{"id":4900,"date":"2025-10-22T21:02:16","date_gmt":"2025-10-22T21:02:16","guid":{"rendered":"https:\/\/makeaiprompt.com\/blog\/code-generation-agent-prompt\/"},"modified":"2025-10-22T21:02:16","modified_gmt":"2025-10-22T21:02:16","slug":"code-generation-agent-prompt","status":"publish","type":"post","link":"https:\/\/makeaiprompt.com\/blog\/code-generation-agent-prompt\/","title":{"rendered":"Code Generation Agent Prompt"},"content":{"rendered":"<div style=\"margin-top: 0px; margin-bottom: 0px;\" class=\"sharethis-inline-share-buttons\" ><\/div><div style=\"padding:20px;border-radius:8px;margin-bottom:20px;\">\n<h3 style=\"margin-top:0;\">About Prompt<\/h3>\n<ul style=\"list-style: none; padding: 0;\">\n<li style=\"margin:8px 0;padding:8px;border-radius:4px;box-shadow:0 1px 3px rgba(255, 255, 255, 1);\"><strong>Prompt Type<\/strong> &#8211; Dynamic<\/li>\n<li style=\"margin:8px 0;padding:8px;border-radius:4px;box-shadow:0 1px 3px rgba(255, 255, 255, 1);\"><strong>Prompt Platform<\/strong> &#8211; ChatGPT, Grok, Deepseek, Gemini, Copilot, Midjourney, Meta AI and more<\/li>\n<li style=\"margin:8px 0;padding:8px;border-radius:4px;box-shadow:0 1px 3px rgba(255, 255, 255, 1);\"><strong>Niche<\/strong> &#8211; Development<\/li>\n<li style=\"margin:8px 0;padding:8px;border-radius:4px;box-shadow:0 1px 3px rgba(255, 255, 255, 1);\"><strong>Language<\/strong> &#8211; English<\/li>\n<li style=\"margin:8px 0;padding:8px;border-radius:4px;box-shadow:0 1px 3px rgba(255, 255, 255, 1);\"><strong>Category<\/strong> &#8211; Programming<\/li>\n<li style=\"margin:8px 0;padding:8px;border-radius:4px;box-shadow:0 1px 3px rgba(255, 255, 255, 1);\"><strong>Prompt Title<\/strong> &#8211; Code Generation Agent Prompt<\/li>\n<\/ul>\n<\/div>\n<h3 style=\"margin-top:0;\">Prompt Details <\/h3>\n<div id=\"promptContent\">Of course. Here is an optimized, dynamic AI prompt for a Code Generation Agent, designed for all AI platforms and adhering to modern prompt engineering best practices. It is followed by a practical example.<\/p>\n<p>&#8212;<\/p>\n<p>### **Optimized Dynamic AI Prompt for Code Generation**<\/p>\n<p>**Prompt Title:** The Expert Co-Pilot: A Dynamic Code Generation Template<\/p>\n<p>**Prompt Goal:** To generate high-quality, production-ready, and context-aware code by providing the AI with a comprehensive and structured set of requirements. This template is designed to be filled in by a developer to minimize ambiguity and maximize the accuracy of the generated output.<\/p>\n<p>&#8212;<\/p>\n<p>### **Prompt Template**<\/p>\n<p>&#8220;`<br \/>\n# AI Code Generation Request<\/p>\n<p>## 1. ROLE &#038; GOAL<\/p>\n<p>You are to act as a **[Specify a detailed persona, e.g., &#8220;Expert Senior Python Developer specializing in secure and scalable REST APIs using the FastAPI framework&#8221;]**. Your primary goal is to generate clean, efficient, and well-documented code that perfectly aligns with the detailed specifications provided below. Think critically about security, performance, and maintainability.<\/p>\n<p>## 2. PROJECT CONTEXT &#038; ENVIRONMENT<\/p>\n<p>This code will be part of a larger project. Understanding its context is crucial for generating integrated and consistent code.<\/p>\n<p>*   **Project Description:** `[Briefly describe the project, e.g., &#8220;A customer relationship management (CRM) platform for small businesses.