Operations

Extract Action Items From Meeting Notes

Decisions actually made, commitments actually given — extracted from fragmentary meeting notes that never label their action items.

Overview

Meeting notes are the messiest extraction source there is: fragmentary, unordered, and full of discussion that sounds like decisions. This setup extracts meeting_date, attendees, decisions, action_items, owners, and next_meeting — with the two field descriptions doing the heavy lifting: decisions means "decisions actually made — not topics discussed", and the reading guidance warns that commitments hide in sentences like "Sara will send the deck". Skip Field keeps the output lean: a meeting with no decisions simply has no decisions key, instead of a row of nulls.

Workflow

Paste the notes raw
No cleanup needed — the source guidance expects fragments, bullets, and half-sentences.
Trust the decisions filter
"Decisions actually made — not topics discussed" is the line that keeps debate out of the record.
Mind the Skip Field behavior
Absent fields are omitted entirely — downstream consumers should check key existence, not null.

Why This Works

Commitment-aware guidance catches the action items notes never label
The decided-vs-discussed distinction lives in the field description, where the model reads it per-field
One-entry-per-item list rules make follow-ups countable and assignable

Best for

Recurring meetings whose notes pile up unprocessed
Teams that lose action items phrased conversationally
Follow-up workflows keyed on owners and next-meeting dates

Not for

Producing meeting minutes or a narrative summary — that's the Structured Summary Prompt
Judging whether decisions were good ones — extraction reports, it doesn't review

Use cases

Turning raw meeting notes into a decisions-and-actions record
Catching commitments phrased as "X will…" instead of labeled tasks
Listing owners separately so follow-ups have a name attached

Customize This Resource

Opens this setup in Extraction Prompt Generator. Generate to get the full extraction prompt — then adjust the fields, missing-data behavior, and ambiguity policy.

Open in Extraction Prompt Generator

Prompt Template

TASK
Extract decisions and follow-ups from the meeting notes in the input.

SOURCE
The input is meeting notes — fragmentary, unordered, and often missing context.
Reading guidance: Action items may be phrased as commitments ("Sara will…") rather than labeled tasks; decisions may hide inside discussion lines.

FIELDS TO EXTRACT
- meeting_date (optional): Date of the meeting
- attendees (optional): People present
- decisions (required): Decisions actually made — not topics discussed
- action_items (required): Concrete commitments, with the owner when stated
- owners (optional): People responsible for the action items
- next_meeting (optional): Date or trigger for the next meeting

EXTRACTION RULES
- meeting_date: Use ISO format (YYYY-MM-DD) when the date can be determined; otherwise extract it as written.
- attendees: List every person named — one entry per person, deduplicated.
- decisions: Extract every distinct item as a separate list entry; deduplicate near-identical ones.
- action_items: Extract every distinct item as a separate list entry; deduplicate near-identical ones.
- owners: List every person named — one entry per person, deduplicated.
- next_meeting: Use ISO format (YYYY-MM-DD) when the date can be determined; otherwise extract it as written.
- Extract values from the source text only — do not use outside knowledge to fill fields.
- Do not summarize or interpret the document — return only the fields listed above.

MISSING DATA
- If a field is not found in the source, omit it from the output entirely.
- Never invent or guess a value for a missing field.

AMBIGUITY POLICY
- Prefer explicitly stated information; infer a value only when the text strongly implies it.
- Keep any inference minimal — one short step from the text, never a chain of assumptions.

OUTPUT FORMAT
Return the extracted data as a single valid JSON object using the field names below.

EXAMPLE OF A VALID EXTRACTION
{
  "meeting_date": "2026-06-10",
  "attendees": [
    "Jane Smith",
    "Marco Ruiz"
  ],
  "decisions": [
    "Ship the beta to the first 50 customers"
  ],
  "action_items": [
    "Send the revised proposal — Jane, by Friday"
  ],
  "owners": [
    "Jane Smith",
    "Marco Ruiz"
  ],
  "next_meeting": "2026-06-10"
}

OUTPUT RULES
- Return only the JSON object — no text before or after it.
- Do not wrap the output in markdown code fences.
- Use the field names exactly as defined — no renaming, no extra fields.

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AI Meeting Notes Workflow Workflow · 3 steps

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