System Prompts for API Agents

Building Agents with grok-build-0.1

If you’re developing your own dev tools—a code review agent, a deployment assistant, a documentation generation tool—you’ll interact directly with the xAI API. The system prompt is your primary lever for controlling model behavior.

Anatomy of a Good System Prompt

An effective system prompt for an agent based on grok-build-0.1 contains four sections:

1. Task Description

Start by clearly defining what the agent does:

## Role
You are a code review assistant specialized in TypeScript.
You analyze code diffs to identify potential bugs,
performance issues, and convention violations.

2. Expectations and Output Format

Describe what you expect from the model:

## Output Format
For each identified issue, provide:
- The file and line involved
- Severity (critical, warning, info)
- A description of the issue
- A correction suggestion with a code example

3. Edge Cases

Anticipate ambiguous situations:

## Edge Cases
- If the diff is empty, respond "No changes to analyze"
- If the code is in an unsupported language, indicate it
- Do not comment on formatting changes (spaces, indentation)
- Ignore generated config files (.lock, dist/)

4. Constraints

Define limits:

## Constraints
- Maximum 10 comments per review
- Prioritize critical bugs over style suggestions
- Do not suggest major refactoring for minor fixes

Structuring with Markdown or XML

The model is accustomed to seeing substantial, structured context in the first prompt. Two formats work well:

Markdown (Recommended for Readability)

## Role
Role description...

## Available Tools
- read_file: read a project file
- write_file: modify a file
- run_command: execute a terminal command

## Rules
1. Always read the file before modifying it
2. Ask for confirmation before deleting code
3. Run tests after each modification

XML (Recommended for Precision)

<agent>
  <role>TypeScript code review assistant</role>
  <tools>
    <tool name="read_file">Read a project file</tool>
    <tool name="write_file">Modify a file</tool>
  </tools>
  <rules>
    <rule>Always read the file before modifying it</rule>
    <rule>Ask for confirmation before deleting code</rule>
  </rules>
</agent>

Both formats are effective. Markdown is easier to maintain; XML is more structured for automatic parsing.

Cache Optimization

Remember the lesson on caching: the system prompt must be stable. Write it once, completely, and do not modify it during the session. If you need to change the agent’s behavior, add instructions in the user message rather than modifying the system prompt.

Complete Example: Test Generation Agent

## Role
You are an agent that generates unit tests for TypeScript code.
You use Vitest as the testing framework.

## Process
1. Read the source file with read_file
2. Identify exported functions
3. For each function, generate tests covering:
   - The nominal case
   - Edge cases (null, undefined, empty array)
   - Error cases
4. Write tests with write_file in the __tests__/ folder
5. Run tests with run_command("npx vitest run")

## Conventions
- Naming: {file}.test.ts
- Structure: describe > it > expect
- Use fixtures for complex data
- Mock external dependencies (API, DB)

## Constraints
- Do not modify source code
- If a test fails, fix the test, not the source code
- Maximum 20 tests per file

This system prompt gives the agent all the information necessary to operate autonomously, while staying within defined limits.

Key Takeaways

• The system prompt structures agent behavior in 4 parts: role, expectations, edge cases, constraints
• Use Markdown or XML to structure sections
• The system prompt must be stable to optimize caching
• Include step-by-step processes for sequential agents
• Always define edge cases to avoid unexpected behaviors

Test Your Knowledge

grok-build in your editors: taking final control.

1. What is grok-build-0.1?

Answer: xAI’s agentic code model: native tool calling, streaming reasoning, context adapted for dev tasks—the engine behind Grok Build and editor integrations.

2. How do you use it in your editor?

Answer: Via integrations: Cline in VS Code, Cursor, GitHub Copilot, Windsurf, and others—the OpenAI-compatible xAI API makes direct integration possible.

3. What habits ensure good code tasks?

Answer: Specify context (files, constraints), define clear and verifiable objectives, iterate progressively—and optimize caching by keeping prefixes stable.

4. grok-build-0.1 or grok-4.5 for code?

Answer: grok-build for everyday dev agentic tasks (fast, specialized); grok-4.5 when the task demands maximum reasoning—the choice follows difficulty.

5. What goes into the system prompt of an API code agent?

Answer: The role, project conventions, editing rules (tests, style), and limits—the framing that turns a code model into a teammate for your codebase.

Specialized model, connected editor, clean tasks, framed prompts: Grok-assisted development comes down to four choices—all made intentionally.