3. Video to Annotated "how to" article

I want to record a video on a "how to" topic and turn it into an article, with text and images. For example, I will record a video about "how to make software mockups with GIMP" and then want it turned into a video. I want this to be a very media-rich article with lots and lots of screenshots, so the idea is that in the video I will explain what I am doing (eg "the first thing we do is open GIMP and click on new image and choose an image size of 1000x1000"), and then we will want to extract the transcription from the video. Then we review this transcription/timestamps and decide on the core steps of the how to task (eg step 1 - download GIMP.. step 2 - create a new image), and then we look at the timestamps mentioned and extract images at those specific timestamps (so if I say "let me open the image now" at 23.39 then we would extract an image frame from the video at that point). Then we will use my transcription file to set specific timings. My software works best when it has a fixed number of actions to take, so I suggest we (fairly abitrarily) go with six steps. This means we will want six images embedded, and six steps written in the article. It will mean that an LLM will need to review the transcription and decide which are the six steps (if the video narrator does not explicitly list six steps, or even does more or fewer).

Sub Agent #1 | Sub Agent #2 | Sub Agent #3

CLAUDE:- final-output-and-component-outputs

Based on the given task description, here's my understanding of the final output and the components required:

a) Final Output:
The final output would be a text-based article with embedded images, specifically:
- A text article containing six steps on "how to make software mockups with GIMP"
- Each step in the article would have a corresponding screenshot image extracted from the video at specific timestamps
- The article would be in a format suitable for publishing on a website or blog (e.g., HTML, Markdown)

b) Components/Outputs:
To generate the final output, the following components would be required:

1. Video Recording:
   - A video recording of the narrator explaining the process of making software mockups with GIMP
   - The video should contain clear explanations and demonstrations of each step involved

2. Video Transcription:
   - A text transcription of the video, including the narration and the corresponding timestamps
   - The transcription should be accurate and properly synchronized with the video timeline

3. Step Identification:
   - An analysis of the video transcription to identify the six main steps of the process
   - If the narrator does not explicitly mention six steps, the AI agent would need to determine the most important steps based on the content and context of the transcription

4. Image Extraction:
   - Extraction of six screenshot images from the video at the timestamps corresponding to each identified step
   - The images should clearly illustrate the actions or results described in each step

5. Article Text:
   - A text article that describes the six steps of making software mockups with GIMP
   - The article should be well-structured, with clear headings for each step and concise explanations
   - The text should be based on the video transcription and the identified steps

6. Image Integration:
   - Integration of the extracted screenshot images into the text article at the appropriate locations
   - Each image should be placed alongside the corresponding step in the article

7. Final Article Formatting:
   - Formatting of the article with the integrated images into a suitable format for publishing (e.g., HTML, Markdown)
   - The formatted article should be ready for uploading to a website or blog

These components would need to be generated and assembled in the correct order to create the final output of a text article with embedded images explaining how to make software mockups with GIMP in six steps.

GPT4:- final-output-and-component-outputs

a) The final output would be a detailed step-by-step instructional article with imbedded screenshots. The article would be structured to include six clear steps on the selected 'how to' topic, in this case "how to make software mockups with GIMP". This tutorial would be created using transcription of a video recorded on the same topic, hence it would be an accurate representation of the video in written form.

b) Breaking this task into components, the key components/outputs needed would include:

1. **Video File**: This is the starting point and will contain the information we need. The video will show step by step instructions on how to use GIMP for creating software mock-ups. This video file could be in any standard format like MP4, MOV, etc.

2. **Transcription File**: Using an AI transcription service, a transcription of the video will be made. This will result in a text file where each line corresponds to a specific time-stamp in the video. This will act as the core text of the article and will be used to identify the key steps.

3. **Identified Key Steps and Timestamps**: An AI model will review the transcription to identify the important steps and their corresponding timestamps. These identified steps will form the sections of the how-to article. As agreed, we will look for six key steps.

4. **Images/Screenshots**: Using timestamps identified above, screenshots from the video will be taken. These images are to be embedded in the instructional article next to the appropriate steps they correspond to.

5. **Formatted Article File**: Lastly, the transcription will be revised, formatted, and divided into six steps. Each step will include explanatory text and associated images. This will be written up into the desired format - HTML, Word, PDF, etc.

In addition to the above, a JSON file could be needed that specifies the order and structure of the final article. It would dictate where each component will be placed, including text, steps, and images. For example, it may specify: `{Step 1: {text: "XYZ", image: "URL or path of image 1"}, Step 2: {text: "ABC", image: "URL or path of image 2"},...}`. These placeholders would be replaced with actual content and images to create the final article.

claude 3 - extract final output

extract component outputs

To generate the final output, the following components would be required:

Claude - research-ideas-and-input-variables

Thank you for the detailed description of your desired automated workflow. Let me address your questions one by one:

a) Clarifying the final output:
- What is the desired length of the final article? Is there a specific word count range you're aiming for?
- Are there any specific formatting requirements for the article (e.g., specific headings, subheadings, or sections)?
- Should the article include any additional elements apart from the text and images (e.g., video embed, links, or references)?
- Is there a specific target audience or platform where the article will be published (e.g., personal blog, educational website, or professional tutorial site)?

b) Required inputs before launching the task:
- The video file containing the "how to" tutorial.
- The specific topic or title of the tutorial (e.g., "How to Make Software Mockups with GIMP").
- Any additional resources or files needed for the tutorial (e.g., sample images, project files, or assets).

c) Potential task segmentation:
I have a few suggestions for task segmentation that could help streamline the workflow:

1. Video transcription and timestamp extraction:
   - Transcribe the video audio to text using a speech-to-text service or tool.
   - Extract the timestamps for key moments or steps mentioned in the video.

2. Image extraction:
   - Use the extracted timestamps to capture relevant screenshots or frames from the video.
   - Ensure the extracted images are of sufficient quality and resolution for the article.

3. Content outline generation:
   - Analyze the video transcription to identify the main steps or sections of the tutorial.
   - Create a structured outline for the article based on the identified steps.

4. Article writing:
   - Use the content outline and video transcription to write the article text.
   - Ensure the article follows a logical flow and provides clear instructions.

