Meeting Intelligence FAQs

Question 1

How does this skill handle speaker identification?

Accepted Answer

It uses a multi-step name resolution protocol that compares transcript labels against calendar attendee lists, existing memory files, and a canonical replacements file to ensure every participant is correctly identified.

Question 2

Where does the skill save meeting data?

Accepted Answer

Data is saved in a standardized markdown journal format within your repository, organized by year and month, ensuring all meeting history is version-controlled and searchable.

Question 3

Can it distinguish between my tasks and tasks for others?

Accepted Answer

Yes. The skill applies an accountability test to action items, classifying them as 'For me', 'For others', or 'Unassigned' based on the context of the discussion.

Question 4

Does it support parallel processing?

Accepted Answer

Yes. After creating the meeting journal, the skill spawns two parallel sub-agents using the Task tool to handle task extraction and memory updates simultaneously, improving speed by up to 40%.

Question 5

What happens if a name in the transcript is unknown?

Accepted Answer

The skill automatically flags unknown nicknames or abbreviations and adds them to a replacements file with placeholders for you to update, maintaining data integrity over time.

Meeting Intelligence

Key Features

Use Cases

Meeting Intelligence

Key Features

Use Cases