Output Styles

Output Styles

Output styles are markdown-based formatting directives injected into the system prompt to control how the agent formats and presents its responses.

Quick Start

from pydantic_deep import create_deep_agent

# Use a built-in style
agent = create_deep_agent(output_style="concise")

Built-in Styles

# Minimal, code-focused responses
agent = create_deep_agent(output_style="concise")

# Detailed explanations for learning
agent = create_deep_agent(output_style="explanatory")

# Professional documentation style
agent = create_deep_agent(output_style="formal")

# Friendly teaching style
agent = create_deep_agent(output_style="conversational")

Custom Styles

Inline

Pass an OutputStyle instance directly:

from pydantic_deep.styles import OutputStyle

agent = create_deep_agent(
    output_style=OutputStyle(
        name="technical",
        description="Deep technical detail",
        content="Always include implementation details, cite specific files and line numbers...",
    ),
)

From Files

Create markdown style files with YAML frontmatter:

---
name: my-style
description: My custom output style
---

Use a structured format:
- Start with a one-sentence summary
- Include code examples for every suggestion
- End with action items

Then reference by name:

agent = create_deep_agent(
    output_style="my-style",
    styles_dir="/path/to/styles",  # Directory containing .md style files
)

Discovery

Load all styles from a directory:

from pydantic_deep.styles import discover_styles

styles = discover_styles("/path/to/styles")
# Returns: {"my-style": OutputStyle(...), "another": OutputStyle(...)}

Resolution Order

When you pass a string name to output_style, the resolution order is:

1. Return OutputStyle instances directly
2. Look up in BUILTIN_STYLES (concise, explanatory, formal, conversational)
3. Search styles_dir directories for matching .md files
4. Raise ValueError if not found

How It Works

The resolved style is appended to the agent's instructions as a system prompt section:

## Output Style: concise

Be extremely concise in all responses:
- No explanations unless explicitly asked
- Code only with minimal comments
- One-line answers when possible
...

Components

Next Steps

• Context Files — Project context injection
• Memory — Persistent agent memory
• Agents — Full agent configuration