# Source: https://docs.giselles.ai/en/prompts/tips.md

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.giselles.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Tips

> Practical Tips for Effective Prompt Creation in Giselle’s Generator Nodes.

This document provides concrete, actionable tips tailored specifically for creating effective prompts within Giselle’s Generator Nodes. Unlike conversational UIs, Giselle uses a single-shot prompting model, meaning each prompt must be precise and complete on its own. While direct iterative refinement through conversation within a single node isn't possible, strategically chaining multiple nodes can significantly elevate the output quality through careful node integration and diverse data sourcing.

## Essential Principles

### 1. Ensure Clarity and Precision

* Clearly define the AI model’s role.
* Provide explicit, focused instructions without ambiguity.

```plaintext  theme={null}
❌ Poor example:
"Describe a useful invention."

✅ Good example:
"Role: Technology historian

Task: Provide a concise summary (100 words max) of the invention of the telephone, highlighting its historical significance and modern impact.

Output Format:
- Summary paragraph
- Clearly stated historical context and modern relevance"
```

### 2. Include Comprehensive Context

* Provide necessary background and purpose clearly in your prompt.
* Explicitly state constraints or expectations relevant to the task.

### 3. Specify Structured Outputs

* Clearly outline the desired response structure, length, and style.
* Define formats explicitly (e.g., bullet points, structured paragraphs, JSON, image dimensions).

## Advanced Node Integration Techniques

### 1. Effective Role Definition

Defining roles guides the AI to produce contextually accurate outputs:

```plaintext  theme={null}
✅ Example:
"Role: UX Designer

Task: Evaluate the provided web interface design for usability issues.

Output Format:
- List identified issues clearly
- Provide specific recommendations for improvements"
```

### 2. Sequential Node Chaining

Although Giselle nodes are single-shot, you can achieve iterative refinement by chaining multiple nodes:

1. **Ideation Node**: Generate initial ideas or concepts.
2. **Drafting Node**: Develop detailed drafts from initial concepts.
3. **Review Node**: Critically evaluate drafts and suggest improvements.

### 3. Leveraging Multi-Node Workflows

Combine diverse AI models across nodes to maximize output quality:

* **Claude** for nuanced analysis and ethical considerations.
* **GPT-5.2** for structured and creative content creation.
* **Gemini** for high-quality image and visual content generation.

## Common Pitfalls to Avoid

### 1. Overly Restrictive Instructions

Avoid excessively rigid constraints:

```plaintext  theme={null}
❌ Avoid:
"Create a detailed report exactly 200 words, including exactly four examples."
```

### 2. Contradictory or Confusing Instructions

Ensure instructions remain logically consistent:

```plaintext  theme={null}
❌ Avoid:
"Provide a highly detailed yet simple explanation using advanced terminology."
```

### 3. Ambiguous or Incomplete Prompts

Avoid vague instructions that lead to unclear outputs:

```plaintext  theme={null}
❌ Avoid:
"Explain something useful."
```

## Optimizing Giselle Workflows

### 1. Iterative Node Refinement

* Regularly review outputs from each node to optimize subsequent prompts.
* Use multiple nodes strategically to iteratively refine concepts, drafts, and final outputs.

### 2. Strategic Use of Templates

Leverage prompt templates for consistent, effective outputs:

```plaintext  theme={null}
✅ Giselle Template:

Role: [Defined AI role]

Task: [Explicit, precise task description]

Constraints:
- [Specific constraint or limitation]
- [Additional constraints as necessary]

Input Data:
- [Clearly referenced or provided data]

Output Format:
- [Detailed expected structure of response]
```

## Giselle-Specific Recommendations

### 1. Select Appropriate AI Models

Choose AI models carefully according to task requirements and capabilities:

* **Claude**: nuanced, ethical analyses.
* **Gemini**: complex multimodal inputs and image generation.
* **GPT-5.2**: structured outputs and creative content.

### 2. Visualize and Collaborate

* Clearly map your workflows visually within Giselle’s UI.
* Share your workflows with teams to enhance collaboration and clarity.
* Experiment with node combinations to achieve advanced, high-quality results beyond standard conversational interfaces.

## Key Points for Effective Giselle Prompts

* **Role Definition**: Clearly articulate the AI model’s role.
* **Precision**: Provide exact, detailed instructions.
* **Contextual Completeness**: Include essential context and constraints.
* **Output Structure**: Clearly define response formats.
* **Workflow Optimization**: Strategically chain multiple nodes to enhance output quality.