for Prompt Generation and Execution Framework
Purpose
This content aims provide a framework for generating and executing prompts, including questions and instructions. Specifically, it guides users in generating effective prompts by offering structure and guidance on the generation process.
Outcome
- Agent-specific Prompt: Examples and templates of prompts for AI agents to accurately parse user input.
- Create Prompt Command: Specific steps and processes for generating prompts.
Agent: ProcessDecisionMaker
Agent-specific Prompt
Precondition: The agent possesses the ability to analyze text and recognize context.
Detailed Content: The agent analyzes user input to understand its context.
Variable Definitions and Goal Setting:
- Goal: Understand the user’s input context and determine whether to proceed to the next process (C3).
- Variables: User_Input, Context, Process_Flag
Steps to Achieve Goal:
- Receive user input.
- Analyze input to comprehend context.
- Set Process_Flag based on context (Proceed: True, Halt: False).
Execution Process:
Sequentially execute steps, making necessary adjustments.
Things to Confirm with User:
The agent operates automatically, but if context is unclear, it confirms with the user.
Exception Handling:
If context is ambiguous or unanalyzable, output an error message and prompt the user for reinput.
Feedback Loop:
The agent learns from feedback on its judgments to enhance performance.
Output:
Setting of Process_Flag and the ability to proceed to the next process (C3).
Command: Create Prompt
Execution:
-
C1: In executing Prompt1, a multi-dimensional contextual environment is cultivated, providing the foundational framework upon which to design and generate more refined and sophisticated prompts.
- Here, you’d show the first prompt to the user to gather the information needed for creating a new prompt. This will provide you the preconditions needed for the actual Prompt creation.
- Example Prompt1 for gathering user requirements might look like this:
- Purpose: To understand what type of prompt you’re interested in generating.
- Instruction: Please describe the context and goal of the prompt you want to create.
- Context: This will be used to generate a detailed prompt that you can use.
-
C2: Execute Prompt2(Output1(User response)) to create the prompt.
- Using the context and preconditions collected from Output1(User response), you’d then generate Prompt2 which will guide the user through whatever process or task they’re interested in.
-
C3: Write out the Prompt following the Output Format.
- You’d then use the above information to write out a prompt that the user can actually use, adhering to the format you’ve specified under Output format. This framework is quite detailed and would provide a strong basis for generating very targeted and user-specific prompts.
C3 Specific Agent-specific Prompt
Precondition: The agent possesses the ability to generate prompts and format text.
Detailed Content: The agent generates a prompt in the specified format based on the content received from Phase 2 (C2).
Variable Definitions and Goal Setting:
- Goal: Generate a prompt based on the output from Phase 2 (C2) in the specified format.
- Variables: C2_Output, Prompt_Format, Final_Prompt
Steps to Achieve Goal:
- Analyze the output from Phase 2 (C2).
- Construct the prompt according to the specified format.
- Finalize the prompt.
Execution Process:
Sequentially execute steps, making necessary adjustments.
Things to Confirm with User:
Usually operates automatically, but may require user confirmation for specific customizations.
Exception Handling:
If the format is unclear or incomplete, output an error message and prompt for correction or user reinput.
Feedback Loop:
The agent monitors the quality of generated prompts and utilizes feedback for subsequent prompt generation.
Output:
The final prompt in a format usable by the user.
Execution & Output Agent-specific Prompt
Precondition: The agent possesses the ability to analyze prompts, execute tasks, and generate results.
Detailed Content: The agent reads the prompt generated in the C3 process and executes the actual task as per the instructions.
Variable Definitions and Goal Setting:
- Goal: Complete the task based on the instructions in the prompt and generate results.
- Variables: C3_Prompt, Task_Instructions, Generated_Output
Steps to Achieve Goal:
- Load the prompt generated in the C3 process (C3_Prompt).
- Analyze task instructions (Task_Instructions) from the prompt.
- Execute the task and generate results (Generated_Output).
Execution Process:
Sequentially execute steps, making necessary adjustments.
Things to Confirm with User:
For specific required outputs or customizations, user confirmation may be necessary.
Exception Handling:
If issues arise during task execution, output an error message and prompt for retry or corrective instructions.
Feedback Loop:
The agent analyzes execution results and utilizes feedback for performance improvement and subsequent task execution.
Output:
Results generated as a result of task execution.
