Meeting Brief

Automated daily meeting preparation system that researches meeting attendees and sends you personalized briefs.

What It Does

Every morning (configurable time):

Checks your calendar for today's meetings (via gcalcli)
Extracts attendees from each meeting
Filters out your team members (configurable)
Deep researches each external person:
- LinkedIn profile (web search)
- Company information
- GitHub profile (if engineer)
- Past interactions/notes (memory search)
- Recent news/activity
Generates AI-powered brief per person
Sends 1 email per person to your inbox

Setup

1. Configure Team Members

Edit config.json to list your team members (these will be skipped):

{
  "team_members": [
    "alice@yourcompany.com",
    "bob@yourcompany.com",
    "team@yourcompany.com"
  ],
  "team_domains": [
    "@yourcompany.com"
  ],
  "schedule": "0 7 * * *",
  "timezone": "America/Los_Angeles",
  "your_email": "you@yourcompany.com",
  "brief_from": "Meeting Brief <briefbot@yourcompany.com>",
  "slack_webhook": "https://hooks.slack.com/services/YOUR/WEBHOOK/URL",
  "send_email": true,
  "send_slack": true,
  "include_calendar_details": true,
  "research_depth": "standard"
}

Config options:

team_members: Emails to skip (exact match)
team_domains: Domain patterns to skip (e.g., skip all @yourcompany.com)
schedule: Cron expression for daily run (default: 7am)
timezone: Timezone for schedule
your_email: Where to send briefs
brief_from: From address for briefs
slack_webhook: Slack incoming webhook URL (optional)
send_email: Whether to send email briefs (default: true)
send_slack: Whether to send Slack notifications (default: false)
include_calendar_details: Include meeting time/location in brief
research_depth: quick (web only), standard (web + GitHub), deep (web + GitHub + past notes)

2. Set Up Daily Cron Job

Use OpenClaw's cron tool to schedule the daily run:

// Create cron job for daily meeting briefs
{
  name: "Meeting Brief - Daily",
  schedule: {
    kind: "cron",
    expr: "0 7 * * *",  // 7 AM daily (UTC)
    tz: "America/Los_Angeles"
  },
  payload: {
    kind: "agentTurn",
    message: "Run the meeting-brief skill for today's meetings",
    timeoutSeconds: 600
  },
  sessionTarget: "isolated"
}

Alternatively, run manually:

cd skills/meeting-brief
./scripts/run_daily.sh

How It Works

Main Workflow (`scripts/run_daily.sh`)

Fetch today's meetings (scripts/check_calendar.sh)
- Uses gcalcli to get today's agenda
- Parses meeting times, titles, attendees
- Outputs JSON with meeting details
Filter external attendees (built into run_daily.sh)
- Loads config.json
- Filters out team members and team domains
- Creates list of people to research
Research each person (scripts/research_person.js)
- Web search: LinkedIn profile, company info
- GitHub search: Profile and repos (if applicable)
- Memory search: Past interactions/notes
- News search: Recent activity
- Outputs structured research JSON
Generate brief (scripts/generate_brief.js)
- Uses OpenClaw session to generate AI brief
- Inputs: research data + meeting context
- Outputs: Two formats:
  - Email: Concise bullet-point brief
  - Slack: Rich paragraph-style story with deeper context and narrative
Send brief
- Email: Uses Gmail skill (send_email: true)
- Slack: Uses webhook (send_slack: true, scripts/send_slack.sh)
- Subject: "Meeting Brief: [Person Name] - [Meeting Title]"
- Body: AI-generated brief with research
Save to personal CRM (supernotes/people/)
- Each researched person saved as markdown file
- Includes: research data, meeting context, date
- Builds personal relationship database over time
Track sent briefs (logs to data/sent/YYYY-MM-DD.json)
- Prevents duplicates
- Enables analytics

Research Process

For each external attendee, the system researches:

Web Search (Always)

LinkedIn profile (name + company)
Company information
Recent news mentions
Professional background

GitHub (If `research_depth` is `standard` or `deep`)

GitHub profile lookup (by name/email)
Recent repos and contributions
Technical focus areas

Memory/Past Notes (If `research_depth` is `deep`)

Search MEMORY.md and daily notes
Past meeting notes
Previous interactions
Context from past conversations

Output Format

Research is structured as JSON:

