stephenrogan

call-summary-generator

0
0
# Install this skill:
npx skills add stephenrogan/csm-skills --skill "call-summary-generator"

Install specific skill from multi-skill repository

# Description

Generates a structured post-call summary from raw notes, key observations, or a brain dump of what happened. Organises the chaos into discussion points, decisions, action items, sentiment, and flags. Use when asked to summarise a call, structure meeting notes, organise what happened in a conversation, create a call summary from notes, or when a CSM has raw thoughts from a customer call and needs them structured. Also triggers for questions about call documentation, meeting summarisation, note organisation, or turning a call brain dump into a usable record.

# SKILL.md


name: call-summary-generator
description: Generates a structured post-call summary from raw notes, key observations, or a brain dump of what happened. Organises the chaos into discussion points, decisions, action items, sentiment, and flags. Use when asked to summarise a call, structure meeting notes, organise what happened in a conversation, create a call summary from notes, or when a CSM has raw thoughts from a customer call and needs them structured. Also triggers for questions about call documentation, meeting summarisation, note organisation, or turning a call brain dump into a usable record.
license: MIT
metadata:
author: Stephen Rogan
version: "1.0.0"
standalone: true


Call Summary Generator

Takes your raw, unstructured post-call notes and turns them into a structured summary. The input can be messy -- bullet points, fragments, stream-of-consciousness. The output is clean and actionable.

Different from the follow-up email (customer-facing) and the meeting outcome log (CRM-facing) -- this is the comprehensive record for your own reference and your team's context.

How to Use

After a call, provide:
- Your raw notes (however messy -- the skill structures them)
- Who was on the call (customer and internal)
- Call duration and type
- Anything you want to highlight or flag

What It Produces

Discussion Points (What Was Covered)

Organises the conversation into distinct topics, each with:
- Topic name
- What was discussed (2-3 sentences)
- Conclusion or outcome (if any)
- Open questions (if the topic was not resolved)

Decisions (What Was Agreed)

Explicit agreements from the call:
- What was decided
- Who decided (consensus, or one person's call)
- Any conditions or caveats

Action Items (Who Committed to What)

Extracted from the notes using the same patterns as the action-item-extractor:

Action Owner Deadline Confidence
[action] [name] [date] [High: explicit commitment / Medium: implied / Low: vague offer]

Sentiment Assessment

Based on your notes and observations:
- Overall: positive / neutral / negative / mixed
- Specific signals: what you noticed about the customer's energy, engagement, specific statements
- Shift: did the sentiment change during the call? (Started positive, turned negative during the pricing discussion)

Flags

Signals that should trigger downstream attention:
- Risk flags: Frustration expressed, competitive mention, budget concern, disengagement signals
- Expansion flags: Growth interest, new team mentions, feature requests indicating deeper adoption
- Product flags: Feature requests, bug reports, integration needs
- Relationship flags: Champion sentiment change, new stakeholder identified, political observation

Output Format

## Call Summary: [Account Name]
**Date:** [date] | **Type:** [type] | **Duration:** [minutes]
**Attendees:** [customer contacts] | [internal team]

### Discussion Points
1. **[Topic]**: [2-3 sentence summary]. Conclusion: [outcome or "open"]
2. **[Topic]**: [2-3 sentence summary]. Conclusion: [outcome or "open"]

### Decisions
- [Decision 1]
- [Decision 2]

### Action Items
| Action | Owner | Deadline | Confidence |
|--------|-------|----------|-----------|
| [action] | [name] | [date] | [H/M/L] |

### Sentiment
Overall: [assessment]
Signals: [specific observations]

### Flags
- [Risk/Expansion/Product/Relationship]: [detail]

### Next Touchpoint
[When and what]

Handling Messy Input

The skill works with various input quality levels:

Input Quality What You Provide What the Skill Does
Detailed notes Structured bullet points with quotes and observations Organises into the template with minimal inference
Rough notes Fragments, shorthand, incomplete sentences Interprets and structures. Flags anything unclear for your review
Brain dump Stream-of-consciousness paragraph about what happened Extracts topics, actions, and sentiment. Asks for clarification on ambiguities
Minimal notes "Discussed renewal, they are happy, Tom will send the data" Produces a minimal summary. Flags: "Notes are sparse -- review for completeness before finalising"

Quality Gates

  • Are all action items extracted? Scan the raw notes for commitment language ("I will," "we will," "let's") and confirm each one appears in the action item table
  • Is the sentiment assessment honest? "Positive" because no one complained is not the same as "positive" because the customer expressed enthusiasm. Label the evidence
  • Are flags captured? A competitive mention buried in paragraph 3 of your notes should appear as a flag in the summary, not disappear into the narrative
  • Could someone who was not on the call understand the summary? That is the bar. Your manager, your successor, your colleague covering your accounts while you are on leave -- they should be able to read this and know what happened

Principles

  • Write the summary within 1 hour. The quality of your recall degrades exponentially. Notes written the same day are 3x more accurate than notes written the next day
  • The summary is a thinking tool, not just a documentation tool. The act of structuring your notes forces you to process what happened: what was the most important topic? What did the customer really mean? What did I commit to? The structure creates clarity that raw notes do not
  • Err on the side of capturing too much. You can always trim a comprehensive summary. You cannot reconstruct a missing observation 2 weeks later. When in doubt, include it
  • The flags section is the highest-value part for downstream use. The discussion points are for you. The flags are for the system -- they trigger risk reviews, expansion conversations, and product feedback loops

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.