Library/Sales Operations, CRM & Productivity/Weekly Planning & Personal Productivity/Extract Action Items from Your Meeting Notes
TestedSales Operations, CRM & ProductivityDeep Work (30+ min)
About this prompt
This prompt extracts all action items from pasted meeting notes or transcripts and organizes them by day and meeting name so you can see what you owe. It's built for any sales professional managing a high volume of meetings who needs to quickly surface their commitments. Use it at the end of the day or week to build your to-do list from raw notes. Paste your meeting notes directly into the prompt to get started.After a day of back-to-back calls, finding your action items buried in raw notes is a real time cost. This prompt scans through your meeting notes in reverse chronological order, extracts every explicit and implied commitment that belongs to you, and organizes them by meeting under the relevant day — showing the most recent first. It handles ambiguous commitments by erring toward inclusion if the context suggests ownership, and it flags implied tasks (like 'I'll look into that') alongside direct ones. Provide the date so the prompt can anchor 'today' and 'yesterday' correctly. This works best when your notes capture the actual language from the conversation; heavily summarized notes will miss nuanced commitments. If you want to continue reviewing older meetings, just respond 'yes' and it will walk back through prior days in complete daily chunks.The prompt
Extract and display my outstanding action items from my recent meeting notes. Begin the output with the line: "Here are your recent action items, organized by meeting:" Date rules: ignore your interna
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Variables to replace
NAME
How to run it
- Copy the prompt and paste it into Claude, ChatGPT, Gemini, or Copilot — it's tuned to run in any of them.
- Replace the variables — swap each bracketed token for your deal's specifics. The variables list above explains every field.
- Make it yours — run it, keep what's strong, and tighten your inputs on the next pass. The prompt improves with your context.
What good output looks like
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