&#8221;]`<br \/>\n*   **Technology Stack:**<br \/>\n    *   **Language &#038; Version:** `[e.g., Python 3.11]`<br \/>\n    *   **Framework(s) &#038; Version(s):** `[e.g., FastAPI 0.104, Pydantic V2]`<br \/>\n    *   **Database &#038; ORM\/Library:** `[e.g., PostgreSQL 15, SQLAlchemy 2.0 with asyncpg driver]`<br \/>\n    *   **Key Libraries:** `[e.g., bcrypt for password hashing, httpx for testing, alembic for migrations]`<br \/>\n*   **Coding Standards &#038; Style Guide:** `[e.g., &#8220;Strictly adhere to PEP 8 for Python. Use Black for formatting and isort for imports.&#8221;]`<br \/>\n*   **File Structure &#038; Location (if relevant):** `[e.g., &#8220;This code should be placed in `app\/api\/v1\/endpoints\/users.py`. It needs to import the database session from `app\/db\/session.py` and Pydantic models from `app\/schemas\/user.py`.&#8221;]`<\/p>\n<p>## 3. PRIMARY TASK DEFINITION<\/p>\n<p>Your main task is to: **[Describe the main task clearly and concisely, e.g., &#8220;Generate a complete FastAPI endpoint function to handle new user registration.&#8221;]`**<\/p>\n<p>## 4. DETAILED SPECIFICATIONS<\/p>\n<p>Follow these technical requirements precisely.<\/p>\n<p>*   **Function\/Class Signature:**<br \/>\n    *   **Name:** `[e.g., create_user]`<br \/>\n    *   **Parameters &#038; Type Hints:** `[e.g., `user_in: schemas.UserCreate`, `db: AsyncSession = Depends(get_db)`]`<br \/>\n    *   **Return Value &#038; Type Hint:** `[e.g., `-> schemas.UserRead`]`<br \/>\n    *   **Decorator(s):** `[e.g., `@router.post(&#8220;\/&#8221;, response_model=schemas.UserRead, status_code=201)`]`<\/p>\n<p>*   **Core Logic (Step-by-Step):**<br \/>\n    1.  `[Describe the first logical step, e.g., &#8220;Check if a user with the provided email already exists in the database.&#8221;]`<br \/>\n    2.  `[Describe the second logical step, e.g., &#8220;If the user exists, raise an `HTTPException` with a 409 Conflict status code and a clear error message.&#8221;]`<br \/>\n    3.  `[Describe the third logical step, e.g., &#8220;If the user does not exist, hash the user&#8217;s plain-text password using the `bcrypt` library.&#8221;]`<br \/>\n    4.  `[Continue with all necessary steps, e.g., &#8220;Create a new `models.User` SQLAlchemy instance, populating it with the validated data from the Pydantic model and the newly hashed password.&#8221;]`<br \/>\n    5.  `[e.g., &#8220;Add the new user instance to the database session, commit the transaction, and refresh the instance to get the database-generated values (like the ID).&#8221;]`<br \/>\n    6.  `[e.g., &#8220;Return the newly created user object, which will be automatically serialized by FastAPI using the `UserRead` response model.&#8221;]`<\/p>\n<p>*   **Input Data Structure &#038; Validation:**<br \/>\n    *   **Description:** `[Describe the input data, e.g., &#8220;The input will be a JSON object matching the `UserCreate` Pydantic schema.&#8221;]`<br \/>\n    *   **Example (if complex):**<br \/>\n        &#8220;`json<br \/>\n        {<br \/>\n          &#8220;email&#8221;: &#8220;test@example.com&#8221;,<br \/>\n          &#8220;password&#8221;: &#8220;a_strong_password_123&#8221;,<br \/>\n          &#8220;full_name&#8221;: &#8220;John Doe&#8221;<br \/>\n        }<br \/>\n        &#8220;`<\/p>\n<p>*   **Output Data Structure:**<br \/>\n    *   **Description:** `[Describe the successful output, e.g., &#8220;A JSON object of the created user, matching the `UserRead` Pydantic schema, which excludes the password.