5. Image integration:
   - Integrate the extracted images into the appropriate sections of the article.
   - Add captions or annotations to the images if necessary.

6. Final review and editing:
   - Perform a final review of the article to ensure clarity, coherence, and accuracy.
   - Make any necessary edits or improvements based on the review.

By segmenting the tasks in this way, each step can be handled by specialized components or tools, allowing for a more modular and efficient workflow.

GPT - research-ideas-and-input-variables

a) Here are some questions that might help to clarify the final output of the task:

1. What is the expected length of the final article? This can help ensure we extract the right amount of content from the video and can also guide the AI when deciding on the six steps of the task.
2. In terms of media richness, apart from the screenshots, are there any other specific requirements such as including videos, GIFs or infographics? 
3. What is the style and tone of the article? Do we want it conversational like in the video or more formal?
4. What kind of "how to" videos will you be creating? Or what industries or topics will these videos come from?
5. Should the screenshots be annotated or edited in any way? Or are raw screenshots adequate?
6. Beyond the six steps, what other sections or information should be included in the article? Such as introduction, conclusion, additional tips, etc.
7. Will the videos always contain a clear explanation of the steps, or should the AI be prepared to infer steps based on the video content?

b) The task should accept these inputs before launching:

1. The video file that contains the "how to" information. It should have clear audio and video quality to ensure accuracy in transcription and screenshot extraction.
2. Any available script or outline of the video content - this will help in transcribing and identifying core steps.
3. Desired keyword, if any, to make sure the article is SEO-optimized.
4. Specific requirements or guidelines on the article style, structure, and tone.
5. Any constraints on the screenshot extraction, e.g., certain elements to focus on or elements to avoid.

template-ideas

Based on the task description and the final output you've provided, here are some template suggestions that could help refine the definition of a successful output:

1. Existing "How-to" articles with step-by-step instructions and images:
   - Search for top-ranking articles on "how to make software mockups with GIMP" or similar topics.
   - Analyze the structure, formatting, and content of these articles.
   - Pay attention to the number of steps, the level of detail in each step, and the placement and relevance of images.

2. GIMP tutorials on YouTube:
   - Look for popular videos on using GIMP for creating software mockups.
   - Review the video transcriptions and analyze how the content is organized and presented.
   - Note the timestamps where key steps or actions are mentioned, as this can help guide the image extraction process.

3. Software mockup galleries or showcases:
   - Search for websites or blog posts showcasing software mockups created with GIMP.
   - Analyze the visual style, composition, and quality of the mockups.
   - This can help set expectations for the type and quality of screenshots to be included in the article.

4. HTML or Markdown templates for step-by-step tutorials:
   - Look for existing templates or examples of well-structured, visually appealing tutorials in HTML or Markdown format.
   - Pay attention to the use of headings, subheadings, lists, and image placement.
   - This can serve as a reference for formatting the final article.

5. GIMP documentation or user manual:
   - Review the official GIMP documentation or user manual sections related to creating software mockups.
   - Analyze the language, terminology, and level of detail used in explaining the process.
   - This can help ensure that the article aligns with the software's official guidelines and uses appropriate terminology.

By collecting and analyzing these templates, the AI Agent can gain insights into the structure, content, and presentation of successful "how-to" articles and software mockup tutorials. This information can then be used to guide the creation of the final article, ensuring that it meets the desired quality standards and effectively communicates the step-by-step process to the readers.

claude 3 - searches

Here are 5 specific keyphrases you can search to find helpful templates and refine your definition of a successful output for your task:

1. "how to make software mockups with gimp step by step tutorial"
   This keyphrase targets step-by-step tutorial articles specifically on creating software mockups using GIMP, which aligns closely with your desired output.

2. "gimp software mockup tutorial video youtube"
   Searching for GIMP software mockup tutorial videos on YouTube can provide valuable insights into the structure, content, and presentation of visual tutorials on this topic.

3. "software mockup showcase created with gimp"
   This keyphrase aims to find showcases or galleries of software mockups created using GIMP, allowing you to analyze the visual style, composition, and quality of successful mockups.

4. "html template for step by step software tutorial with images"
   Searching for HTML templates designed for step-by-step software tutorials with images can help you find well-structured and visually appealing examples to reference when formatting your final article.

5. "gimp user manual creating software mockups"
   This keyphrase targets sections of the official GIMP user manual or documentation that specifically cover creating software mockups, providing insights into the language, terminology, and level of detail used in explaining the process.

By searching for these specific keyphrases and reviewing the top results, you should be able to find relevant and useful templates that can help refine your understanding of what a successful output looks like for your task of creating a step-by-step article on making software mockups with GIMP.

subagent-summary

A) FULL TASK SUMMARY: Create a text-based article with embedded images explaining how to make software mockups using GIMP, based on a video recording of the process.

B) FINAL TASK OUTPUT: An HTML or Markdown formatted article containing six steps on how to make software mockups with GIMP, with each step accompanied by a relevant screenshot image extracted from the video. The article should be ready for publishing on a website or blog.

C) COMPONENTS OVERVIEW:
1. Video recording of the process
2. Text transcription of the video with timestamps
3. Identification of the six main steps from the transcription
4. Extraction of six screenshot images corresponding to each step
5. Text article describing the six steps based on the transcription and identified steps
6. Integration of the extracted images into the text article
7. Final formatting of the article for publishing

D) OVERVIEW OF SUBAGENTS:
- Video Recorder: Records the video of the narrator explaining the process of making software mockups with GIMP.
- Transcriber: Generates a text transcription of the video, including the narration and corresponding timestamps.
- Step Analyzer: Analyzes the video transcription to identify the six main steps of the process.
- Image Extractor: Extracts six screenshot images from the video at the timestamps corresponding to each identified step.
- Article Writer: Writes the text article describing the six steps based on the video transcription and identified steps.
- Image Integrator: Integrates the extracted screenshot images into the text article at the appropriate locations.
- Article Formatter: Formats the article with the integrated images into a suitable format for publishing (e.g., HTML, Markdown).

