from the default.