&#8221;]`<br \/>\n    *   **Example:**<br \/>\n        &#8220;`json<br \/>\n        {<br \/>\n          &#8220;id&#8221;: 1,<br \/>\n          &#8220;email&#8221;: &#8220;test@example.com&#8221;,<br \/>\n          &#8220;full_name&#8221;: &#8220;John Doe&#8221;,<br \/>\n          &#8220;is_active&#8221;: true<br \/>\n        }<br \/>\n        &#8220;`<\/p>\n<p>*   **Error Handling &#038; Edge Cases:**<br \/>\n    *   `[Specify an error case, e.g., &#8220;If the input email already exists in the database, return an HTTP 409 Conflict error.&#8221;]`<br \/>\n    *   `[Specify another error case, e.g., &#8220;Pydantic should automatically handle validation errors, returning an HTTP 422 Unprocessable Entity error.&#8221;]`<br \/>\n    *   `[Specify an edge case, e.g., &#8220;Ensure database connection errors are handled gracefully (FastAPI&#8217;s dependency injection and middleware may handle this, but be mindful of transaction rollbacks).&#8221;]`<\/p>\n<p>## 5. QUALITY ATTRIBUTES<\/p>\n<p>In addition to the core logic, the final code must exhibit the following qualities:<\/p>\n<p>*   **Documentation:** Generate a comprehensive docstring for the function\/class using **[e.g., Google Style or reStructuredText format]**. Explain the purpose, arguments, return value, and any exceptions it might raise. Add concise inline comments for any complex or non-obvious lines of code.<br \/>\n*   **Security:** The code must follow security best practices. **[e.g., &#8220;Do NOT store passwords in plain text. Use a strong, one-way hashing algorithm like bcrypt. Prevent SQL injection by using the ORM correctly.&#8221;]`**<br \/>\n*   **Performance:** The code should be efficient. **[e.g., &#8220;Make database queries asynchronous and specific. Only select the columns you need if the query were more complex.&#8221;]`**<br \/>\n*   **Testing:** After generating the function, create a corresponding unit\/integration test file using the **[e.g., `pytest` framework and `httpx` for making requests to the test client]**. The tests should cover:<br \/>\n    1.  The &#8220;happy path&#8221; (successful user creation).<br \/>\n    2.  The error case (attempting to create a user with a duplicate email).<br \/>\n    3.  A validation error case (e.g., providing an invalid email format).<\/p>\n<p>## 6. OUTPUT FORMAT<\/p>\n<p>Please provide your response in the following structure:<\/p>\n<p>1.  **Brief Explanation:** A short paragraph explaining your approach and any important decisions made.<br \/>\n2.  **Main Code:** The complete, production-ready code for the requested feature, inside a single, well-formatted markdown code block with the appropriate language identifier (e.g., ` &#8220;`python `).<br \/>\n3.  **Test Code:** The complete test code in a separate markdown code block.<br \/>\n&#8220;`<\/p>\n<p>&#8212;<\/p>\n<p>### **Example of the Filled-Out Prompt in Practice**<\/p>\n<p>Here is the above template filled out for a specific, real-world task.<\/p>\n<p>&#8212;<\/p>\n<p>&#8220;`<br \/>\n# AI Code Generation Request<\/p>\n<p>## 1. ROLE &#038; GOAL<\/p>\n<p>You are to act as an **Expert Senior Python Developer specializing in secure and scalable REST APIs using the FastAPI framework**. Your primary goal is to generate clean, efficient, and well-documented code that perfectly aligns with the detailed specifications provided below. Think critically about security, performance, and maintainability.