E) SUBAGENT 1: Video Recorder
- Name: Video Recorder
- Final Output: A video file (.mp4, .avi, or other suitable format) containing the narrator's explanation and demonstration of making software mockups with GIMP.
- Accomplishment: The Video Recorder subagent will use the connected camera and microphone to record the narrator's explanation and demonstration. It will save the recorded video in a suitable format with appropriate resolution and audio quality.
- Sequence: Initialize camera and microphone > Start recording > Monitor recording process > Stop recording when the narrator finishes > Save the recorded video file

F) SUBAGENT 2: Transcriber
- Name: Transcriber
- Final Output: A text file containing the transcription of the video, including the narration and corresponding timestamps.
- Accomplishment: The Transcriber subagent will use a speech recognition API (e.g., Google Speech-to-Text, AWS Transcribe) to convert the audio from the video into text. It will also generate timestamps for each sentence or phrase in the transcription.
- Sequence: Load the video file > Extract audio from the video > Send audio to speech recognition API > Receive transcription with timestamps > Save the transcription as a text file

G) SUBAGENT 3: Step Analyzer
- Name: Step Analyzer
- Final Output: A list of the six main steps identified from the video transcription.
- Accomplishment: The Step Analyzer subagent will use natural language processing techniques to analyze the video transcription and identify the six main steps of the process. It will look for key phrases, action words, and transitions to determine the steps.
- Sequence: Load the transcription file > Perform linguistic analysis (e.g., part-of-speech tagging, dependency parsing) > Identify action words and key phrases > Determine the six main steps based on the analysis > Save the list of steps

H) SUBAGENT 4: Image Extractor
- Name: Image Extractor
- Final Output: Six image files (.png, .jpg, or other suitable format) containing screenshots from the video corresponding to each identified step.
- Accomplishment: The Image Extractor subagent will use video processing libraries (e.g., OpenCV, FFmpeg) to extract screenshots from the video at the timestamps corresponding to each identified step. It will save the extracted images in a suitable format.
- Sequence: Load the video file and the list of steps with timestamps > For each step, seek to the corresponding timestamp in the video > Capture a screenshot at that timestamp > Save the screenshot as an image file

I) SUBAGENT 5: Article Writer
- Name: Article Writer
- Final Output: A text file containing the article describing the six steps of making software mockups with GIMP, based on the video transcription and identified steps.
- Accomplishment: The Article Writer subagent will use the video transcription and the list of identified steps to generate a coherent and well-structured text article. It will organize the content into sections, add headings, and ensure clarity and readability.
- Sequence: Load the transcription file and the list of steps > For each step, extract relevant information from the transcription > Organize the information into a logical structure > Write the article with clear headings and descriptions for each step > Save the article as a text file

J) SUBAGENT 6: Image Integrator
- Name: Image Integrator
- Final Output: A text file containing the article with the extracted images integrated at the appropriate locations.
- Accomplishment: The Image Integrator subagent will combine the text article and the extracted images by inserting the images at the relevant locations within the article. It will ensure proper formatting and alignment of the images.
- Sequence: Load the article text file and the extracted image files > For each step in the article, find the corresponding image file > Insert the image into the article at the appropriate location > Adjust formatting and alignment of the images > Save the updated article with integrated images

K) SUBAGENT 7: Article Formatter
- Name: Article Formatter
- Final Output: An HTML or Markdown formatted file containing the final article with integrated images, ready for publishing on a website or blog.
- Accomplishment: The Article Formatter subagent will take the article with integrated images and format it into a suitable format for publishing, such as HTML or Markdown. It will add necessary tags, styles, and metadata to ensure proper rendering on a website or blog.
- Sequence: Load the article file with integrated images > Determine the desired output format (HTML or Markdown) > Add appropriate tags, styles, and metadata based on the chosen format > Validate the formatted article for correctness and compatibility > Save the final formatted article file

subagent-summary-amended-for-actual-tasks

Based on the available tasks, here are the updated subagents that will work together to transform the initial input (the video recording) into the required output (a text-based article with embedded images):

A) FULL TASK SUMMARY: Create a text-based article with embedded images explaining how to make software mockups using GIMP, based on a video recording of the process.

C) COMPONENTS OVERVIEW:
1. Video recording of the process (provided by the user)
2. Text transcription of the video with timestamps
3. Identification of the six main steps from the transcription
4. Extraction of six screenshot images corresponding to each step
5. Text article describing the six steps based on the transcription and identified steps
6. Integration of the extracted images into the text article
7. Final formatting of the article for publishing

D) OVERVIEW OF SUBAGENTS:
- Transcriber: Generates a text transcription of the video, including the narration and corresponding timestamps.
- Step Analyzer: Analyzes the video transcription to identify the six main steps of the process.
- Image Extractor: Extracts six screenshot images from the video at the timestamps corresponding to each identified step.
- Article Writer: Writes the text article describing the six steps based on the video transcription and identified steps.
- Image Integrator: Integrates the extracted screenshot images into the text article at the appropriate locations.
- Article Formatter: Formats the article with the integrated images into a suitable format for publishing (e.g., HTML, Markdown).

E) SUBAGENT 1: Transcriber
- Name: Transcriber
- Final Output: A text file containing the transcription of the video, including the narration and corresponding timestamps.
- Accomplishment: The Transcriber subagent will use Task 32 (Get text transcription of mp3 (SRT subtitles)) to convert the audio from the video into text with timestamps.
- Sequence: Save the video file to the server > Extract audio from the video using Task 44 (Convert mp4 to mp3) > Use Task 32 to generate the transcription with timestamps > Save the transcription as a text file using Task 9 (Save content to server)

F) SUBAGENT 2: Step Analyzer
- Name: Step Analyzer
- Final Output: A list of the six main steps identified from the video transcription.
- Accomplishment: The Step Analyzer subagent will use Task 1 (GPT4) to analyze the video transcription and identify the six main steps of the process.
- Sequence: Load the transcription file using Task 10 (Access text files already saved) > Use Task 1 to perform linguistic analysis and identify the six main steps > Save the list of steps using Task 9

