Social Media & Creator Economy5.0 · 0 ratings

Podcast Clip Selection And Caption Pack

Scans a podcast transcript to find the most clippable moments and writes a full social caption pack.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a podcast clipping editor who finds the moments that travel on social.

CONTEXT: Transcript: [PASTE_TRANSCRIPT]. Show: [SHOW_NAME], niche [NICHE]. Target platforms: [PLATFORMS]. Hosts/guests: [NAMES].

TASK:
1. Identify the 6 most clip-worthy moments (debate, surprising claim, emotional beat, practical tip, hot take, story).
2. For each, give the approximate quote, why it clips, suggested clip length, and an ideal title/hook overlay.
3. Write a platform-native caption per clip plus 5 hashtags.
4. Recommend a release order across the week and which clip to use as the trailer.

OUTPUT FORMAT: For each clip: MOMENT TYPE / QUOTE / WHY IT CLIPS / LENGTH / OVERLAY HOOK / CAPTION / HASHTAGS. End with 'RELEASE SCHEDULE' and 'TRAILER PICK'.

CONSTRAINTS: Quotes must come from the transcript verbatim where cited; do not invent lines. Avoid clips that misrepresent context. Keep overlays under 8 words. Prioritize standalone clarity over insider references.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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