<\/p>\n<p>## 2. PROJECT CONTEXT &#038; ENVIRONMENT<\/p>\n<p>This code will be part of a larger project. Understanding its context is crucial for generating integrated and consistent code.<\/p>\n<p>*   **Project Description:** **A customer relationship management (CRM) platform for small businesses.**<br \/>\n*   **Technology Stack:**<br \/>\n    *   **Language &#038; Version:** **Python 3.11**<br \/>\n    *   **Framework(s) &#038; Version(s):** **FastAPI 0.104, Pydantic V2**<br \/>\n    *   **Database &#038; ORM\/Library:** **PostgreSQL 15, SQLAlchemy 2.0 with asyncpg driver**<br \/>\n    *   **Key Libraries:** **bcrypt for password hashing, httpx for testing, alembic for migrations**<br \/>\n*   **Coding Standards &#038; Style Guide:** **Strictly adhere to PEP 8 for Python. Use Black for formatting and isort for imports.**<br \/>\n*   **File Structure &#038; Location (if relevant):** **This code should be placed in `app\/api\/v1\/endpoints\/users.py`. It needs to import the database session from `app\/db\/session.py`, Pydantic schemas from `app\/schemas\/`, and the User model from `app\/models\/user.py`.**<\/p>\n<p>## 3. PRIMARY TASK DEFINITION<\/p>\n<p>Your main task is to: **Generate a complete FastAPI endpoint function to handle new user registration.**<\/p>\n<p>## 4. DETAILED SPECIFICATIONS<\/p>\n<p>Follow these technical requirements precisely.<\/p>\n<p>*   **Function\/Class Signature:**<br \/>\n    *   **Name:** `create_user`<br \/>\n    *   **Parameters &#038; Type Hints:** `user_in: schemas.UserCreate`, `db: AsyncSession = Depends(get_db)`<br \/>\n    *   **Return Value &#038; Type Hint:** `-> models.User` (FastAPI will handle serialization via `response_model`)<br \/>\n    *   **Decorator(s):** `@router.post(&#8220;\/&#8221;, response_model=schemas.UserRead, status_code=status.HTTP_201_CREATED)`<\/p>\n<p>*   **Core Logic (Step-by-Step):**<br \/>\n    1.  **Query the database to check if a user with the `user_in.email` already exists.**<br \/>\n    2.  **If the user exists, raise an `HTTPException` with status code `409 Conflict` and the detail message &#8220;Email already registered&#8221;.**<br \/>\n    3.  **If the user does not exist, hash the `user_in.password` using `bcrypt.hashpw` with a generated salt.**<br \/>\n    4.  **Create a new `models.User` SQLAlchemy instance. Pass all attributes from `user_in` except the password. Set the `hashed_password` attribute with the result from the previous step.**<br \/>\n    5.  **Add the new user object to the async database session, commit the transaction, and refresh the instance to load the database-generated ID.**<br \/>\n    6.  **Return the newly created `models.User` object.**<\/p>\n<p>*   **Input Data Structure &#038; Validation:**<br \/>\n    *   **Description:** **The input is a JSON object matching the `schemas.UserCreate` Pydantic schema, which requires an email, a password, and a full_name.**<br \/>\n    *   **Example (if complex):**<br \/>\n        &#8220;`json<br \/>\n        {<br \/>\n          &#8220;email&#8221;: &#8220;new.user@example.com&#8221;,<br \/>\n          &#8220;password&#8221;: &#8220;VerySecurePassword!123&#8221;,<br \/>\n          &#8220;full_name&#8221;: &#8220;Jane Doe&#8221;<br \/>\n        }<br \/>\n        &#8220;`<\/p>\n<p>*   **Output Data Structure:**<br \/>\n    *   **Description:** **A JSON object of the created user, matching the `schemas.UserRead` Pydantic schema, which excludes the password and includes the `id`.