Prompt

Meeting to Actions Prompt

Extract decisions, owners, and dates from a meeting transcript.

1 min readupdated 2026-07-04

/ quick answer

Run after every meeting to keep a clean action log. Extract decisions, owners, and dates from a meeting transcript.

Extract decisions, owners, and dates from a meeting transcript. Run after every meeting to keep a clean action log. Copy the prompt below, swap the bracketed variables for your own context, and run it in any capable model. This prompt node is part of the Onexial knowledge graph and links to related concepts, workflows and tools below.

Context

Run after every meeting to keep a clean action log.

Prompt

Extract from the transcript:
- Decisions (with rationale in 1 line).
- Actions (owner, deliverable, due date).
- Open questions (owner to answer).

Do not invent owners or dates. If unclear, mark as 'unassigned' or 'no date'.

Transcript:
{{transcript}}

Return as JSON.

Example Output

{
  "decisions": [{ "decision": "Ship v2 without dark mode", "rationale": "Time to launch" }],
  "actions": [{ "owner": "Ana", "deliverable": "Draft v2 changelog", "due": "2026-07-08" }],
  "open_questions": [{ "question": "Pricing tier for SMB?", "owner": "Rui" }]
}

Related Workflow

Workflow · AI Meeting Intelligence Workflow

/ frequently asked

What does the Meeting to Actions Prompt prompt do?

Run after every meeting to keep a clean action log.

Which AI models work with this prompt?

It is model-agnostic: it works with any capable general model. Replace the bracketed variables with your own context before running it.

What output should I expect?

{ "decisions": [{ "decision": "Ship v2 without dark mode", "rationale": "Time to launch" }], "actions": [{ "owner": "Ana", "deliverable": "Draft v2 changelog", "due": "2026-07-08" }], "open_questions": [{ "question": "Pricing tier for SMB?", "owner": "Rui" }] }.

/ topics#productivity #prompt

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