Extract structured decisions, action items, and follow-ups from meeting transcripts.
npx skills add https://github.com/ericosiu/ai-marketing-skills --skill ai-team-ops
Please help me install this Agent Skill. Skill: AI Team Ops Source: https://github.com/ericosiu/ai-marketing-skills/tree/main/team-ops Command: npx skills add https://github.com/ericosiu/ai-marketing-skills --skill ai-team-ops
This Skill helps you stop running teams on vibes by turning team performance signals and meeting discussions into structured, actionable decisions.
Use case example: After a quarterly review, run the team audit to identify underperformers and bottlenecks, then run the meeting extractor on weekly standups so every commitment becomes a trackable task.
Run the meeting extractor on a transcript named standup.txt and output results as Markdown.
High-intent search queries and answers about installing and using this skill.
You can extract action items from meeting transcripts by using LLM-powered extraction with JSON schema enforcement. This process converts transcripts into structured decisions, assigned tasks with owners and deadlines, open questions, and follow-up topics formatted as Markdown.
You can audit team performance by scoring individuals across output velocity, quality, independence, and initiative. The team audit stack-ranks members into A/B/C tiers and provides specific recommendations to identify bottlenecks and underperformers.
Yes, you can push extracted meeting action items to HubSpot as CRM tasks. This optional integration requires configuring environment variables to connect the LLM extraction output directly to your HubSpot workflow.
Yes, processing meeting transcripts requires both OpenAI and Anthropic dependencies for LLM extraction, along with the requests library. These dependencies power the structured JSON schema enforcement and batch processing across transcript directories.
The best way to batch process meeting transcripts for CRM task creation is to run LLM extraction across transcript directories with JSON schema enforcement. This outputs formatted Markdown and optionally pushes action items to HubSpot via environment variables.
JSON schema enforcement for meeting intelligence extraction ensures structured, consistent output of decisions and action items. It guarantees that LLM extraction yields trackable tasks with owners, deadlines, priority levels, and confidence scoring for reliable accountability.
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