G) SUBAGENT 3: Image Extractor
- Name: Image Extractor
- Final Output: Six image files containing screenshots from the video corresponding to each identified step.
- Accomplishment: The Image Extractor subagent will use Task 45 (Split/extract video by interval) to extract screenshots from the video at the timestamps corresponding to each identified step.
- Sequence: Load the video file and the list of steps with timestamps > For each step, use Task 45 to extract a screenshot at the corresponding timestamp > Save the screenshots as image files using Task 9

H) SUBAGENT 4: Article Writer
- Name: Article Writer
- Final Output: A text file containing the article describing the six steps of making software mockups with GIMP, based on the video transcription and identified steps.
- Accomplishment: The Article Writer subagent will use Task 1 (GPT4) to generate a coherent and well-structured text article using the video transcription and the list of identified steps.
- Sequence: Load the transcription file and the list of steps using Task 10 > Use Task 1 to generate the article with clear headings and descriptions for each step > Save the article as a text file using Task 9

I) SUBAGENT 5: Image Integrator
- Name: Image Integrator
- Final Output: A text file containing the article with the extracted images integrated at the appropriate locations.
- Accomplishment: The Image Integrator subagent will use Task 1 (GPT4) to combine the text article and the extracted images by inserting the images at the relevant locations within the article.
- Sequence: Load the article text file and the extracted image files using Task 10 and Task 11 > Use Task 1 to integrate the images into the article at the appropriate locations > Save the updated article with integrated images using Task 9

J) SUBAGENT 6: Article Formatter
- Name: Article Formatter
- Final Output: An HTML or Markdown formatted file containing the final article with integrated images, ready for publishing on a website or blog.
- Accomplishment: The Article Formatter subagent will use Task 1 (GPT4) to format the article with integrated images into a suitable format for publishing, such as HTML or Markdown.
- Sequence: Load the article file with integrated images using Task 10 > Use Task 1 to format the article into HTML or Markdown with proper tags, styles, and metadata > Save the final formatted article file using Task 9

These subagents, using the available tasks, will work together to transform the initial video recording into a well-structured, text-based article with embedded images, ready for publishing on a website or blog.

random-autocomplete

To achieve the end goal of creating a text-based article with embedded images from a video tutorial on "how to make software mockups with GIMP," the most relevant tasks might be:

1. Transcribe the video to extract the spoken content and timestamps
2. Analyze the transcription to identify the six main steps in the tutorial
3. Extract screenshot images from the video at the relevant timestamps for each step
4. Generate a text article using the identified steps and the transcription content
5. Embed the extracted screenshot images into the article at the appropriate locations
6. Format the article for publishing on a website or blog (e.g., HTML, Markdown)

The overall sequence would be:

1. Video transcription > 
2. Transcription analysis and step identification > 
3. Image extraction from video > 
4. Article generation > 
5. Image embedding > 
6. Article formatting

To accomplish this, the Agent could use the following tools and APIs:

1. Video transcription: Use a speech-to-text API (e.g., Google Cloud Speech-to-Text, AWS Transcribe) to transcribe the video and obtain the spoken content along with timestamps.

2. Transcription analysis and step identification: Utilize an AI language model (e.g., GPT-3, BERT) to analyze the transcription, identify the main steps in the tutorial, and select the six most important steps.

3. Image extraction from video: Use a video processing library (e.g., OpenCV, FFmpeg) to extract screenshot images from the video at the timestamps corresponding to each identified step.

4. Article generation: Employ an AI language model (e.g., GPT-3) to generate a coherent text article based on the identified steps and the transcription content.

5. Image embedding: Use an HTML or Markdown library (e.g., Python-Markdown, BeautifulSoup) to embed the extracted screenshot images into the generated article at the appropriate locations.

6. Article formatting: Format the article with the embedded images using HTML or Markdown, ensuring it is suitable for publishing on a website or blog.

By following this sequence and utilizing the mentioned tools and APIs, the Agent should be able to effectively create a text-based article with embedded images from the video tutorial on "how to make software mockups with GIMP."

claude 3 - mermaid-for-all

SubAgent #1

claude 3 - subagent1

subagent1-refined

A) SUBAGENT SUMMARY: The Transcriber subagent generates a text transcription with timestamps from a video recording.

B) FINAL TASK OUTPUT: A text file containing the transcription of the video, including the narration and corresponding timestamps, saved as a .txt file on the server.

C) SUBAGENT INPUT: The URL of the video file (MP4 format) saved on the server.

D) SUBAGENT TASK SUMMARY:
1. Input: Video URL (MP4 format) saved on the server
2. Use Task 44 (Convert mp4 to mp3) to extract the audio from the video and save it as an MP3 file on the server
3. Use Task 32 (Get text transcription of mp3 (SRT subtitles)) to generate a text transcription with timestamps from the MP3 file
4. Use Task 1 (GPT4) to process the SRT file and extract only the text and corresponding timestamps, formatting it as a plain text file
5. Use Task 9 (Save content to server) to save the formatted transcription as a .txt file on the server
6. Output: The URL of the saved transcription text file on the server

E) SILOS:
Silo 1: Audio Extraction
- Input: Video URL (MP4 format) saved on the server
- Task 44 (Convert mp4 to mp3) to extract audio and save as MP3
- Output: MP3 URL saved on the server

Silo 2: Transcription Generation
- Input: MP3 URL saved on the server
- Task 32 (Get text transcription of mp3 (SRT subtitles)) to generate SRT transcription
- Output: SRT transcription

Silo 3: Transcription Formatting
- Input: SRT transcription
- Task 1 (GPT4) to extract text and timestamps, formatting as plain text
- Output: Formatted plain text transcription

Silo 4: Transcription Saving
- Input: Formatted plain text transcription
- Task 9 (Save content to server) to save transcription as .txt file
- Output: URL of the saved transcription text file on the server

subagent1refined-repeating

A) SUBAGENT SUMMARY: The Transcriber subagent generates a text transcription with timestamps from a video recording.

B) FINAL TASK OUTPUT: A text file containing the transcription of the video, including the narration and corresponding timestamps, saved as a .txt file on the server.

C) SUBAGENT INPUT: The URL of the video file (MP4 format) saved on the server.

