Prompt Engineering

Prompt engineering is the art of crafting effective instructions for AI models like Kilo Code. Well-written prompts lead to better results, fewer errors, and a more efficient workflow.

General Principles

• Be Clear and Specific: Clearly state what you want Kilo Code to do. Avoid ambiguity.

  • Bad: Fix the code.
  • Good: Fix the bug in the calculateTotal function that causes it to return incorrect results.

• Provide Context: Use Context Mentions to refer to specific files, folders, or problems.

  • Good: @/src/utils.ts Refactor the calculateTotal function to use async/await.

• Break Down Tasks: Divide complex tasks into smaller, well-defined steps.

• Give Examples: If you have a specific coding style or pattern in mind, provide examples.

• Specify Output Format: If you need the output in a particular format (e.g., JSON, Markdown), specify it in the prompt.

• Iterate: Don't be afraid to refine your prompt if the initial results aren't what you expect.

Thinking vs. Doing

It's often helpful to guide Kilo Code through a "think-then-do" process:

1. Analyze: Ask Kilo Code to analyze the current code, identify problems, or plan the approach.
2. Plan: Have Kilo Code outline the steps it will take to complete the task.
3. Execute: Instruct Kilo Code to implement the plan, one step at a time.
4. Review: Carefully review the results of each step before proceeding.

Using Custom Instructions

You can provide custom instructions to further tailor Kilo Code's behavior. There are two types of custom instructions:

• Global Custom Instructions: Apply to all modes.
• Mode-Specific Custom Instructions: Apply only to a specific mode (e.g., Code, Architect, Ask, Debug, or a custom mode).

Custom instructions are added to the system prompt, providing persistent guidance to the AI model. You can use these to:

• Enforce coding style guidelines.
• Specify preferred libraries or frameworks.
• Define project-specific conventions.
• Adjust Kilo Code's tone or personality.

See the Custom Instructions section for more details.

Handling Ambiguity

If your request is ambiguous or lacks sufficient detail, Kilo Code might:

• Make Assumptions: It might proceed based on its best guess, which may not be what you intended.
• Ask Follow-Up Questions: It might use the ask_followup_question tool to clarify your request.

It's generally better to provide clear and specific instructions from the start to avoid unnecessary back-and-forth.

Providing Feedback

If Kilo Code doesn't produce the desired results, you can provide feedback by:

• Rejecting Actions: Click the "Reject" button when Kilo Code proposes an action you don't want.
• Providing Explanations: When rejecting, explain why you're rejecting the action. This helps Kilo Code learn from its mistakes.
• Rewording Your Request: Try rephrasing your initial task or providing more specific instructions.
• Manually Correcting: If there are a few small issues, you can also directly modify the code before accepting the changes.

Examples

Good Prompt:

@/src/components/Button.tsx Refactor the Button component to use the useState hook instead of the useReducer hook.

Bad Prompt:

Fix the button.

Good Prompt:

Create a new file named utils.py and add a function called calculate_average that takes a list of numbers and returns their average.

Bad Prompt:

Write some Python code.

Good Prompt:

@problems Address all errors and warnings in the current file.

Bad Prompt:

Fix everything.

By following these tips, you can write effective prompts that get the most out of Kilo Code's capabilities.