notion-meeting-intelligence

Solid

Prepare meeting materials with Notion context and Codex research; use when gathering context, drafting agendas/pre-reads, and tailoring materials to attendees.

AI & Automation 27,705 stars 2858 forks Updated today MIT

Install

View on GitHub

Quality Score: 96/100

Stars 20%
100
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Meeting Intelligence Prep meetings by pulling Notion context, tailoring agendas/pre-reads, and enriching with Codex research. ## Quick start 1) Confirm meeting goal, attendees, date/time, and decisions needed. 2) Gather context: search with `Notion:notion-search`, then fetch with `Notion:notion-fetch` (prior notes, specs, OKRs, decisions). 3) Pick the right template via `reference/template-selection-guide.md` (status, decision, planning, retro, 1:1, brainstorming). 4) Draft agenda/pre-read in Notion with `Notion:notion-create-pages`, embedding source links and owner/timeboxes. 5) Enrich with Codex research (industry insights, benchmarks, risks) and update the page with `Notion:notion-update-page` as plans change. ## Workflow ### 0) If any MCP call fails because Notion MCP is not connected, pause and set it up: 1. Add the Notion MCP: - `codex mcp add notion --url https://mcp.notion.com/mcp` 2. Enable remote MCP client: - Set `[features].rmcp_client = true` in `config.toml` **or** run `codex --enable rmcp_client` 3. Log in with OAuth: - `codex mcp login notion` After successful login, the user will have to restart codex. You should finish your answer and tell them so when they try again they can continue with Step 1. ### 1) Gather inputs - Ask for objective, desired outcomes/decisions, attendees, duration, date/time, and prior materials. - Search Notion for relevant docs, past notes, specs, and action items (`Notion:notion-search`), then fetch key pages (`Notion...

Details

Author
davila7
Repository
davila7/claude-code-templates
Created
11 months ago
Last Updated
today
Language
Python
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category