E) SILOS:
Silo 1: Audio Extraction
- Input: Video URL (MP4 format) saved on the server
- Task 44 (Convert mp4 to mp3) to extract audio and save as MP3
- Output: MP3 URL saved on the server

Silo 2: Transcription Generation
- Input: MP3 URL saved on the server
- Task 32 (Get text transcription of mp3 (SRT subtitles)) to generate SRT transcription
- Output: SRT transcription

Silo 3: Transcription Formatting
- Input: SRT transcription
- Task 1 (GPT4) to extract text and timestamps, formatting as plain text
- Output: Formatted plain text transcription

G) FULL TASKS (INCLUDING REPEATING TASKS):
1. Input: Video URL (MP4 format) saved on the server
2. Use Task 44 (Convert mp4 to mp3) to extract the audio from the video and save it as an MP3 file on the server
3. Use Task 32 (Get text transcription of mp3 (SRT subtitles)) to generate a text transcription with timestamps from the MP3 file
4. Use Task 1 (GPT4) to process the SRT file and extract only the text and corresponding timestamps, formatting it as a plain text file
5. Use Task 9 (Save content to server) to save the formatted transcription as a .txt file on the server
6. Output: The URL of the saved transcription text file on the server

In this case, there are no explicit instructions for repeating tasks, so the full task list remains the same as the subagent task summary. Each task is performed once to achieve the desired output.

Subagent1 task-ID-numbers

subagent1-output-variables

A) SUBAGENT SUMMARY: The Transcriber subagent generates a text transcription with timestamps from a video recording.

B) FINAL TASK OUTPUT: A text file containing the transcription of the video, including the narration and corresponding timestamps, saved as a .txt file on the server.

C) SUBAGENT INPUT: The URL of the video file (MP4 format) saved on the server.

D) SUBAGENT TASK SUMMARY:
1. Input: Video URL (MP4 format) saved on the server [video-url]
2. Use Task 44 (Convert mp4 to mp3) to extract the audio from the video and save it as an MP3 file on the server [audio-url]
3. Use Task 32 (Get text transcription of mp3 (SRT subtitles)) to generate a text transcription with timestamps from the MP3 file [srt-transcription]
4. Use Task 1 (GPT4) to process the SRT file and extract only the text and corresponding timestamps, formatting it as a plain text file [formatted-transcription]
5. Use Task 9 (Save content to server) to save the formatted transcription as a .txt file on the server [transcription-url]
6. Output: The URL of the saved transcription text file on the server [transcription-url]

E) SILOS:
Silo 1: Audio Extraction
- Input: Video URL (MP4 format) saved on the server [video-url]
- Task 44 (Convert mp4 to mp3) to extract audio and save as MP3 [audio-url]
- Output: MP3 URL saved on the server [audio-url]

Silo 2: Transcription Generation
- Input: MP3 URL saved on the server [audio-url]
- Task 32 (Get text transcription of mp3 (SRT subtitles)) to generate SRT transcription [srt-transcription]
- Output: SRT transcription [srt-transcription]

Silo 3: Transcription Formatting
- Input: SRT transcription [srt-transcription]
- Task 1 (GPT4) to extract text and timestamps, formatting as plain text [formatted-transcription]
- Output: Formatted plain text transcription [formatted-transcription]

Silo 4: Transcription Saving
- Input: Formatted plain text transcription [formatted-transcription]
- Task 9 (Save content to server) to save transcription as .txt file [transcription-url]
- Output: URL of the saved transcription text file on the server [transcription-url]

G) FULL TASKS (INCLUDING REPEATING TASKS):
1. Input: Video URL (MP4 format) saved on the server [video-url]
2. Use Task 44 (Convert mp4 to mp3) to extract the audio from the video and save it as an MP3 file on the server [audio-url]
3. Use Task 32 (Get text transcription of mp3 (SRT subtitles)) to generate a text transcription with timestamps from the MP3 file [srt-transcription]
4. Use Task 1 (GPT4) to process the SRT file and extract only the text and corresponding timestamps, formatting it as a plain text file [formatted-transcription]
5. Use Task 9 (Save content to server) to save the formatted transcription as a .txt file on the server [transcription-url]
6. Output: The URL of the saved transcription text file on the server [transcription-url]

H) OUTPUT TOKENS:
- [video-url]: The URL of the video file (MP4 format) saved on the server
- [audio-url]: The URL of the extracted audio file (MP3 format) saved on the server
- [srt-transcription]: The SRT transcription generated from the MP3 file
- [formatted-transcription]: The formatted plain text transcription extracted from the SRT file
- [transcription-url]: The URL of the saved transcription text file (.txt format) on the server

subagent1refined-repeating-json-core

G) TASKFLOW SUMMARY

Task 1: Extract Audio from Video
Description: Use a video-to-audio conversion tool to extract the audio from the input video file and save it as an MP3 file on the server.
Input(s) involved: [video_url]
Output token name: [mp3_url]

Task 2: Generate SRT Transcription
Description: Use a speech-to-text transcription service to generate an SRT file containing the text transcription and corresponding timestamps from the input MP3 file.
Input(s) involved: [mp3_url]
Output token name: [srt_transcription]

Task 3: Format SRT Transcription
Description: Process the SRT file using a language model to extract only the text and timestamps, formatting it as a plain text file for easier readability and processing.
Input(s) involved: [srt_transcription]
Output token name: [formatted_transcription]

Task 4: Save Transcription to Server
Description: Save the formatted plain text transcription as a .txt file on the server, making it accessible via a unique URL for further processing or retrieval.
Input(s) involved: [formatted_transcription]
Output token name: [transcription_url]

subagent1mermaid

SubAgent #2

claude 3 - subagent2

subagent2-refined

A) SUBAGENT SUMMARY: The Step Analyzer subagent analyzes the video transcription to identify the six main steps of the process.

B) FINAL TASK OUTPUT: A text file containing a list of the six main steps identified from the video transcription, with each step on a separate line.

C) SUBAGENT INPUT:
- A text file containing the transcription of the video, including the narration and corresponding timestamps.

