Agent skill · Content & Marketing

meeting-brief

Daily meeting preparation system that checks your calendar each morning, deeply researches external attendees (LinkedIn, company info, GitHub, past notes), and sends you personalized briefs via email (1 per person). Use when you want automated preparation for upcoming meetings with context about each person you're meeting.

gooseworks-aigithub.com/gooseworks-aiGitHub ↗
claude-codecodexcursorships scriptsMIT
Install
npx skills add gooseworks-ai/goose-skills --skill meeting-brief --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 12
SKILL.md size: 9 KB
Bundled scripts: yes
Path: skills/sales/composites/meeting-brief/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,091
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Meeting Brief Automated daily meeting preparation system that researches meeting attendees and sends you personalized briefs. ## What It Does Every morning (configurable time): 1. Checks your calendar for today's meetings (via gcalcli) 2. Extracts attendees from each meeting 3. Filters out your team members (configurable) 4. Deep researches each external person: - LinkedIn profile (web search) - Company information - GitHub profile (if engineer) - Past interactions/notes (memory search) - Recent news/activity 5. Generates AI-powered brief per person 6. 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): ```json { "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 option

What's inside
Steps it walks through
  1. What It Does
  2. Setup
  3. 1. Configure Team Members
  4. 2. Run Daily (Manual or Scheduled)
  5. How It Works
  6. Main Workflow (scripts/rundaily.sh)
  7. Research Process
  8. Web Search (Always)
  9. GitHub (If researchdepth is standard or deep)
  10. Memory/Past Notes (If researchdepth is deep)
  11. Output Format
  12. Brief Generation
  13. Email Format (Concise Bullets)
  14. Slack Format (Rich Story)
Ships with 11 files
  • .gitignore
  • EXAMPLE.md
  • SETUP.md
  • config.json.example
  • scripts/check_calendar.sh
  • scripts/format_for_slack.sh
  • scripts/generate_brief.js
  • scripts/research_person.js
  • scripts/run_daily.sh
  • scripts/send_slack.sh
  • skill.meta.json
Commands it runs
cd skills/meeting-brief
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
More from goose-skills
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About this skill
What does the meeting-brief skill do?

Daily meeting preparation system that checks your calendar each morning, deeply researches external attendees (LinkedIn, company info, GitHub, past notes), and sends you personalized briefs via email (1 per person). Use when you want automated preparation for upcoming meetings with context about each person you're meeting.

How do I install it?

Run `npx skills add gooseworks-ai/goose-skills --skill meeting-brief --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From gooseworks-ai/goose-skills, a repository with 1,091 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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