Deep Meeting Minutes Generator

The Challenge: From Noisy Transcripts to Actionable Minutes

Transcripts of meeting audio are often lengthy, filled with conversational filler, repetitions, and irrelevant chatter. Distributing or reviewing these raw records is inefficient, as key decisions and action items can easily get buried. What stakeholders and managers need is not a verbatim log, but structured information that can be immediately used for follow-up and decision-making.

How the Skill Works: Pre-processing, Extraction, and Structured Output

This skill addresses the challenge with an automated pipeline that transforms raw materials into professional minutes.

Core Processing Logic

1. Intelligent Cleaning & Structuring: It first filters the raw text, automatically removing phrases like "hello everyone" and "thanks for your time," as well as repeated expressions. It then segments and reorganizes the text based on speaker turns and topic boundaries.
2. Key Information Extraction: Within the cleaned text, the skill automatically identifies and tags four types of core information:
   • [Decision]: Conclusions or plans confirmed during the meeting.
   • [Action]: Explicit to-do items and task assignments.
   • [Pending]: Unresolved issues requiring follow-up.
   • [Data]: Key business metrics mentioned, such as revenue or growth rates.
3. Standardized Templated Output: After processing, the final minutes are generated as Markdown, strictly following a predefined structure to ensure clear information hierarchy:
   • Executive Summary: A concise 100-200 word summary at the beginning, distilling the meeting's purpose, core decisions, and critical issues for quick management review.
   • Discussion by Topic: The main body is divided by natural meeting topics, each module is self-contained, and incorporates the extracted tags like [Decision] and [Action].
   • Action Items List: All tasks are consolidated into a table, which mandates a specific responsible individual and a clear deadline (e.g., "2026-04-30").

Furthermore, the skill includes a full-dimension quality control mechanism. It automatically checks, for instance, if the summary is complete and if any action items were missed before delivery, ensuring output quality.

Use Cases and Boundaries

This skill is particularly suited for recurring meetings like operational analysis, project updates, and retrospectives, where crystallizing conclusions and assigning tasks is essential. Its effectiveness is highly dependent on the quality and completeness of the input text, requiring reasonably accurate meeting transcripts. The output is based on rule and prompt logic, focusing on information structuring and distillation, and does not include analysis of the veracity of statements or underlying business logic.