> Analyze meeting transcripts to extract decisions, action items, owners, due dates, open questions, and risks. Use after recorded meetings, sales calls, customer interviews, or planning sessions, or to build a decision log.
npx skills add https://github.com/borghei/Claude-Skills --skill meeting-insights
Turn raw meeting transcripts into a structured set of decisions, action items, owners, due dates, open questions, and risks.
meeting, meetings, transcript, notes, minutes, action items, decisions, decision log, follow-up, recap, sales call, customer interview, retrospective, standup, planning, async
Before extracting insights, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Speaker: text format drives owner attribution on action itemsStop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
transcript.txt (one speaker turn per line, format Speaker: text) python scripts/transcript_analyzer.py transcript.txt
assets/recap_template.md to send a follow-upGoal: Convert a 60-minute conversation into a 90-second readable summary that everyone can act on.
Steps:
python scripts/transcript_analyzer.py transcript.txtassets/recap_template.mdExpected Output: Recap with decisions, action items (owner + due date), open questions, and risks.
Time Estimate: 5-10 minutes vs. 30+ for manual note review.
Goal: Pull the signals out of a discovery call without losing the customer's actual words.
Steps:
python scripts/transcript_analyzer.py transcript.txt --jsonpains and quotes — these are the discovery signalsreferences/insight_extraction_patterns.md to triangulate across multiple interviewsExpected Output: Tagged customer pain list with verbatim quotes per insight.
Time Estimate: 15 minutes per interview after the call.
Goal: Build an organizational memory so the same decision is not re-litigated quarter after quarter.
Steps:
Expected Output: Append-only decision log searchable by topic and date.
Time Estimate: 2-3 minutes per meeting.
Reads a transcript text file and extracts:
# Human-readable
python scripts/transcript_analyzer.py transcript.txt
# JSON for programmatic use
python scripts/transcript_analyzer.py transcript.txt --json
Transcript format expected:
Alice: We need to decide on the launch date this week.
Bob: I'll send the draft by Friday.
Alice: Are we blocked on legal review?
Bob: Yes, that's the risk — if legal slips, launch slips.
references/insight_extraction_patterns.md — Heuristic triggers for decisions, actions, and risks; how to triangulate across interviewsassets/recap_template.md — Post-meeting recap email with placeholder sectionsproduct-team/user-story/ for converting interview pains into storiesproject-management/ for action-item trackingmarketing/ voice-of-customer workflowsInteractive daily standup/meeting update generator. Use when user says 'daily', 'standup', 'scrum update', 'status update', 'what did I do yesterday', 'prepare for meeting', 'morning update', or 'team sync'. Pulls activity from GitHub, Jira, and Claude Code session history. Conducts 4-question interview (yesterday, today, blockers, discussion topics) and generates formatted Markdown update.
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Take borghei/meeting-insights from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.