{
  "person": {
    "name": "Jane Doe",
    "email": "jane@example.com",
    "company": "Example Corp",
    "title": "VP Engineering"
  },
  "linkedin": {
    "url": "...",
    "bio": "...",
    "experience": [...]
  },
  "github": {
    "username": "janedoe",
    "profile_url": "...",
    "recent_repos": [...]
  },
  "company": {
    "name": "Example Corp",
    "industry": "...",
    "recent_news": [...]
  },
  "past_interactions": [
    "Met at conference in 2024",
    "Discussed partnership opportunity"
  ]
}

Brief Generation

The AI-generated brief comes in two formats:

Email Format (Concise Bullets)

Quick Overview
- Who they are (name, title, company)
- Why you're meeting (meeting title/description)
Background
- Professional background (LinkedIn)
- Company context
- Technical expertise (GitHub, if applicable)
Conversation Starters
- Based on recent activity
- Shared interests/connections
- Relevant topics
Action Items / Notes
- Past interactions (if any)
- Things to remember
- Follow-up items

Slack Format (Rich Story)

Deeper, narrative-driven brief with:

Paragraph-style storytelling about the person
Context about their journey and recent work
Compelling hooks and conversation angles
More background color and detail
Stronger narrative flow than bullet points

Example Brief:

Subject: Meeting Brief: Jane Doe - Product Partnership Discussion

Hi,

You're meeting with Jane Doe today at 2pm.

## Quick Overview
Jane is VP of Engineering at Example Corp, a B2B SaaS company in the dev tools space. She's been there for 3 years and previously worked at GitHub and Microsoft.

## Background
- Strong background in developer tooling and infrastructure
- Recently led Example Corp's API platform overhaul (launched Q4 2025)
- Active on GitHub (janedoe) - maintains several open-source CLI tools
- Technical blog focuses on API design and developer experience

## Conversation Starters
- Their new API platform (just launched, getting good traction)
- Recent blog post on GraphQL vs REST (published last week)
- Shared interest in developer experience (noted in her LinkedIn)

## Notes
- You met briefly at DevTools Summit 2024
- She mentioned interest in partnering on integration opportunities

---
Meeting: Product Partnership Discussion
Time: Today at 2:00 PM
Location: Zoom (link in calendar)

Manual Usage

Run for a specific person:

# Research a person
node scripts/research_person.js "Jane Doe" "jane@example.com" "Example Corp"

# Generate brief
node scripts/generate_brief.js research_output.json meeting_context.json

# Send brief
./scripts/send_brief.sh brief.html "Jane Doe"

Run for today's meetings:

./scripts/run_daily.sh

Data & Logs

meeting-brief/
├── data/
│   ├── sent/              # Sent brief logs (by date)
│   │   └── 2026-02-21.json
│   ├── research/          # Research cache (by person)
│   │   └── jane-doe.json
│   └── meetings/          # Meeting data (by date)
│       └── 2026-02-21.json
└── logs/
    └── run.log            # Execution logs

Tips

Test with dry-run first: Set DRY_RUN=true in run_daily.sh to preview without sending
Adjust research depth: Start with quick, upgrade to standard or deep as needed
Refine team filter: Add domains/emails to skip internal meetings
Review briefs: Check data/sent/ logs to see what's being sent
Iterate on prompts: Edit generate_brief.js to customize AI prompt

Troubleshooting

No briefs sent:

Check gcalcli authentication (gcalcli agenda today tomorrow)
Verify calendar has events with external attendees
Check logs in logs/run.log

Briefs missing information:

Increase research_depth in config.json
Check web_search and GitHub CLI are working
Review research data in data/research/

Duplicate briefs:

Check data/sent/ for already-sent tracking
Verify cron job isn't running multiple times

Integration with OpenClaw

This skill uses:

gcalcli-calendar: For fetching today's meetings
web_search: For LinkedIn and company research
GitHub CLI (gh): For GitHub profile lookup
memory_search: For past interactions (deep mode)
gmail skill: For sending brief emails
sessions_spawn: For AI brief generation
cron: For daily scheduling

Privacy & Security

Research data is cached locally in data/research/
No external APIs (uses web_search, GitHub CLI, memory_search)
Briefs sent only to configured email
Team member filtering prevents leaking internal info
All data stored in skill directory (no cloud storage)

meeting-brief