Agent skill

notion-meeting-intelligence

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

Stars 19
Forks 4

Install this agent skill to your Project

npx add-skill https://github.com/x-cmd/skill/tree/main/data/openai/.curated/notion-meeting-intelligence

Metadata

Additional technical details for this skill

short description
Prep meetings with Notion context and tailored agendas

SKILL.md

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:notion-fetch).
  • Capture blockers/risks and open questions up front.

2) Choose format

  • Status/update → status template.
  • Decision/approval → decision template.
  • Planning (sprint/project) → planning template.
  • Retro/feedback → retrospective template.
  • 1:1 → one-on-one template.
  • Ideation → brainstorming template.
  • Use reference/template-selection-guide.md to confirm.

3) Build the agenda/pre-read

  • Start from the chosen template in reference/ and adapt sections (context, goals, agenda, owner/time per item, decisions, risks, prep asks).
  • Include links to pulled Notion pages and any required pre-reading.
  • Assign owners for each agenda item; call out timeboxes and expected outputs.

4) Enrich with research

  • Add concise Codex research where helpful: market/industry facts, benchmarks, risks, best practices.
  • Keep claims cited with source links; separate fact from opinion.

5) Finalize and share

  • Add next steps and owners for follow-ups.
  • If tasks arise, create/link tasks in the relevant Notion database.
  • Update the page via Notion:notion-update-page when details change; keep a brief changelog if multiple edits.

References and examples

  • reference/ — template picker and meeting templates (e.g., template-selection-guide.md, status-update-template.md, decision-meeting-template.md, sprint-planning-template.md, one-on-one-template.md, retrospective-template.md, brainstorming-template.md).
  • examples/ — end-to-end meeting preps (e.g., executive-review.md, project-decision.md, sprint-planning.md, customer-meeting.md).

Expand your agent's capabilities with these related and highly-rated skills.

x-cmd/skill

pufferlib

High-performance reinforcement learning framework optimized for speed and scale. Use when you need fast parallel training, vectorized environments, multi-agent systems, or integration with game environments (Atari, Procgen, NetHack). Achieves 2-10x speedups over standard implementations. For quick prototyping or standard algorithm implementations with extensive documentation, use stable-baselines3 instead.

19 4
Explore
x-cmd/skill

fluidsim

Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.

19 4
Explore
x-cmd/skill

metabolomics-workbench-database

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.

19 4
Explore
x-cmd/skill

geniml

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

19 4
Explore
x-cmd/skill

zinc-database

Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.

19 4
Explore
x-cmd/skill

astropy

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

19 4
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results