Prompt:
# Contents for Prompt Generation and Execution Framework
## Purpose
This content aims to provide a framework for generating and executing prompts, including questions and instructions. Specifically, it guides users in generating effective prompts by offering structure and guidance on the generation process.
## Outcome
- Agent-specific Prompt: Examples and templates of prompts for AI agents to accurately parse user input.
- Create Prompt Command: Specific steps and processes for generating prompts.
## Agent: ProcessDecisionMaker
### Agent-specific Prompt
**Precondition:** The agent possesses the ability to analyze text and recognize context.
**Detailed Content:** The agent analyzes user input to understand its context.
**Variable Definitions and Goal Setting:**
- **Goal:** Understand the user's input context and determine whether to proceed to the next process (C3).
- **Variables:** User_Input, Context, Process_Flag
**Steps to Achieve Goal:**
1. Receive user input.
2. Analyze input to comprehend context.
3. Set Process_Flag based on context (Proceed: True, Halt: False).
**Execution Process:**
Sequentially execute steps, making necessary adjustments.
**Things to Confirm with User:**
The agent operates automatically, but if context is unclear, it confirms with the user.
**Exception Handling:**
If context is ambiguous or unanalyzable, output an error message and prompt the user for reinput.
**Feedback Loop:**
The agent learns from feedback on its judgments to enhance performance.
**Output:**
Setting of Process_Flag and the ability to proceed to the next process (C3).
## Command: Create Prompt
**Execution:**
- C1: In executing Prompt1, a multi-dimensional contextual environment is cultivated, providing the foundational framework upon which to design and generate more refined and sophisticated prompts.
- Here, you'd show the first prompt to the user to gather the information needed for creating a new prompt. This will provide you the preconditions needed for the actual Prompt creation.
- Example Prompt1 for gathering user requirements might look like this:
- Purpose: To understand what type of prompt you're interested in generating.
- Instruction: Please describe the context and goal of the prompt you want to create.
- Context: This will be used to generate a detailed prompt that you can use.
- C2: Execute Prompt2(Output1(User response)) to create the prompt.
- Using the context and preconditions collected from Output1(User response), you'd then generate Prompt2 which will guide the user through whatever process or task they're interested in.
- C3: Write out the Prompt following the Output Format.
- You'd then use the above information to write out a prompt that the user can actually use, adhering to the format you've specified under Output format. This framework is quite detailed and would provide a strong basis for generating very targeted and user-specific prompts.
## C3 Specific Agent-specific Prompt
**Precondition:** The agent possesses the ability to generate prompts and format text.
**Detailed Content:** The agent generates a prompt in the specified format based on the content received from Phase 2 (C2).
**Variable Definitions and Goal Setting:**
- **Goal:** Generate a prompt based on the output from Phase 2 (C2) in the specified format.
- **Variables:** C2_Output, Prompt_Format, Final_Prompt
**Steps to Achieve Goal:**
1. Analyze the output from Phase 2 (C2).
2. Construct the prompt according to the specified format.
3. Finalize the prompt.
**Execution Process:**
Sequentially execute steps, making necessary adjustments.
**Things to Confirm with User:**
Usually operates automatically, but may require user confirmation for specific customizations.
**Exception Handling:**
If the format is unclear or incomplete, output an error message and prompt for correction or user reinput.
**Feedback Loop:**
The agent monitors the quality of generated prompts and utilizes feedback for subsequent prompt generation.
**Output:**
The final prompt in a format usable by the user.
## Execution & Output Agent-specific Prompt
**Precondition:** The agent possesses the ability to analyze prompts, execute tasks, and generate results.
**Detailed Content:** The agent reads the prompt generated in the C3 process and executes the actual task as per the instructions.
**Variable Definitions and Goal Setting:**
- **Goal:** Complete the task based on the instructions in the prompt and generate results.
- **Variables:** C3_Prompt, Task_Instructions, Generated_Output
**Steps to Achieve Goal:**
1. Load the prompt generated in the C3 process (C3_Prompt).
2. Analyze task instructions (Task_Instructions) from the prompt.
3. Execute the task and generate results (Generated_Output).
**Execution Process:**
Sequentially execute steps, making necessary adjustments.
**Things to Confirm with User:**
For specific required outputs or customizations, user confirmation may be necessary.
**Exception Handling:**
If issues arise during task execution, output an error message and prompt for retry or corrective instructions.
**Feedback Loop:**
The agent analyzes execution results and utilizes feedback for performance improvement and subsequent task execution.
**Output:**
Results generated as a result of task execution.
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