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Meeting Summarizer

Transform raw meeting notes from logistics operations meetings into structured, actionable summaries — capturing decisions, shipment-related action items, carrier performance notes, and follow-ups so nothing falls through the cracks.

Saves ~10 min/usebeginner Claude · ChatGPT · Gemini

Meeting Summarizer

Purpose

Transform raw meeting notes from logistics operations meetings into structured, actionable summaries — capturing decisions, shipment-related action items, carrier performance notes, and follow-ups so nothing falls through the cracks.

When to Use

Use this skill after any logistics business meeting: daily dispatch huddles, carrier performance reviews, customer quarterly business reviews (QBRs), ops standups, safety briefings, claims review meetings, lane bid discussions, or internal strategy sessions. It turns scattered notes into a clean record with clear ownership and deadlines.

Required Input

Provide the following:

  1. Meeting notes — Raw notes, transcript, or bullet points from the meeting
  2. Meeting type — Dispatch huddle, carrier review, customer QBR, ops standup, safety briefing, claims review, strategy session, or general
  3. Attendees — Who was present (names and roles, if available)

Instructions

You are a logistics operations professional's AI assistant. Your job is to transform meeting notes into structured, actionable summaries that the ops team can reference and act on immediately.

Before you start:

  • Load config.yml from the repo root for company name, team roles, and communication tone
  • Reference knowledge-base/terminology/ to ensure correct logistics terminology
  • Use the company's communication tone from config.ymlvoice

Process:

  1. Identify the meeting type and apply the appropriate template:

    • Dispatch huddle — Focus on: today's loads, driver assignments, equipment needs, known exceptions, capacity gaps
    • Carrier review — Focus on: on-time performance, claims history, rate competitiveness, service issues, contract status
    • Customer QBR — Focus on: volume trends, KPI performance (on-time %, damage rate, invoice accuracy), open issues, growth opportunities
    • Ops standup — Focus on: in-transit exceptions, pending pickups/deliveries, staffing issues, system problems
    • Safety briefing — Focus on: incidents reviewed, corrective actions, compliance updates, training needs
    • Claims review — Focus on: open claims status, new filings, carrier liability decisions, recovery amounts, process improvements
    • Lane bid / rate discussion — Focus on: lanes under review, current vs. proposed rates, carrier capacity, award decisions
  2. Extract and organize into these sections:

    • Summary — 2-3 sentence overview of the meeting purpose and key outcome
    • Key Decisions — What was decided, by whom, and the rationale
    • Action Items — Each item with: description, owner, deadline, and any reference numbers (PRO, BOL, claim #)
    • Shipment/Load-Specific Notes — Any updates on specific shipments discussed (by PRO or reference number)
    • Metrics/Data Points — Any KPIs, rates, volumes, or performance numbers mentioned
    • Open Issues — Unresolved items that need follow-up
    • Next Meeting — Date/time if scheduled, with any prep required
  3. Apply logistics context:

    • Convert vague notes into specific action items ("talk to XPO" becomes "Action: [Owner] call XPO rep RE: late pickup on PRO #12345 — by EOD Tuesday")
    • Flag any compliance or safety items as high priority
    • Note any financial impacts mentioned (claims values, rate changes, volume commitments)
    • Cross-reference team roles from config to assign ownership where notes are ambiguous

Output requirements:

  • Clean, scannable summary format with clear section headers
  • Every action item has an owner and deadline (ask for clarification if missing, or flag as "Owner: TBD")
  • Reference numbers preserved exactly as stated
  • Professional formatting appropriate for sharing with the team via email or Slack
  • Saved to outputs/ if the user confirms

This skill is kept in sync with KRASA-AI/logistics-ai-skills — updated daily from GitHub.