Prompt Templates for Development Teams: A Practical Guide

Why Standardization Matters

Here’s a scene that plays out daily in engineering teams:

Developer A asks Claude Code to review their pull request. They get thorough feedback on code structure, potential bugs, and performance implications. It takes them 10 minutes to write a good prompt, but the review is excellent.

Developer B asks Claude Code to review their pull request with a quick, generic prompt. They get surface-level feedback that misses critical issues. The PR passes review, and a bug reaches production.

Developer C is new to the team. They don’t know what Developer A’s effective approach looks like. They spend 30 minutes trying different prompts, eventually giving up and doing the review manually.

This is the prompt roulette problem: similar tasks producing wildly different results depending on who’s prompting and how. It’s wasteful, inconsistent, and frustrating.

Prompt templates solve this by encoding effective patterns into reusable structures. Instead of every developer reinventing prompts, they use templates that consistently produce high-quality outputs.

The Benefits

Consistency: Same task, same approach, similar quality outputs. Code reviews follow the same structure. Documentation matches the same style. Tests cover the same patterns.

Knowledge Preservation: When your best prompt engineers leave, their knowledge stays. Templates capture institutional intelligence that would otherwise walk out the door.

Onboarding Acceleration: New developers don’t start from zero. They get instant access to effective patterns that took months to develop.

Quality Baseline: Templates establish a minimum quality floor. Even quick, low-effort usage produces acceptable results.

Iteration Foundation: Templates provide a stable base for improvement. You can A/B test template variations and measure which produces better outcomes.

Template Categories

Most development teams need templates in these categories. Start with one category, perfect it, then expand.

Code Review Templates

Code review is often the highest-ROI template category. Reviews happen constantly, quality varies wildly, and the cost of missed issues is high.

Template Types:

• General code review (language-specific)
• Security-focused review
• Performance review
• Architecture/design review
• Migration/refactoring review

Example Structure:

# TypeScript Code Review Template

## Context
You are reviewing TypeScript code for [TEAM_NAME]'s codebase.
Our coding standards: [LINK_TO_STANDARDS]
Our architecture patterns: [LINK_TO_PATTERNS]

## Instructions
Review the following code changes for:
1. Correctness: Logic errors, edge cases, error handling
2. TypeScript: Type safety, proper typing, avoid any
3. Architecture: Alignment with our patterns
4. Performance: Obvious inefficiencies
5. Security: Input validation, injection risks
6. Maintainability: Readability, naming, complexity

## Format
Provide feedback as:
- 🔴 CRITICAL: Issues that must be fixed
- 🟡 SUGGESTION: Improvements to consider
- 🟢 NICE: Things done well (brief)

For each item, include:
- Location (file:line)
- Issue description
- Suggested fix

## Code to Review
[CODE_CHANGES]

Documentation Templates

Documentation is often neglected because it’s tedious. Good templates reduce friction.

Template Types:

• API documentation
• Architecture decision records (ADRs)
• Runbooks and playbooks
• README generation
• Code comments
• Changelog entries

Example Structure:

# API Documentation Template

## Context
Document this API endpoint for our developer documentation.
Follow our documentation style guide: [LINK]
Target audience: External developers integrating our API

## Instructions
Generate documentation including:
1. Endpoint summary (one sentence)
2. Authentication requirements
3. Request format (method, path, headers, body)
4. Response format (success and error cases)
5. Code examples (curl and JavaScript)
6. Common errors and troubleshooting

## Format
Use our documentation markdown format:
- H2 for endpoint path
- H3 for sections
- Code blocks with language tags
- Tables for parameters

## Endpoint to Document
[ENDPOINT_DEFINITION]
[IMPLEMENTATION_CODE]

Testing Templates

Test generation benefits from templates because tests should be consistent, comprehensive, and match team patterns.

Template Types:

• Unit test generation
• Integration test scenarios
• E2E test cases
• Test data generation
• Edge case identification

Example Structure:

# Unit Test Template

## Context
Generate unit tests for [TEAM_NAME] using our testing stack:
- Framework: Jest with TypeScript
- Mocking: jest.mock for dependencies
- Assertions: expect().toBe/toEqual/toThrow patterns
- Structure: describe/it with clear naming

Our test naming convention: "should [expected behavior] when [condition]"

## Instructions
Generate comprehensive tests including:
1. Happy path: Normal successful execution
2. Edge cases: Boundary values, empty inputs, nulls
3. Error cases: Expected failure modes
4. Type safety: TypeScript-specific checks

Each test should:
- Be independent (no test interdependencies)
- Mock external dependencies
- Use descriptive names
- Include AAA pattern (Arrange, Act, Assert)