D) SUBAGENT TASK SUMMARY:
1. Load the transcription file using Task 10 (Access text files already saved)
2. Use Task 1 (GPT4) to analyze the transcription and identify the six main steps:
   - Provide the transcription text as input to GPT4
   - Request GPT4 to identify the six most important steps in the process, based on the content and context of the transcription
   - If the transcription explicitly mentions fewer than six steps, ask GPT4 to break down the mentioned steps into more granular sub-steps to reach a total of six
   - If the transcription mentions more than six steps, ask GPT4 to consolidate related steps and prioritize the most critical ones to arrive at six main steps
   - GPT4 should return the six identified steps as a list, with each step on a separate line
3. Save the list of steps as a text file using Task 9 (Save content to server)

E) SILOS:
Silo 1: Transcription Loading
- Task 10: Access the video transcription text file from the server

Silo 2: Step Identification
- Task 1 (GPT4): Analyze the transcription to identify the six main steps
  - Input: Video transcription text
  - Output: List of six main steps, with each step on a separate line

Silo 3: Step List Saving
- Task 9: Save the list of identified steps as a text file on the server

The Step Analyzer subagent focuses on processing the video transcription to extract the six most important steps in the described process. By using GPT4's language understanding capabilities, it can analyze the content and context of the transcription to identify and prioritize the key steps, ensuring that the final output consists of six main steps, even if the original transcription mentions fewer or more steps. The resulting list of steps will be saved as a text file, ready to be used by the other subagents in the workflow.

subagent2refined-repeating

G) FULL TASKS (INCLUDING REPEATING TASKS):

1. Load the transcription file using Task 10 (Access text files already saved)
2. Use Task 1 (GPT4) to analyze the transcription and identify the six main steps:
   a. Provide the transcription text as input to GPT4
   b. Request GPT4 to identify the six most important steps in the process, based on the content and context of the transcription
   c. If the transcription explicitly mentions fewer than six steps:
      i. Ask GPT4 to break down the mentioned steps into more granular sub-steps to reach a total of six
   d. If the transcription mentions more than six steps:
      i. Ask GPT4 to consolidate related steps and prioritize the most critical ones to arrive at six main steps
   e. GPT4 should return the six identified steps as a list, with each step on a separate line
3. Save the list of steps as a text file using Task 9 (Save content to server)

In this specific case, there are no explicitly stated repetitions of the same individual tasks. The subagent is designed to analyze the transcription once and extract the six main steps, regardless of the number of steps initially mentioned in the transcription. The process involves a single iteration of loading the transcription, analyzing it with GPT4, and saving the resulting list of steps.

Subagent2 task-ID-numbers

subagent2-output-variables

Here's the updated task list with the output tokens added:

G) FULL TASKS (INCLUDING REPEATING TASKS):

1. Load the transcription file using Task 10 (Access text files already saved)
   - Output token: [transcription]

2. Use Task 1 (GPT4) to analyze the transcription and identify the six main steps:
   a. Provide the transcription text as input to GPT4
      - Input token: [transcription]
   b. Request GPT4 to identify the six most important steps in the process, based on the content and context of the transcription
   c. If the transcription explicitly mentions fewer than six steps:
      i. Ask GPT4 to break down the mentioned steps into more granular sub-steps to reach a total of six
   d. If the transcription mentions more than six steps:
      i. Ask GPT4 to consolidate related steps and prioritize the most critical ones to arrive at six main steps
   e. GPT4 should return the six identified steps as a list, with each step on a separate line
      - Output token: [steps-list]

3. Save the list of steps as a text file using Task 9 (Save content to server)
   - Input token: [steps-list]
   - Output token: [steps-file]

H) OUTPUT TOKENS

- [transcription]: The loaded transcription file
- [steps-list]: The list of six main steps identified by GPT4 from the transcription
- [steps-file]: The saved text file containing the list of steps

However, if the requirement was to analyze multiple transcriptions or to extract a different number of steps for each transcription, the task list would need to be adjusted accordingly to include the necessary repetitions, and the output tokens would be numbered accordingly, e.g., [transcription1], [transcription2], [steps-list1], [steps-list2], [steps-file1], [steps-file2], etc.

subagent2refined-repeating-json-core

G) TASKFLOW SUMMARY

Title task: Load transcription file
Description of the task: Access the transcription file stored on the server using the predefined Task 10 (Access text files already saved) and load its contents for further processing.
Input(s) involved: [transcription_file_path]
Output token name: [loaded_transcription_text]

Title task: Analyze transcription with GPT4
Description of the task: Provide the loaded transcription text to GPT4 and request it to identify the six most important steps in the process, adjusting the number of steps based on the content of the transcription.
Input(s) involved: [loaded_transcription_text]
Output token name: [identified_steps_list]

Title task: Adjust steps based on transcription content
Description of the task: If the transcription explicitly mentions fewer than six steps, ask GPT4 to break down the mentioned steps into more granular sub-steps to reach a total of six. If the transcription mentions more than six steps, ask GPT4 to consolidate related steps and prioritize the most critical ones to arrive at six main steps.
Input(s) involved: [identified_steps_list]
Output token name: [adjusted_steps_list]

Title task: Format steps as a list
Description of the task: GPT4 should return the six identified steps as a list, with each step on a separate line, to ensure a consistent and easily readable format for further processing.
Input(s) involved: [adjusted_steps_list]
Output token name: [formatted_steps_list]

Title task: Save steps list as a text file
Description of the task: Use Task 9 (Save content to server) to save the formatted list of steps as a text file on the server for later use in generating the final article.
Input(s) involved: [formatted_steps_list]
Output token name: [saved_steps_file_path]

subagent2mermaid

SubAgent #3

claude 3 - subagent3

subagent1-refined

A) SUBAGENT SUMMARY: The Image Extractor subagent extracts six screenshot images from the video at the timestamps corresponding to each identified step.

B) FINAL TASK OUTPUT: Six image files (PNG or JPEG format) containing screenshots from the video corresponding to each identified step. The images should have a resolution suitable for embedding in a web article (e.g., 1280x720 pixels or higher).

C) SUBAGENT INPUT:
1. The video file (MP4 format) from which the screenshots will be extracted.
2. A text file containing the list of six main steps identified by the Step Analyzer subagent, along with their corresponding timestamps in the video.

