Output Dev Prompt File

src/workflows/{workflow-name}/
├── workflow.ts
├── steps.ts
├── types.ts
└── prompts/
    ├── analyzeContent@v1.prompt
    ├── generateSummary@v1.prompt
    └── extractData@v2.prompt

{promptName}@v{version}.prompt

---
provider: anthropic
# current as of 2026-05-04 — run output-dev-model-selection for the latest
model: claude-sonnet-4-6
temperature: 0.7
maxOutputTokens: 4096
---

<system>
System instructions go here.
</system>

<user>
User message with {{ variable }} placeholders.
</user>

---
provider: openai
model: gpt-image-1
---

Create a cinematic image of {{ subject }}.

---
provider: anthropic    # LLM provider: anthropic, openai, google-vertex, amazon-bedrock, azure, perplexity
# current as of 2026-05-04 — run output-dev-model-selection for the latest
model: claude-sonnet-4-6
---

---
provider: anthropic
# current as of 2026-05-04 - run output-dev-model-selection for the latest
model: claude-sonnet-4-6
temperature: 0.7       # Supported range and default vary by provider
maxOutputTokens: 4096  # Maximum output tokens
maxSteps: 5            # Tool-loop ceiling when tools or skills are present (default 10)
skills:                # Skill file or directory paths, relative to this prompt
  - ./skills
providerOptions:       # Provider-specific options
  thinking:
    type: enabled
    budgetTokens: 2000
---

---
provider: anthropic
model: claude-sonnet-4-6
temperature: 0.7
maxOutputTokens: 8192
---

---
provider: anthropic
model: claude-sonnet-4-6
temperature: 0.7
maxOutputTokens: 32000
providerOptions:
  thinking:
    type: enabled
    budgetTokens: 2000
---

---
provider: openai
# current as of 2026-05-04 — run output-dev-model-selection for the latest
model: gpt-5-5
temperature: 0.7
maxOutputTokens: 4096
---

---
provider: google-vertex
# current as of 2026-05-04 — run output-dev-model-selection for the latest
model: gemini-3-pro
temperature: 0.7
maxOutputTokens: 8192
---

<system>
You are an expert at analyzing technical content.
Your responses should be clear and structured.
</system>

<user>
Please analyze the following content:

{{ content }}
</user>

<assistant>
I'll analyze this content step by step...
</assistant>

<user>
Analyze this content about {{ topic }}:

{{ content }}

Generate {{ numberOfIdeas }} ideas.
</user>

<system>
You are an expert content analyzer.

{% if colorPalette %}
**Color Palette Constraints:** {{ colorPalette }}
{% endif %}

{% if artDirection %}
**Art Direction Constraints:** {{ artDirection }}
{% endif %}
</system>

<user>
Analyze each of these items:

{% for item in items %}
- {{ item.name }}: {{ item.description }}
{% endfor %}
</user>

<user>
Generate {{ numberOfIdeas | default: 3 }} ideas for {{ topic }}.
</user>

---
provider: anthropic
# current as of 2026-05-04 — run output-dev-model-selection for the latest
model: claude-sonnet-4-6
temperature: 0.7
maxOutputTokens: 32000
providerOptions:
  thinking:
    type: enabled
    budgetTokens: 2000
---

<system>
You are an expert at creating structured, precise infographic prompts optimized for Gemini's image generation model.

Your task is to generate prompts for informational infographics that illustrate key concepts from the provided content.

CRITICAL RULES you MUST follow:
- Use Markdown dashed lists to specify constraints
- Use ALL CAPS for "MUST" requirements to ensure strict adherence
- Include specific compositional constraints (e.g., rule of thirds, lighting)
- Always include negative constraints to prevent unwanted elements
- Keep each infographic focused on ONE clear concept

{% if colorPalette %}
**Color Palette Constraints:** {{ colorPalette }}
{% endif %}

{% if artDirection %}
**Art Direction Constraints:** {{ artDirection }}
{% endif %}
</system>

<user>
Generate {{ numberOfIdeas }} structured infographic prompts based on key topics from this content.

<content>
{{ content }}
</content>

Each prompt MUST follow this structure:

Create an infographic about [specific topic]. The infographic MUST follow ALL of these constraints:
- The infographic MUST use the reference images as a visual style guide
- The composition MUST follow the rule of thirds for visual balance
- The infographic MUST use clean, minimal design with simple lines and shapes
{% if colorPalette %}- The color palette MUST strictly follow: {{ colorPalette }}{% endif %}
{% if artDirection %}- The art direction MUST strictly follow: {{ artDirection }}{% endif %}
- NEVER include any watermarks, logos, or decorative overlays
- NEVER use generic AI art buzzwords like "hyperrealistic"

Focus on the most important concepts that would benefit from visual explanation.
</user>

const { output } = await generateText( {
  prompt: 'rank@v1',
  variables: {
    stories: storyArray,
    interests: interestArray
  }
} );

{% for story in stories %}
- {{ story.title }} (score: {{ story.score }}, by: {{ story.author }})
{% endfor %}

Interests: {{ interests | join: ", " }}

import { generateText, aiSdk } from '@outputai/llm';
import { z } from '@outputai/core';

const { output } = await generateText( {
  prompt: 'generateImageIdeas@v1',  // References prompts/generateImageIdeas@v1.prompt
  variables: {
    content: 'Solar panel technology explained...',
    numberOfIdeas: 3,
    colorPalette: 'blue and green tones',
    artDirection: 'minimalist style'
  },
  output: aiSdk.Output.object( {
    schema: z.object( {
      ideas: z.array( z.string() )
    } )
  } )
} );
// output contains { ideas: [...] }

import { generateText } from '@outputai/llm';

const { result } = await generateText( {
  prompt: 'summarize@v1',
  variables: {
    content: 'Long article text...',
    maxLength: 200
  }
} );
// result contains the generated text string

src/workflows/{workflow-name}/
└── prompts/
    ├── writing_assistant@v1.prompt
    └── skills/
        ├── clarity_guidelines.md
        └── structure_guide.md

---
provider: anthropic
model: claude-sonnet-4-6
skills:
  - ./skills
---

<system>
You are an expert technical writing assistant.
Use load_skill to get the full instructions for any skill before applying it.
</system>

import { Agent, aiSdk } from '@outputai/llm';

const agent = new Agent( {
  prompt: 'writing_assistant@v1',
  variables: {
    content_type: 'documentation',
    focus: 'clarity',
    content: input.content
  },
  output: aiSdk.Output.object( { schema: reviewSchema } )
} );
const { output } = await agent.generate();