Many people have watched many prompt tutorials, but when they actually use them, they still say:

"Help me write..."

The problem isn't the tool, but the input is too casual.

The following are not "theories," but practical and effective writing methods that have been proven through use.

1. General Task Template (Most Practical)

This can cover 80% of scenarios:

Background:
(Your current situation)

Task:
(What you want the AI to do)

Requirements:
1.
2.
3.

Output Format:
(List / Table / Code / Step-by-step)

Example:

Background: I am building a blog system
Task: Help me design the comment module
Requirements:
1. Support pagination
2. Support replies
3. Implement as simply as possible
Output Format: Step-by-step explanation + simple code example

2. Code Optimization Prompts

Many people only say "Help me optimize my code," which is useless.

Use this directly:

Please optimize the following code for me:
1. Improve performance
2. Reduce redundant logic
3. Enhance readability
4. Mark the modified points
5. Explain the optimization reasons

3. Debugging Specific Prompts

More effective than "What's wrong?":

Here is my code and the error message:
(Paste code)

Please help me to:
1. Identify the cause of the problem
2. Provide a modification plan
3. Explain why this error occurred

4. Writing Articles / Content Generation

The key to avoiding empty talk is to limit the output.



Write an article about (topic):

Requirements:
1. Target audience: (target audience)
2. No concepts, just practical steps
3. Include 2-3 real-world examples
4. Concise language, avoid clichés

Output structure:
1. Problem
2. Solution
3. Examples

5. Style Imitation Prompt

This is much better than "write an article":

Refer to the style of the following content:

(Paste example)

Please write content about (topic) in a similar style

6. Deconstruct Complex Problems

Don't ask everything at once, use this method:

Please provide the overall idea first, without going into details

And then:

Expand Step 2 and provide specific implementation details.

7. Limit the Scope (Very Important)

Prevent the output from becoming too broad:

Analyze only from (a specific perspective), do not expand on other content.

For example:

Analyze performance issues solely from the database perspective.