E) SUBAGENT TASK SUMMARY:
1. Load the video file (MP4) and the text file containing the list of steps with timestamps.
2. For each step in the list:
   a. Use Task 45 (Split/extract video by interval) to extract a screenshot from the video at the corresponding timestamp.
   b. Save the extracted screenshot as an image file (PNG or JPEG format) using Task 9 (Save content to server).
3. Output the URLs of the six saved screenshot image files.

Detailed task sequence:
- Input: Video file (MP4) URL, Text file URL containing steps and timestamps
- Task 10 (Access text files already saved): Load the text file containing the list of steps and timestamps
- Task 1 (GPT4): Parse the text file to extract the six steps and their corresponding timestamps
- For each step:
  - Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp
  - Task 9 (Save content to server): Save the extracted screenshot as an image file (PNG or JPEG format)
- Task 1 (GPT4): Generate a list of the six saved screenshot image file URLs
- Output: List of six screenshot image file URLs

F) SILOS:
Silo 1: Load input files
- Load the video file (MP4) URL
- Load the text file URL containing the list of steps and timestamps

Silo 2: Extract and save screenshots
- For each step:
  - Extract a screenshot from the video at the corresponding timestamp
  - Save the extracted screenshot as an image file (PNG or JPEG format)

Silo 3: Generate output
- Generate a list of the six saved screenshot image file URLs
- Output the list of screenshot image file URLs

subagent1refined-repeating

G) FULL TASKS (INCLUDING REPEATING TASKS):

1. Task 10 (Access text files already saved): Load the text file containing the list of steps and timestamps
2. Task 1 (GPT4): Parse the text file to extract the six steps and their corresponding timestamps
3. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 1
4. Task 9 (Save content to server): Save the extracted screenshot for step 1 as an image file (PNG or JPEG format)
5. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 2
6. Task 9 (Save content to server): Save the extracted screenshot for step 2 as an image file (PNG or JPEG format)
7. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 3
8. Task 9 (Save content to server): Save the extracted screenshot for step 3 as an image file (PNG or JPEG format)
9. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 4
10. Task 9 (Save content to server): Save the extracted screenshot for step 4 as an image file (PNG or JPEG format)
11. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 5
12. Task 9 (Save content to server): Save the extracted screenshot for step 5 as an image file (PNG or JPEG format)
13. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 6
14. Task 9 (Save content to server): Save the extracted screenshot for step 6 as an image file (PNG or JPEG format)
15. Task 1 (GPT4): Generate a list of the six saved screenshot image file URLs
16. Output: List of six screenshot image file URLs

Subagent1 task-ID-numbers3

subagent3-output-variables

Here's the updated task list with the added section for output tokens:

G) FULL TASKS (INCLUDING REPEATING TASKS):

1. Task 10 (Access text files already saved): Load the text file containing the list of steps and timestamps
   Output: [steps-timestamps-file]

2. Task 1 (GPT4): Parse the text file to extract the six steps and their corresponding timestamps
   Input: [steps-timestamps-file]
   Output: [step1], [step1-timestamp], [step2], [step2-timestamp], [step3], [step3-timestamp], [step4], [step4-timestamp], [step5], [step5-timestamp], [step6], [step6-timestamp]

3. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 1
   Input: [step1-timestamp]
   Output: [step1-screenshot]

4. Task 9 (Save content to server): Save the extracted screenshot for step 1 as an image file (PNG or JPEG format)
   Input: [step1-screenshot]
   Output: [step1-screenshot-url]

5. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 2
   Input: [step2-timestamp]
   Output: [step2-screenshot]

6. Task 9 (Save content to server): Save the extracted screenshot for step 2 as an image file (PNG or JPEG format)
   Input: [step2-screenshot]
   Output: [step2-screenshot-url]

7. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 3
   Input: [step3-timestamp]
   Output: [step3-screenshot]

8. Task 9 (Save content to server): Save the extracted screenshot for step 3 as an image file (PNG or JPEG format)
   Input: [step3-screenshot]
   Output: [step3-screenshot-url]

9. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 4
   Input: [step4-timestamp]
   Output: [step4-screenshot]

10. Task 9 (Save content to server): Save the extracted screenshot for step 4 as an image file (PNG or JPEG format)
    Input: [step4-screenshot]
    Output: [step4-screenshot-url]

11. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 5
    Input: [step5-timestamp]
    Output: [step5-screenshot]

12. Task 9 (Save content to server): Save the extracted screenshot for step 5 as an image file (PNG or JPEG format)
    Input: [step5-screenshot]
    Output: [step5-screenshot-url]

13. Task 45 (Split/extract video by interval): Extract a screenshot from the video at the corresponding timestamp for step 6
    Input: [step6-timestamp]
    Output: [step6-screenshot]

14. Task 9 (Save content to server): Save the extracted screenshot for step 6 as an image file (PNG or JPEG format)
    Input: [step6-screenshot]
    Output: [step6-screenshot-url]

15. Task 1 (GPT4): Generate a list of the six saved screenshot image file URLs
    Input: [step1-screenshot-url], [step2-screenshot-url], [step3-screenshot-url], [step4-screenshot-url], [step5-screenshot-url], [step6-screenshot-url]
    Output: [screenshot-url-list]

16. Output: List of six screenshot image file URLs
    Output: [screenshot-url-list]

H) OUTPUT TOKENS

[steps-timestamps-file], [step1], [step1-timestamp], [step2], [step2-timestamp], [step3], [step3-timestamp], [step4], [step4-timestamp], [step5], [step5-timestamp], [step6], [step6-timestamp], [step1-screenshot], [step1-screenshot-url], [step2-screenshot], [step2-screenshot-url], [step3-screenshot], [step3-screenshot-url], [step4-screenshot], [step4-screenshot-url], [step5-screenshot], [step5-screenshot-url], [step6-screenshot], [step6-screenshot-url], [screenshot-url-list]

subagent3refined-repeating-json-core

A) SUBAGENT SUMMARY: Extract screenshots from a video at specified timestamps and generate a list of image file URLs.

B) FINAL TASK OUTPUT: A list of six screenshot image file URLs in a text file format.

