Meeting Insights

# Create a "Meeting Insights" AI Skill

I want you to help me set up a reusable AI skill that I can use in future conversations. Read the complete skill definition below, then help me install it.

## Complete Skill Definition

# Meeting Insights

Turn raw meeting transcripts into a structured set of decisions, action items, owners, due dates, open questions, and risks.

---

## Table of Contents

- [Keywords](#keywords)
- [Quick Start](#quick-start)
- [Core Workflows](#core-workflows)
- [Tools](#tools)
- [Reference Guides](#reference-guides)
- [Templates](#templates)
- [Best Practices](#best-practices)

---

## Keywords

meeting, meetings, transcript, notes, minutes, action items, decisions, decision log, follow-up, recap, sales call, customer interview, retrospective, standup, planning, async

---

## Quick Start

### Process a Transcript in 5 Minutes

1. Save your transcript text as `transcript.txt` (one speaker turn per line, format `Speaker: text`)
2. Run:
   ```bash
   python scripts/transcript_analyzer.py transcript.txt
   ```
3. Review the structured output: decisions, action items, owners, due dates, open questions
4. Drop into `assets/recap_template.md` to send a follow-up

---

## Core Workflows

### Workflow 1: Post-Meeting Recap

**Goal:** Convert a 60-minute conversation into a 90-second readable summary that everyone can act on.

**Steps:**
1. Export the transcript (Otter, Fireflies, Zoom, Google Meet, etc.)
2. Run: `python scripts/transcript_analyzer.py transcript.txt`
3. Verify owners and due dates — the analyzer is heuristic; humans correct
4. Paste structured output into `assets/recap_template.md`
5. Send within 24 hours of the meeting

**Expected Output:** Recap with decisions, action items (owner + due date), open questions, and risks.

**Time Estimate:** 5-10 minutes vs. 30+ for manual note review.

### Workflow 2: Customer Interview Synthesis

**Goal:** Pull the signals out of a discovery call without losing the customer's actual words.

**Steps:**
1. Run analyzer in JSON mode: `python scripts/transcript_analyzer.py transcript.txt --json`
2. Filter for `pains` and `quotes` — these are the discovery signals
3. Use `references/insight_extraction_patterns.md` to triangulate across multiple interviews
4. Tag findings by ICP segment for product / marketing handoff

**Expected Output:** Tagged customer pain list with verbatim quotes per insight.

**Time Estimate:** 15 minutes per interview after the call.

### Workflow 3: Decision Log Maintenance

**Goal:** Build an organizational memory so the same decision is not re-litigated quarter after quarter.

**Steps:**
1. After each meeting, run the analyzer to extract decisions
2. Append to a running decision log keyed by date and topic
3. When a future meeting raises an old topic, search the log first
4. Re-open formally rather than silently overturning

**Expected Output:** Append-only decision log searchable by topic and date.

**Time Estimate:** 2-3 minutes per meeting.

---

## Tools

### transcript_analyzer.py

Reads a transcript text file and extracts:

- **Decisions** — sentences with decision markers ("we decided", "agreed", "going with")
- **Action items** — sentences with action markers ("will", "going to", "by next week"), with heuristic owner + due date
- **Open questions** — sentences ending in "?" or marked with "open question"
- **Risks** — sentences with risk markers ("risk", "concern", "blocker", "if X then Y")
- **Quotes** — distinctive verbatim sentences > 12 words (for customer interview workflows)

```bash
# 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.
```

---

## Reference Guides

- **`references/insight_extraction_patterns.md`** — Heuristic triggers for decisions, actions, and risks; how to triangulate across interviews

---

## Templates

- **`assets/recap_template.md`** — Post-meeting recap email with placeholder sections

---

## Best Practices

- **Verify before sending.** The analyzer is heuristic; an unverified recap that mis-attributes an action item destroys trust.
- **Owner + date or it does not exist.** An action item without an owner is a hope; without a date, it is a wish.
- **Send within 24 hours.** Memory of who said what fades fast; recap latency directly correlates with action-item completion rate.
- **Quote verbatim.** For customer interviews, the customer's words matter more than your summary of them.
- **Decision log is append-only.** Never silently overturn — re-open with a dated update.

---

## Integration Points

- Pairs with `product-team/user-story/` for converting interview pains into stories
- Pairs with `project-management/` for action-item tracking
- Feeds into `marketing/` voice-of-customer workflows

---

## What I Need You to Do

First, detect which platform I'm using (Claude.ai, ChatGPT, etc.) and follow the matching instructions below.

### If I'm on Claude.ai:

Walk me through these exact steps:

1. **Create the Project:** Tell me to go to **claude.ai > Projects > Create project** and name it **"Meeting Insights"**

2. **Add Project Knowledge:** Give me the COMPLETE skill definition above as a single copyable text block inside a code fence. Tell me to click **"Add content" > "Add text content"** inside the project, then paste that entire block. Do NOT say "paste from above" -- give me the actual text to copy right there.

3. **Set Custom Instructions:** Tell me to open project settings and paste this exact instruction:
   "You are an expert Meeting Insights in the Personal Productivity domain. Use the project knowledge as your expertise. Follow the workflows, frameworks, and templates defined there. Always provide specific, actionable output."

4. **Test It:** Give me a specific sample prompt I can use inside the new project to verify it works. Pick a real task from the skill's workflows.

### If I'm on ChatGPT:

Walk me through these exact steps:

1. **Create a Custom GPT:** Tell me to go to **chatgpt.com > Explore GPTs > Create**
2. **Configure it:**
   - Name: **"Meeting Insights"**
   - Description: "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 when the user mentions meeting notes, action items, decision log, transcript analysis, or follow-up emails."
   - Instructions: Give me the COMPLETE skill definition above as a single copyable text block inside a code fence to paste into the Instructions field. Do NOT say "paste from above."
3. **Test It:** Give me a sample prompt to verify it works.

### If I'm on another platform:
Ask which tool I'm using and adapt the instructions accordingly.

## Important
- Always provide the full skill text in a ready-to-copy code block -- never tell me to "scroll up" or "copy from above"
- Keep the setup steps simple and numbered
- After setup, test it with me using a real workflow from the skill

Source: https://github.com/borghei/Claude-Skills/tree/main/personal-productivity/meeting-insights/SKILL.md