## 1. Preliminary Analysis and Purpose Definition (Project Manager)

1. **Information Gathering**:
  - Clearly identify the main question or task.
  - Note any additional constraints, requirements, or expectations (e.g., style, format, tone).

2. **Objective and Context**:
  - Define the specific purpose of the output (inform, explain, instruct, persuade, etc.).
  - Specify the context where it will be used (e.g., platform, audience, domain).

---

## 2. Identification of Key Concepts (Computational Linguistics Expert)

1. **Semantic Parsing**:
  - Extract key terms and expressions from the provided context.
  - Check for ambiguity and clarify meanings if needed.

2. **Information Structuring**:
  - Organize concepts into a “semantic map” (main ideas, secondary ideas, correlations).
  - Include synonyms or paraphrases, if useful, to cover various shades of meaning.

---

## 3. Interaction Design and Adaptation to Use (HCI/UX Specialist)

1. **Identifying User Needs**:
  - Consider the user’s expertise level in the subject matter.
  - Anticipate potential questions or doubts they might have.

2. **Text Structure**:
  - Choose the most effective format (bullet points, short paragraphs, schemas).
  - Evaluate using examples or concrete use cases to enhance understanding.

---

## 4. Cognitive Processing and Progressive Clarity (Cognitive Scientist)

1. **Order of Presentation**:
  - Start with foundational and “invariant” concepts, then elaborate only if necessary.
  - Avoid cognitive overload and overly complex conceptual hierarchies.

2. **Ambiguity and Context Management**:
  - Provide concise definitions for abstract concepts.
  - If cultural or technical references may be unclear to the user, offer additional explanations or analogies.

---

## 5. Consistency and Alignment Verification (Knowledge Engineer)

1. **Source Alignment**:
  - Integrate standard definitions or reference guidelines, if available (e.g., regulations, best practices).
  - Ensure proposed concepts do not contradict official documentation.

2. **Internal Validation**:
  - Ensure that all points from previous steps are coherent with one another.
  - Remove unnecessary redundancies or repetitions.

---

## 6. Final Composition and Synthesis (Project Manager)

1. **Content Integration**:
  - Gather the parts drafted by specialists into a cohesive and linear text.
  - Ensure the style matches the initial request (e.g., formal vs. conversational).

2. **Output Validation**:
  - Review and revise for clarity, relevance, and completeness.
  - If needed, seek further input from a Domain-Specific Expert.

---

## 7. (Optional) Domain Specialization (Domain Expert)

1. **Sector-Specific Adjustment**:
  - If the topic falls within a vertical domain (medicine, finance, engineering, etc.), add specialist references and ensure accuracy.
  - Provide typical examples from the domain to make the discourse more concrete.

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## 8. Final Output

- **Structure**:
 1. **Introduction**: Reference the context and main question.
 2. **Development**: Present essential concepts according to defined logic (principles, examples, synthesis).
 3. **Conclusion/Summary**: Highlight key points, emphasizing their universal importance.
 4. **Attachments/References**: If required, include additional materials (links, bibliography, standards).

- **Final Check**:
 - Ensure the output achieves its intent: to inform, clarify, and generalize the interaction’s key elements with a language model.
 - Verify that the final form aligns with UX guidelines and is cognitively manageable for the user.

---

### Additional Enhancements to Improve Logical Quality

1. **Practical Examples**:
  - Add concrete examples for each phase to illustrate practical applications of the described concepts.

2. **Visual Support**:
  - Include diagrams, tables, and mind maps to visualize concepts and relationships.

3. **Role-Specific Checklists**:
  - Provide role-specific checklists to ensure completeness and consistency.

4. **Iterative Feedback Integration**:
  - Include an iterative review process based on user feedback.

5. **Supportive Technologies**:
  - List useful tools for each role, such as:
    - **Project Manager**: Project management software (e.g., Trello, Asana), spreadsheets (e.g., Google Sheets).
    - **Linguistics Expert**: Online semantic analyzers (e.g., WordNet, NLTK), keyword extraction tools.
    - **HCI/UX Specialist**: Wireframe creation software (e.g., Figma), prototyping tools.
    - **Cognitive Scientist**: Mind mapping tools (e.g., Miro, XMind).
    - **Knowledge Engineer**: Official documentation, domain-specific resources.

By following this enriched and improved procedure, the aim is to optimize the understanding and effectiveness of the output based on the dynamics in play.

---

## Derived Prompt

**Task**: Analyze the following text (insert the text here). Your goal is to determine the central theme, identify the key points and conclusions, and summarize them. Imagine yourself as an advanced model with access to "expert vectors."

Follow this chain of thought, detailing each phase, and refer to the provided examples:

1. **Phase 1: Initial Analysis and Task Dispatch.** Carefully read the text. Based on your internal mechanism, identify the required areas of expertise (e.g., linguistic comprehension, logic, domain-specific knowledge) and indicate which "expert vectors" might be useful. Explain your choice.
  - **Example**: If the text to be analyzed is a scientific article on quantum physics, the primary expertise would be knowledge of physics, but logical analysis might also be needed to understand the arguments.

2. **Phase 2: Selection and Adaptation of Expert Vectors.** Select the expert vectors you find most useful. Explain how and why you chose them. How would you modify/adapt these "expert vectors" for this specific task? Select an adaptation strategy (prompt-based, classifier-based, few-shot) and explain your choice.
  - **Example**: If the model has an 'expert vector' for scientific text analysis and another for understanding logical arguments, it will activate both.

3. **Phase 3: Identification of Key Concepts.** Apply the selected expert vectors to identify key concepts and entities mentioned in the text. Explain how the expert vectors help you pinpoint relevant concepts. (Tip: Use online semantic analysis tools to assist in this phase).

4. **Phase 4: Argumentative Structure Analysis and Skill Combination.** Analyze the relationships between the key concepts, reconstructing the argumentative structure of the text (hypotheses, evidence, conclusions). Combine various skills (logic, text analysis, domain knowledge) and explain how you used "combined skills" in this process. (Tip: Try representing the argumentative structure with a flow diagram).

5. **Phase 5: Evaluation of Conclusions.** Assess the text’s conclusions. Are they well-supported by evidence? Are there weaknesses? Explain how you used "combined skills" for this evaluation.

6. **Phase 6: Synthesis.** Summarize the central theme, key points, and conclusions concisely and clearly. Highlight how your "self-adaptation" process enabled you to provide an accurate response. **Consider how the quality of the response could be influenced by the model’s self-adaptation approach. Experiment by varying texts or phases of the prompt to see how results change.**

**User Checklist**:
- [ ] I have inserted the text to be analyzed into the prompt.
- [ ] I understand the purpose of each phase of the prompt.
- [ ] I am ready to analyze the model’s response step by step, following the indicated chain of thought.

**Model Checklist (Output)**:
- [ ] I have explained my reasoning process.
- [ ] I have broken the task into manageable subproblems.
- [ ] I have identified key concepts.
- [ ] I have combined multiple areas of expertise.
- [ ] I have summarized everything concisely.