C) SUBAGENT INPUT:
- A text file containing the list of six steps and their corresponding timestamps
- The video file from which screenshots need to be extracted

E) SUBAGENT TASK SUMMARY:
1. Load the text file containing the list of steps and timestamps
2. Parse the text file to extract the six steps and their corresponding timestamps
3. For each step (1-6):
   a. Extract a screenshot from the video at the corresponding timestamp
   b. Save the extracted screenshot as an image file (PNG or JPEG format)
4. Generate a list of the six saved screenshot image file URLs
5. Output the list of six screenshot image file URLs

G) TASKFLOW SUMMARY:

Task 1:
Title task: Load steps and timestamps text file
Description of the task: Load the text file that contains the list of six steps and their corresponding timestamps from the video.
Input(s) involved: [text_file_path]
Output token name: [loaded_text_file]

Task 2:
Title task: Extract steps and timestamps
Description of the task: Parse the loaded text file to extract the six steps and their corresponding timestamps.
Input(s) involved: [loaded_text_file]
Output token name: [steps_and_timestamps]

Task 3:
Title task: Extract screenshot for step 1
Description of the task: Extract a screenshot from the video at the corresponding timestamp for step 1.
Input(s) involved: [video_file_path], [steps_and_timestamps]
Output token name: [screenshot_step_1]

Task 4:
Title task: Save screenshot for step 1
Description of the task: Save the extracted screenshot for step 1 as an image file (PNG or JPEG format).
Input(s) involved: [screenshot_step_1]
Output token name: [saved_screenshot_step_1]

Task 5:
Title task: Extract screenshot for step 2
Description of the task: Extract a screenshot from the video at the corresponding timestamp for step 2.
Input(s) involved: [video_file_path], [steps_and_timestamps]
Output token name: [screenshot_step_2]

Task 6:
Title task: Save screenshot for step 2
Description of the task: Save the extracted screenshot for step 2 as an image file (PNG or JPEG format).
Input(s) involved: [screenshot_step_2]
Output token name: [saved_screenshot_step_2]

Task 7:
Title task: Extract screenshot for step 3
Description of the task: Extract a screenshot from the video at the corresponding timestamp for step 3.
Input(s) involved: [video_file_path], [steps_and_timestamps]
Output token name: [screenshot_step_3]

Task 8:
Title task: Save screenshot for step 3
Description of the task: Save the extracted screenshot for step 3 as an image file (PNG or JPEG format).
Input(s) involved: [screenshot_step_3]
Output token name: [saved_screenshot_step_3]

Task 9:
Title task: Extract screenshot for step 4
Description of the task: Extract a screenshot from the video at the corresponding timestamp for step 4.
Input(s) involved: [video_file_path], [steps_and_timestamps]
Output token name: [screenshot_step_4]

Task 10:
Title task: Save screenshot for step 4
Description of the task: Save the extracted screenshot for step 4 as an image file (PNG or JPEG format).
Input(s) involved: [screenshot_step_4]
Output token name: [saved_screenshot_step_4]

Task 11:
Title task: Extract screenshot for step 5
Description of the task: Extract a screenshot from the video at the corresponding timestamp for step 5.
Input(s) involved: [video_file_path], [steps_and_timestamps]
Output token name: [screenshot_step_5]

Task 12:
Title task: Save screenshot for step 5
Description of the task: Save the extracted screenshot for step 5 as an image file (PNG or JPEG format).
Input(s) involved: [screenshot_step_5]
Output token name: [saved_screenshot_step_5]

Task 13:
Title task: Extract screenshot for step 6
Description of the task: Extract a screenshot from the video at the corresponding timestamp for step 6.
Input(s) involved: [video_file_path], [steps_and_timestamps]
Output token name: [screenshot_step_6]

Task 14:
Title task: Save screenshot for step 6
Description of the task: Save the extracted screenshot for step 6 as an image file (PNG or JPEG format).
Input(s) involved: [screenshot_step_6]
Output token name: [saved_screenshot_step_6]

Task 15:
Title task: Generate screenshot URLs list
Description of the task: Generate a list of the six saved screenshot image file URLs.
Input(s) involved: [saved_screenshot_step_1], [saved_screenshot_step_2], [saved_screenshot_step_3], [saved_screenshot_step_4], [saved_screenshot_step_5], [saved_screenshot_step_6]
Output token name: [screenshot_urls_list]

Task 16:
Title task: Output screenshot URLs list
Description of the task: Output the list of six screenshot image file URLs.
Input(s) involved: [screenshot_urls_list]
Output token name: [final_output]

subagent3mermaid

prompts-required

Based on the components identified for the task of creating a text article with embedded images on how to make software mockups with GIMP, the following unique prompts would be required:

Task: Step Identification
Output of the task: A list of six main steps for making software mockups with GIMP
Description: Analyze the provided video transcription and identify the six most important steps for making software mockups with GIMP. If the narrator does not explicitly mention six steps, determine the most crucial steps based on the content and context of the transcription. Each step should be concisely summarized in one or two sentences.

Task: Article Text Generation
Output of the task: A well-structured text article describing the six steps of making software mockups with GIMP
Description: Using the video transcription and the identified six steps, generate a text article that guides readers through the process of making software mockups with GIMP. The article should have clear headings for each step and provide concise explanations of the actions involved. Ensure that the text is well-written, easy to understand, and follows a logical flow from one step to the next.

Task: Image Integration Instructions
Output of the task: Instructions for integrating the extracted screenshot images into the text article
Description: Provide clear instructions on where and how to integrate the six extracted screenshot images into the text article. Specify the exact location for each image (e.g., after which paragraph or sentence) and provide any necessary formatting guidelines to ensure the images are properly displayed alongside the corresponding steps in the article.

Task: Final Article Formatting
Output of the task: Instructions for formatting the article with integrated images into a suitable format for publishing
Description: Give detailed instructions on how to format the final article, including the text and integrated images, into a format suitable for publishing on a website or blog (e.g., HTML, Markdown). Provide any necessary code snippets, templates, or guidelines to ensure the formatted article is ready for uploading and displays correctly on the intended platform.

These unique prompts cover the main tasks that require the involvement of an LLM in the overall workflow. The other components, such as video recording, video transcription, and image extraction, would be handled by separate tools or processes.