Added a prompt optimization assistant (#709)

app/MindWork AI Studio/Assistants/PromptOptimizer/prompting_guideline.md

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+# 1 – Be Clear and Direct
+
+LLMs respond best to clear, explicit instructions. Being specific about your desired output improves results. If you want high-quality work, ask for it directly rather than expecting the model to guess.
+
+Think of the LLM as a skilled new employee: They do not know your specific workflows yet. The more precisely you explain what you want, the better the result.
+
+**Golden Rule:** If a colleague would be confused by your prompt without extra context, the LLM will be too.
+
+**Less Effective:**
+```text
+Create an analytics dashboard
+```
+
+**More Effective:**
+```text
+Create an analytics dashboard. Include relevant features and interactions. Go beyond the basics to create a fully-featured implementation.
+```
+
+# 2 – Add Examples and Context to Improve Performance
+
+Providing examples, context, or the reason behind your instructions helps the model understand your goals.
+
+**Less Effective:**
+```text
+NEVER use ellipses
+```
+
+**More Effective:**
+```text
+Your response will be read aloud by a text-to-speech engine, so never use ellipses since the engine will not know how to pronounce them.
+```
+
+The model can generalize from the explanation.
+
+# 3 – Use Sequential Steps
+
+When the order of tasks matters, provide instructions as a numbered list.
+
+**Example:**
+```text
+1. Analyze the provided text for key themes.
+2. Extract the top 5 most frequent terms.
+3. Format the output as a table with columns: Term, Frequency, Context.
+```
+
+# 4 – Structure Prompts with Markers
+
+Headings (e.g., `#` or `###`) or backticks (` `````` `) help the model parse complex prompts, especially when mixing instructions, context, and data.
+
+**Less Effective:**
+```text
+{text input here}
+
+Summarize the text above as a bullet point list of the most important points.
+```
+
+**More Effective:**
+```text
+# Text: 
+```{text input here}```
+
+# Task: 
+Summarize the text above as a bullet point list of the most important points.
+```
+
+# 5 – Give the LLM a Role
+
+Setting a role in your prompt focuses the LLM's behavior and tone. Even a single sentence makes a difference.
+
+**Example:**
+```text
+You are a helpful coding assistant specializing in Python.
+```
+```text
+You are a senior marketing expert with 10 years of experience in the aerospace industry.
+```
+
+# 6 – Prompt Language
+
+LLMs are primarily trained on English text. They generally perform best with prompts written in **English**, especially for complex tasks.
+
+*   **Recommendation:** Write your prompts in English.
+*   **If needed:** You can ask the LLM to respond in your native language (e.g., "Answer in German").
+*   **Note:** This is especially important for smaller models, which may have limited multilingual capabilities.
+