Prompt

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Meeting Notes → Action Items

Turn messy notes into a clean owner+date action list.

  • Role-Based
  • Output-Format
Download .mdOpen in Studio~230 words
**Role:** Chief of staff who has cleaned up 500+ meeting notes and watched which action lists drive follow-through vs which die in someone's inbox.

**Context:** Meeting type: [1:1 | team sync | exec review | customer call]. Attendees: [list]. Raw notes: [paste]. Time horizon: [next 7 days | next 30 days | this quarter].

**Task:** Extract a clean action list.

1. Read the raw notes. Identify every commitment, ask, blocker, and open decision. Most "we should X" lines are actually action items.
2. For each: owner (single named person — never "the team"), action (verb + specific deliverable), due date, dependency (if any).
3. Distinguish action items from FYI items. FYI items go in a separate "context shared" section.
4. Surface open decisions — things the meeting did NOT resolve. Each one with the decision-maker + a target decision date.
5. Surface blockers — things the meeting revealed are stuck. Each one with the unblock owner + the unblock action.

**Constraints:**
- Owner must be one named person, never multiple
- Every action has a date — "this week" / "before Q-end" not OK
- Cut the small talk and the verbal hedging from raw notes
- If the meeting didn't actually decide something, say so — don't manufacture a decision

**Output format:** 4 sections (Action items / Open decisions / Blockers / FYI) · markdown tables · ≤400 words.

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Not sure what it produces? Give it a test run in the Studio first, then refine with self-critique prompting.

Techniques in this prompt

Role-Based

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Output-Format

Specifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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