**<br \/>\n    *   **Example:**<br \/>\n        &#8220;`json<br \/>\n        {<br \/>\n          &#8220;id&#8221;: 5,<br \/>\n          &#8220;email&#8221;: &#8220;new.user@example.com&#8221;,<br \/>\n          &#8220;full_name&#8221;: &#8220;Jane Doe&#8221;,<br \/>\n          &#8220;is_active&#8221;: true<br \/>\n        }<br \/>\n        &#8220;`<\/p>\n<p>*   **Error Handling &#038; Edge Cases:**<br \/>\n    *   **If the email from the payload already exists in the `users` table, the API must return an HTTP 409 Conflict error.**<br \/>\n    *   **If the input JSON fails Pydantic validation (e.g., invalid email format, missing fields), FastAPI&#8217;s default 422 Unprocessable Entity response is acceptable.**<\/p>\n<p>## 5. QUALITY ATTRIBUTES<\/p>\n<p>In addition to the core logic, the final code must exhibit the following qualities:<\/p>\n<p>*   **Documentation:** Generate a comprehensive docstring for the function using **Google Style format**. It should detail the function&#8217;s purpose, arguments (user_in, db), return value, and the `HTTPException` it can raise.<br \/>\n*   **Security:** The code must follow security best practices. **Do NOT store passwords in plain text. Use bcrypt for hashing. Rely on SQLAlchemy&#8217;s parameterization to prevent SQL injection.**<br \/>\n*   **Performance:** **The database query to check for an existing user must be asynchronous (`await db.execute(&#8230;)`).**<br \/>\n*   **Testing:** After generating the function, create a corresponding unit test file `tests\/api\/v1\/test_users.py` using the **`pytest` framework and `httpx.AsyncClient`**. The tests should cover:<br \/>\n    1.  Successful user creation (expect a 201 status code and correct data).<br \/>\n    2.  Attempting to create a user with a duplicate email (expect a 409 status code).<br \/>\n    3.  Attempting to create a user with an invalid email (expect a 422 status code).<\/p>\n<p>## 6. OUTPUT FORMAT<\/p>\n<p>Please provide your response in the following structure:<\/p>\n<p>1.  **Brief Explanation:** A short paragraph explaining your approach.<br \/>\n2.  **Main Code:** The complete Python code for the FastAPI endpoint, inside a ` &#8220;`python ` markdown block.<br \/>\n3.  **Test Code:** The complete `pytest` code in a separate ` &#8220;`python ` markdown block.<br \/>\n&#8220;`<\/p><\/div>\n<div style=\"margin-top: 40px; text-align: center;\"><button class=\"copyPostContent\" id=\"copyPostContent\">\ud83d\udccb Copy Prompt<\/button><\/div>\n<div class=\"ai-buttons\"><a href=\"https:\/\/makeaiprompt.com\">Create Your Own Prompts<\/a><a href=\"https:\/\/makeaiprompt.com\/blog\/category\/prompts\">View All Prompts<\/a><a href=\"https:\/\/makeaiprompt.com\/top-ai-tools\">Top AI Tools<\/a><a href=\"https:\/\/chatgpt.com\/\" target=\"_blank\" rel=\"noopener\">Try on ChatGPT<\/a><a href=\"https:\/\/gemini.google.com\/app\" target=\"_blank\" rel=\"noopener\">Try on Gemini<\/a><a href=\"https:\/\/aistudio.google.com\" target=\"_blank\" rel=\"noopener\">Try on Google AI Studio<\/a><a href=\"https:\/\/grok.com\" target=\"_blank\" rel=\"noopener\">Try on Grok<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Code Generation Agent Prompt: You are to act as a [Specify a detailed persona, e.g., &#8220;Expert Senior Python Developer specializing in secure and scalable