AI Coding Assistant Prompts

AI coding assistants like Cursor, GitHub Copilot, and Claude Code have transformed how developers write software, but their output quality depends heavily on how you configure and prompt them. A vague instruction like "fix this bug" produces very different results than a prompt that includes the error message, relevant context, and the expected behavior. The gap between mediocre and excellent AI-assisted coding is almost entirely about prompting.

Each coding assistant has its own configuration layer -- Cursor uses .cursorrules files, Claude Code reads CLAUDE.md, and Copilot supports custom instructions. These files act as persistent system prompts that shape every interaction. Getting them right means your assistant understands your codebase conventions, preferred libraries, testing patterns, and code style from the start, without you repeating yourself in every prompt.

Browse our curated collection of coding assistant prompts, configuration templates, and workflow tips. Save the ones that fit your stack to your PromptingBox workspace, then pull them into your editor with MCP integration whenever you start a new project.

Coding Assistant Prompts

Copy these prompts to get better results from Cursor, Copilot, Claude Code, and other AI coding tools.

Context-Aware Code Completion

Complete the following {{language}} function based on the surrounding context.

File: {{file_path}}
Project: {{project_description}}

Existing code:
{{surrounding_code}}

Function to complete:
{{function_signature}}

Requirements:
- Follow the coding style and patterns visible in the surrounding code
- Use the same libraries/imports already present in the file
- Include proper error handling consistent with the project's approach
- Add inline comments only for non-obvious logic
- Do not modify any existing code — only fill in the function body
languagefile_pathproject_descriptionsurrounding_codefunction_signature

Why it works: Providing the surrounding code and project context lets the model match existing patterns exactly. The constraint against modifying existing code prevents unwanted side effects.

Inline Code Suggestion

I am writing {{language}} code in a {{framework}} project. Suggest the next 3-5 lines of code based on what I have written so far.

Current file context:
{{current_code}}

Cursor position: after line {{line_number}}

Rules:
- Match the existing indentation and formatting style exactly
- Use variables and functions already defined in scope
- Prefer the simplest correct implementation
- If there are multiple valid approaches, pick the one most consistent with the existing code
- Return ONLY the suggested lines, no explanation
languageframeworkcurrent_codeline_number

Why it works: Constraining suggestions to match existing style and scope produces insertions that feel native to the codebase. The 'no explanation' rule mimics real inline completion behavior.

Code Explanation

Explain the following {{language}} code to a {{audience_level}} developer.

{{code_block}}

Structure your explanation as:
1. **Purpose**: What does this code do in one sentence?
2. **How it works**: Walk through the logic step by step. For each significant line or block, explain what it does and why.
3. **Key concepts**: List any design patterns, algorithms, or language features used (e.g., closures, memoization, dependency injection)
4. **Potential issues**: Note any edge cases, performance concerns, or maintenance risks
5. **Usage example**: Show a brief example of how to call/use this code
languageaudience_levelcode_block

Why it works: The audience level parameter adjusts complexity automatically. Requiring a usage example ensures the explanation is practical, not just theoretical.

Code Refactoring

Refactor the following {{language}} code to improve {{refactoring_goal}}.

Original code:
{{original_code}}

Constraints:
- Maintain the exact same external behavior (inputs and outputs must not change)
- Do not add new dependencies unless absolutely necessary
- Follow {{style_guide}} conventions

Provide:
1. The refactored code
2. A bullet list of every change made and why
3. Before/after comparison of any metrics that changed (lines of code, cyclomatic complexity, number of parameters)
4. Any risks or trade-offs introduced by the refactoring
languagerefactoring_goaloriginal_codestyle_guide

Why it works: Explicitly stating that external behavior must be preserved prevents breaking changes. Requiring a change log with rationale makes the refactoring reviewable and educational.

Test Generation

Generate comprehensive tests for the following {{language}} code using {{test_framework}}.

{{code_to_test}}

Test coverage requirements:
1. Happy path: Test the primary expected behavior with typical inputs
2. Edge cases: Empty inputs, boundary values, maximum/minimum values
3. Error cases: Invalid inputs, null/undefined values, type mismatches
4. Integration points: Test interactions with dependencies (mock external calls)

For each test:
- Use descriptive test names that explain the scenario: "should [expected behavior] when [condition]"
- Follow the Arrange-Act-Assert pattern
- Include at least one assertion per test
- Add a brief comment explaining why each edge case matters

Generate at least {{min_tests}} tests.
languagetest_frameworkcode_to_testmin_tests

Why it works: Categorizing tests by type (happy path, edge, error, integration) ensures comprehensive coverage. The AAA pattern and naming convention produce tests that serve as documentation.

Documentation Generator

Generate documentation for the following {{language}} code.

{{code_to_document}}

Documentation format: {{doc_format}}

For each public function/method/class, include:
- A one-line summary of what it does
- @param descriptions for all parameters with types and constraints
- @returns description with type and possible values
- @throws / @raises for all error conditions
- @example with a realistic usage example
- @since version (use {{version}})

For the module/file level:
- A brief overview of the module's purpose
- How it fits into the larger system
- Any prerequisites or setup required

Style: Write for a developer who has never seen this code before. Be precise, not verbose.
languagecode_to_documentdoc_formatversion

Why it works: Structured doc annotations (@param, @returns, @throws) are parseable by IDE tooling. The 'never seen this code' guideline prevents assumed-knowledge gaps.