Gera Tools

Action Item Extractor

Extract actionable tasks and next steps from LLM-generated notes or reports.

Paste LLM-generated meeting notes or a report and extract the action items automatically. Detects action language (will, must, assign, by [date]), pulls out owners and deadlines, and outputs a clean Markdown task list — all in your browser. It runs free in your browser on Gera Tools, with nothing uploaded.

Last updated Source: Gera Tools

How does it know a sentence is an action?

It scores each sentence for action signals — modal verbs (will, must, should, need to), assignment phrases (assign, owner, responsible), and explicit imperatives — plus a date phrase boosts the score. Sentences above the threshold become tasks.

Turn LLM notes into a clean action list

LLMs are great at summarising a meeting or drafting a report — but the next steps end up buried in prose. This tool reads that prose and pulls out the action items, separating the task, the owner, and the deadline into a tidy checklist you can paste straight into a tracker. It runs entirely in your browser.

How it works

Each sentence is scored for “action-ness”:

  • Modal / intent verbs — will, must, should, need to, plan to, going to
  • Assignment language — assign, owner, responsible, action:, todo, follow up
  • Imperative openings — a sentence that starts with a bare verb (Send …, Review …, Schedule …)
  • Date signals — by Friday, due 12 March, before EOD — these boost the score because a dated sentence is almost always a commitment

Sentences above the sensitivity threshold become tasks. The extractor then runs a second pass to lift out a likely owner (@name, assigned to X, a leading proper noun) and a deadline (relative or absolute date phrases), shown only when confidently found.

Getting the best source text

The extraction quality depends on how clearly the source prose marks action items. Some patterns that extract cleanly:

  • “Sarah will send the revised proposal by Wednesday” — owner, action, deadline all present
  • “Action: update the API docs before the release” — explicit action tag
  • “We need to schedule a follow-up call next week” — modal verb + date signal

Patterns that need sensitivity adjustment:

  • Passive voice without an owner (“The report should be reviewed”) — task detected but owner blank
  • Implicit deadlines (“soon,” “ASAP”) — task detected but deadline blank; you will need to fill these in

Output format

Extracted tasks appear as a Markdown checklist:

- [ ] Send revised proposal (Owner: Sarah, Due: Wednesday)
- [ ] Update API docs (Due: before release)
- [ ] Schedule follow-up call (Due: next week)

The - [ ] format renders as an interactive checkbox in GitHub, Notion, Obsidian, Linear, and most modern trackers. You can paste it directly without reformatting.

Tips

  • Prompt your LLM to structure notes as “Owner — task — due date” and extraction becomes nearly perfect.
  • If real tasks are missed, lower the sensitivity threshold; if irrelevant sentences are captured, raise it.
  • Review owner and deadline fields — they are best-effort heuristics and may need corrections, especially for implicit or informal dates.

Why extract action items from AI notes specifically

LLM-generated meeting summaries and status reports often contain action items that were implicitly agreed but not made structurally explicit. A human writing the same summary would naturally bullet the next steps; an LLM summarizing from a transcript may embed them in flowing prose. This extractor bridges that gap — it applies the same action-identification logic a careful human editor would use, so you get the structured task list without rewriting the summary yourself.