Cc Call Summariser

Call Summariser

Generates structured post-call summaries from transcripts or CSM notes. Extracts discussion points, decisions, action items, sentiment signals, and flags -- then routes extracted data to downstream skills for tracking and action. Part of the Communication & Content Production pillar.

This is a content extraction and structuring skill. It transforms unstructured conversation data into structured, actionable records. It does not interpret relationship dynamics or make strategic assessments -- those are human reads the CSM applies after reviewing the summary.

When to Run

• Triggered: After a customer call when a transcript is available (via Gong, Chorus, or equivalent)
• On-demand: When a CSM provides notes and requests a structured summary
• Batch: End-of-day processing of all calls from that day

Core Execution Logic

Step 1: Ingest Source Material

Accept input from any available source:

Step 2: Extract Discussion Points

Identify the 3-7 main topics covered during the call:

• Detect topic transitions in the transcript (shift in subject, new questions, agenda item changes)
• Summarise each topic in 1-2 sentences capturing what was discussed and any conclusion reached
• Preserve conversation order -- the sequence of discussion sometimes matters (what was raised first indicates priority)

Step 3: Extract Decisions and Commitments

Scan for explicit and implicit commitments:

For each action item captured:

• Action: What needs to happen (stated clearly, not verbatim)
• Owner: Who committed. If "let's" without a name, flag as "Owner TBD -- confirm"
• Deadline: Explicit date if stated. Inferred date if implied ("next week" = [specific date]). "No deadline stated" if neither
• Priority: High (affects customer directly or has a hard deadline), Medium (important but flexible), Low (internal housekeeping)
• Source quote: The specific passage where the commitment was made (for CSM verification)

Step 4: Assess Sentiment

Analyse the emotional undercurrent of the conversation:

Produce an overall sentiment classification: positive / neutral / negative / mixed. Include specific evidence for the classification.

Step 5: Route Extracted Data

Structured data from the summary feeds downstream skills:

Output Format

{
  "call_id": "string",
  "account_id": "string",
  "date": "2026-03-10",
  "duration_minutes": 32,
  "source": "gong_transcript",
  "attendees": {
    "customer": [
      { "name": "Tom Chen", "role": "VP Engineering", "speaking_share": 0.45 },
      { "name": "Lisa Park", "role": "Engineering Manager", "speaking_share": 0.20 }
    ],
    "internal": [
      { "name": "Jane Doe", "role": "CSM", "speaking_share": 0.35 }
    ]
  },
  "summary": "Discussed API latency resolution and Q2 expansion plans. Tom confirmed satisfaction with support response. Lisa raised concerns about onboarding timeline for new engineering team.",
  "discussion_points": [
    {
      "topic": "API latency resolution",
      "summary": "Engineering fix deployed for ticket #4521. Currently in monitoring phase -- 7 days before declaring resolved",
      "conclusion": "Both sides satisfied with progress. Will confirm resolution next week"
    },
    {
      "topic": "Q2 engineering expansion",
      "summary": "Customer planning to onboard 15 new engineers in April. Need API documentation and training materials before they start",
      "conclusion": "CSM to provide advanced API docs by March 14. Training plan to be discussed next call"
    },
    {
      "topic": "Advanced reporting interest",
      "summary": "Tom asked about custom dashboards. Currently on Professional tier which does not include this. Expressed interest if available",
      "conclusion": "No commitment. CSM noted interest for potential expansion conversation"
    }
  ],
  "decisions": [
    "Proceed with 15-engineer expansion in April"
  ],
  "action_items": [
    {
      "action": "Send advanced API documentation to Lisa",
      "owner": "Jane Doe (CSM)",
      "deadline": "2026-03-14",
      "priority": "high",
      "source_quote": "I will get that API documentation over to you by Friday",
      "confidence": "high"
    },
    {
      "action": "Confirm API latency fix is stable after 7-day monitoring period",
      "owner": "Jane Doe (CSM)",
      "deadline": "2026-03-17",
      "priority": "medium",
      "source_quote": "We will confirm resolution after the monitoring period",
      "confidence": "high"
    },
    {
      "action": "Provide headcount plan and start dates for April engineering onboarding",
      "owner": "Tom Chen (Customer)",
      "deadline": "2026-03-21",
      "priority": "medium",
      "source_quote": "I will get you the details of who is starting and when",
      "confidence": "high"
    },
    {
      "action": "Build training plan for new engineering team",
      "owner": "TBD -- confirm",
      "deadline": "Before April onboarding",
      "priority": "medium",
      "source_quote": "Let's put together a training plan for the new team",
      "confidence": "medium -- 'let's' without a named owner"
    }
  ],
  "sentiment": {
    "overall": "positive",
    "signals": [
      { "type": "positive", "evidence": "Tom: 'Really happy with how fast your team responded on the latency issue'", "confidence": "high" },
      { "type": "positive", "evidence": "Expansion planning indicates commitment to growing with the product", "confidence": "medium" }
    ]
  },
  "flags": {
    "risk": [],
    "expansion": [
      { "signal": "15 new engineers planned for Q2", "type": "seat_growth", "confidence": "high" },
      { "signal": "Interest in Advanced Reporting (higher tier feature)", "type": "tier_upgrade", "confidence": "low -- exploratory, no commitment" }
    ],
    "competitive": [],
    "product_feedback": [
      { "topic": "Custom dashboards", "type": "feature_interest", "detail": "Asked about custom reporting dashboards. Currently not available on their tier" }
    ]
  },
  "routing": {
    "lo_sla_monitor": 4,
    "bi_expansion_detector": 2,
    "pa_feedback_aggregator": 1,
    "cc_crm_updater": 1,
    "cc_email_drafter": "follow_up_email_triggered"
  },
  "next_touchpoint": "Follow-up email today. Next call scheduled for March 24"
}