## Format
```typescript
describe('[Function/Class Name]', () => {
  describe('[method or scenario]', () => {
    it('should [behavior] when [condition]', () => {
      // Arrange
      // Act
      // Assert
    });
  });
});

Code to Test

[FUNCTION_OR_CLASS]

### Refactoring Templates

Refactoring assistance helps maintain code quality over time.

**Template Types**:
- Code modernization
- Pattern migration
- Performance optimization
- Dependency updates
- Technical debt reduction

## Template Anatomy

Every effective prompt template has four components:

### 1. Context

Context tells Claude Code who it is and what it knows. Good context includes:

**Role Definition**: What expertise should Claude assume?

You are a senior TypeScript engineer with deep expertise in React performance optimization.

**Domain Knowledge**: What does Claude need to know about your specific situation?

Our application is a B2B SaaS dashboard with 50,000 DAU. We use React 18 with Server Components. Performance budget: LCP < 2.5s, FID < 100ms.

**Constraints**: What limitations or requirements exist?

We cannot use external state management libraries. All changes must be backward compatible. We follow semantic versioning.

### 2. Instruction

Instructions tell Claude Code what to do. Good instructions are:

**Specific**: "Review for security vulnerabilities" not "check the code"

**Structured**: Numbered steps or clear phases

**Complete**: All required outputs are mentioned

**Prioritized**: Most important items first

Example:

Analyze this database migration for:

1. Data integrity: Will existing data be preserved correctly?
2. Rollback safety: Can we reverse this migration if needed?
3. Performance: Will the migration complete in <5 minutes for 1M rows?
4. Locking: What tables/rows will be locked and for how long?

If you find critical issues, stop and explain before proceeding.

### 3. Format

Format specifies how Claude Code should structure its output. Without format guidance, outputs vary wildly in structure.

**Markdown Structure**: Headings, lists, code blocks

Use this structure:

Summary

Critical Issues

Recommendations

Implementation Steps

**Specific Formats**: JSON, YAML, specific code patterns

Return your analysis as JSON: { “risk_level”: “low|medium|high|critical”, “issues”: [{“type”: ”…”, “description”: ”…”, “location”: ”…”}], “recommendations”: [”…”] }

**Length Guidance**: How much detail is expected?

Provide a brief summary (2-3 sentences) followed by detailed analysis. Keep the total response under 500 words unless critical issues require more detail.

### 4. Examples

Examples (few-shot learning) dramatically improve output quality for complex tasks.

**Input/Output Pairs**: Show what good looks like

Example review comment: Input: const data = await fetch(url); Output: 🟡 SUGGESTION: Add error handling for fetch. Consider:

const response = await fetch(url);
if (!response.ok) {
  throw new ApiError(`HTTP ${response.status}`, response);
}
const data = await response.json();

**Anti-Examples**: Show what to avoid

Avoid generic comments like “looks good” or “consider refactoring”. Every comment should be specific and actionable.

## Implementation Patterns

How you implement templates matters as much as the templates themselves.

### Version Control

Treat templates as code. Store them in git with proper versioning.

templates/ ├── code-review/ │ ├── typescript-review.v2.1.0.md │ ├── security-review.v1.3.0.md │ └── CHANGELOG.md ├── documentation/ │ ├── api-docs.v1.2.0.md │ └── adr-template.v1.0.0.md └── testing/ ├── unit-test.v2.0.0.md └── e2e-scenarios.v1.1.0.md

**Semantic Versioning**:
- **Major**: Breaking changes to template structure
- **Minor**: New capabilities, backward compatible
- **Patch**: Bug fixes, wording improvements

### Variables and Customization

Templates should be customizable without modification. Use clear variable patterns.

**Variable Syntax**:

[VARIABLE_NAME] - Required, must be provided [OPTIONAL_VAR?] - Optional, can be omitted [VAR:default] - Has default value if not provided

**Common Variables**:
- `[CODE]` - The code being analyzed
- `[LANGUAGE]` - Programming language
- `[TEAM_STANDARDS]` - Link to coding standards
- `[OUTPUT_FORMAT]` - Desired output structure

### Context Injection

Connect templates to your specific codebase and standards.

**Static Context**: Always-included information

Team Standards

• TypeScript strict mode required
• No any types
• All public functions must have JSDoc
• Maximum function complexity: 10

**Dynamic Context**: Injected at runtime

Current Context

Repository: {{repo_name}} Branch: {{branch_name}} Related files: {{related_files}} Recent changes: {{git_log_summary}}

**MCP Integration**: Pull context from servers

Project Context

prompt-library/
├── README.md                    # Library overview, how to use
├── CONTRIBUTING.md              # How to add/modify templates
├── catalog.json                 # Machine-readable template index
│
├── by-category/                 # Organized by use case
│   ├── code-review/
│   ├── documentation/
│   ├── testing/
│   └── refactoring/
│
├── by-language/                 # Language-specific variants
│   ├── typescript/
│   ├── python/
│   └── go/
│
├── experimental/                # Templates under development
│   └── README.md               # Experimental usage policy
│
└── archived/                    # Deprecated templates
    └── README.md               # Migration guidance