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Great prompts are rarely written perfectly on the first try. They evolve through a cycle of drafting, testing, and refining. Prompt Lockbox’s AI features are designed to supercharge this cycle, turning a slow, manual process into a rapid, intelligent workflow. This guide will walk you through a complete iteration loop. We’ll start with a rough, undocumented prompt idea and, in just a few commands, use AI to transform it into a documented, improved, and versioned asset ready for use.
The Goal: To demonstrate a rapid development workflow:Start with a basic prompt template.
  • Use AI Documentation to create a baseline understanding.
  • Use AI Improvement to refine and strengthen the prompt.
  • Version the final, polished result.
Here are the steps:
1

Create the Initial Draft

First, let’s create a new prompt. Imagine we need a prompt to summarize meeting transcripts. We’ll start by creating a file with a name and a simple template, but leave the description and tags blank.In your teminal, run the command:
plb create
# Name: meeting-summarizer
# (Leave description and tags blank)
Created prompt file:
prompts/meeting-summarizer.v1.0.0.yml
name: meeting-summarizer
version: "1.0.0"
description: ""
tags: []
... 
template: |
  Here is a meeting transcript. Please summarize it.

  TRANSCRIPT:
  ${transcript_text}
This prompt is functional, but it’s vague and undocumented.
2

Generate Documentation with AI

Instead of manually writing a description and thinking of tags, let’s use the document command.
plb prompt document meeting-summarizer
Result: The AI analyzes the template and automatically updates the .yml file:
prompts/meeting-summarizer.v1.0.0.yml
... 
description: "Summarizes a provided meeting transcript text into a concise overview."
tags: [summarization, meetings, transcription, nlp]
template: |
  Here is a meeting transcript. Please summarize it.
  
  TRANSCRIPT:
  ${transcript_text}
Now our prompt is documented and discoverable, but the template itself can still be improved.
3

Improve the Prompt with AI

Our current template is too generic. Let’s ask the AI to make it more specific and structured. Optionally, you can provide notes to LLM using note.
You can use the CLI or Python, but the CLI is recommended for clearer visibility into the changes.
  plb prompt improve meeting-summarizer --note "Make it output action items and decisions separately."
Result: The improve command will suggest a much more robust template. After you confirm the changes, your file will be updated. Here’s the updated file:
  template: |
    You are an expert meeting assistant. Analyze the following meeting transcript and provide a structured summary.
  
    Your summary must contain two distinct sections:
    1.  **Key Decisions:** A bulleted list of all decisions made during the meeting.
    2.  **Action Items:** A bulleted list of all tasks assigned, including who is responsible if mentioned.
    
    If no decisions or action items are found, state "None".
  
    TRANSCRIPT:
    ${transcript_text}
4

Version the Polished Prompt

We’ve transformed our rough draft into a documented and structured prompt. The final step is to lock this polished version or create a new one to signify that it’s a major improvement.
# We can lock v1.0.0 now that it's complete
plb lock meeting-summarizer

# Or, if we feel the change was significant, create v1.1.0
plb version meeting-summarizer --minor
This rapid iteration loop — Create -> Document -> Improve -> Version —is at the heart of what makes the toolkit useful.