Handoff to Human

Confidence and Limitations

• High confidence for action item extraction from clear transcripts with explicit commitment language ("I will", "by Friday")
• High confidence for topic identification -- major subject transitions are detectable in transcript structure
• Medium confidence for sentiment assessment -- explicit praise and frustration are clear, but subtle signals (hedging, low energy, polite dissatisfaction) require human interpretation
• Medium confidence for implicit commitments -- "let's circle back on that" may be a real commitment, a polite deferral, or an empty phrase. The skill flags these for confirmation rather than asserting
• Low confidence for disengagement detection from transcript alone. Short answers and delegation may indicate disengagement, a busy day, or simply a reserved communication style
• Cannot extract information from sidebar conversations, body language, facial expressions, or unrecorded portions of the meeting. The most important moment in a call may happen in the 30 seconds after recording stops
• Transcript quality varies by platform, audio quality, speaker count, and accent. Poor transcripts degrade all extraction
• Multi-person calls with overlapping speakers produce lower-quality transcripts and action item attribution may be incorrect

Dependencies

Required:

• Call transcript integration (Gong, Chorus, or equivalent) OR CSM notes input

Strongly recommended:

• CRM API (for activity logging via cc-crm-updater)
• lo-sla-monitor (action item routing for commitment tracking)
• bi-risk-detector (risk signal routing)
• bi-expansion-detector (expansion signal routing)
• pa-feedback-aggregator (product feedback routing)
• bi-competitive-intel (competitive mention routing)
• cc-email-drafter (follow-up email generation)

Downstream consumers:

• lo-sla-monitor (action items)
• bi-risk-detector (risk signals)
• bi-expansion-detector (expansion signals)
• bi-competitive-intel (competitive mentions)
• pa-feedback-aggregator (product feedback)
• cc-crm-updater (activity record)
• cc-email-drafter (follow-up email content)

References

• references/extraction-patterns.md -- Signal language patterns, confidence calibration, and extraction rules