REST&#8230;<\/p>\n","protected":false},"author":4,"featured_media":4899,"comment_status":"","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[3,7,5,6,4,26,8,1,30,25],"tags":[],"class_list":["post-4900","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-chatgpt-prompts","category-copilot-prompts","category-deepseek-prompts","category-gemini-prompts","category-grok-prompts","category-meta-ai-prompts","category-midjourney-prompts","category-prompts","category-sora-prompts","category-veo-prompts"],"jetpack_featured_media_url":"https:\/\/makeaiprompt.com\/blog\/wp-content\/uploads\/2025\/10\/Code-Generation-Agent-Prompt.jpg","jetpack_sharing_enabled":true,"jetpack-related-posts":[],"rttpg_featured_image_url":{"full":["https:\/\/makeaiprompt.com\/blog\/wp-content\/uploads\/2025\/10\/Code-Generation-Agent-Prompt.jpg",1200,630,false],"landscape":["https:\/\/makeaiprompt.com\/blog\/wp-content\/uploads\/2025\/10\/Code-Generation-Agent-Prompt.jpg",1200,630,false],"portraits":["https:\/\/makeaiprompt.com\/blog\/wp-content\/uploads\/2025\/10\/Code-Generation-Agent-Prompt.jpg",1200,630,false],"thumbnail":["https:\/\/makeaiprompt.com\/blog\/wp-content\/uploads\/2025\/10\/Code-Generation-Agent-Prompt-150x150.jpg",150,150,true],"medium":["https:\/\/makeaiprompt.com\/blog\/wp-content\/uploads\/2025\/10\/Code-Generation-Agent-Prompt-300x158.jpg",300,158,true],"large":["https:\/\/makeaiprompt.com\/blog\/wp-content\/uploads\/2025\/10\/Code-Generation-Agent-Prompt-1024x538.jpg",1024,538,true],"1536x1536":["https:\/\/makeaiprompt.com\/blog\/wp-content\/uploads\/2025\/10\/Code-Generation-Agent-Prompt.jpg",1200,630,false],"2048x2048":["https:\/\/makeaiprompt.com\/blog\/wp-content\/uploads\/2025\/10\/Code-Generation-Agent-Prompt.jpg",1200,630,false]},"rttpg_author":{"display_name":"AIPrompts","author_link":"https:\/\/makeaiprompt.com\/blog\/author\/aiprompts\/"},"rttpg_comment":0,"rttpg_category":"<a href=\"https:\/\/makeaiprompt.com\/blog\/category\/prompts\/chatgpt-prompts\/\" rel=\"category tag\">ChatGPT Prompts<\/a> <a href=\"https:\/\/makeaiprompt.com\/blog\/category\/prompts\/copilot-prompts\/\" rel=\"category tag\">Copilot Prompts<\/a> <a href=\"https:\/\/makeaiprompt.com\/blog\/category\/prompts\/deepseek-prompts\/\" rel=\"category tag\">Deepseek Prompts<\/a> <a href=\"https:\/\/makeaiprompt.com\/blog\/category\/prompts\/gemini-prompts\/\" rel=\"category tag\">Gemini Prompts<\/a> <a href=\"https:\/\/makeaiprompt.com\/blog\/category\/prompts\/grok-prompts\/\" rel=\"category tag\">Grok Prompts<\/a> <a href=\"https:\/\/makeaiprompt.com\/blog\/category\/prompts\/meta-ai-prompts\/\" rel=\"category tag\">Meta AI Prompts<\/a> <a href=\"https:\/\/makeaiprompt.com\/blog\/category\/prompts\/midjourney-prompts\/\" rel=\"category tag\">Midjourney Prompts<\/a> <a href=\"https:\/\/makeaiprompt.com\/blog\/category\/prompts\/\" rel=\"category tag\">Prompts<\/a> <a 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REST...","_links":{"self":[{"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/posts\/4900","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/comments?post=4900"}],"version-history":[{"count":0,"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/posts\/4900\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/media\/4899"}],"wp:attachment":[{"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/media?parent=4900"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/categories?post=4900"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/makeaiprompt.com\/blog\/wp-json\/wp\/v2\/tags?post=4900"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}