Detect meeting type and extract structured data from transcripts.
npx skills add https://github.com/KISHOR403/claude-skills --skill meeting-processor
Please help me install this Agent Skill. Skill: meeting-processor Source: https://github.com/KISHOR403/claude-skills/tree/main/meeting-processor Command: npx skills add https://github.com/KISHOR403/claude-skills --skill meeting-processor
Intelligent meeting transcripts require manual analysis and extraction of commitments, decisions, and follow-ups. This skill automates detection of meeting type and generates a structured, type-specific analysis that can be appended to transcripts.
Run the processor on a transcript to auto-detect its type and generate a structured analysis.
High-intent search queries and answers about installing and using this skill.
To auto-detect meeting type from transcripts, the processor identifies whether the session is leadgen, partnership, coaching, or internal, then extracts commitments, follow-ups, context, and sentiment into a structured payload appended directly to the transcript.
Yes, batch processing meeting transcripts is fully supported. The processor automates type detection and structured extraction across large sets of real-world sales, partnership, coaching, and internal review transcripts without requiring manual intervention.
Yes, extracting structured meeting data requires Python 3.8+ and an OpenAI or Cerebras interface. These dependencies handle the natural language processing needed to identify meeting types and generate type-specific analysis sections.
The best way to preserve YAML frontmatter during meeting analysis is using a frontmatter-aware processor that maintains existing metadata integrity while appending a consistent, structured Meeting Analysis section to the end of the transcript file.
Yes, interactive mode supports clarifying questions for incomplete transcripts. It guides users through data completion by asking targeted questions, ensuring accurate meeting type detection and comprehensive extraction of commitments and follow-ups.
Wrong meeting type detection usually happens when transcript content is ambiguous or lacks clear indicators for leadgen, partnership, coaching, or internal categories. Using interactive mode can help clarify context and improve auto-detection accuracy.
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