Notion Knowledge Capture logo

Notion Knowledge Capture

Organization
beep-effect
notion-knowledge-capture

Capture conversations and decisions into structured Notion pages; use when turning chats/notes into wiki entries, how-tos, decisions, or FAQs with proper linking.

Overview

Publisherbeep-effect
Repositorybeep-effect
Skill namenotion-knowledge-capture
Stars
74
Forks
14
Bundled files
15
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 15 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by beep-effect on GitHub. Read the source before you install it.

Installation

Install the Notion Knowledge Capture AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/beep-effect/beep-effect.git /tmp/beep-effect
mkdir -p .claude/skills
cp -r /tmp/beep-effect/plugins/notion/skills/notion-knowledge-capture .claude/skills/notion-knowledge-capture
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Notion Knowledge Capture in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Notion Knowledge Capture on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Notion Knowledge Capture is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Knowledge Capture

Convert conversations and notes into structured, linkable Notion pages for easy reuse.

Quick start

  1. Clarify what to capture (decision, how-to, FAQ, learning, documentation) and target audience.
  2. Identify the right database/template in reference/ (team wiki, how-to, FAQ, decision log, learning, documentation).
  3. Pull any prior context from Notion with Notion:search → Notion:fetch (existing pages to update/link).
  4. Draft the page with Notion:notion-create-pages using the database’s schema; include summary, context, source links, and tags/owners.
  5. Link from hub pages and related records; update status/owners with Notion:notion-update-page as the source evolves.

Tool-call guardrails

  • Notion tool availability can vary by workspace. If a Notion MCP call returns Tool <name> not found, treat that tool as unavailable for the rest of the current task. Do not retry it with different arguments or call it again later; use Notion:search and Notion:fetch where sufficient.
  • Use one literal search query per Notion:search call and include filters: {} when no narrower filter is needed. If several query variants are useful, issue separate searches instead of writing or or + inside one query string.
  • Only pass Notion page, database, or data-source URLs/IDs to Notion:fetch. Search can also surface external connected-source URLs; use those as context or citations, but do not feed them into fetch.
  • Create pages with an explicit parent and a pages array. For database-backed pages, fetch the database first and use the returned collection://... data source ID.
  • To edit existing page content, fetch the current page first, then use Notion:notion-update-page with command: "update_content", properties: {}, and exact old_str / full replacement new_str pairs. For property-only edits, use command: "update_properties" with content_updates: []. The current deployed schema expects both top-level fields even when one is unused. Do not invent insertion-only commands.

Workflow

0) If Notion tools are unavailable, pause and ask the user to connect the Notion app:

  1. Enable the bundled Notion app for this plugin or session.
  2. Complete the Notion auth flow if Codex prompts for it.
  3. Restart Codex or the current session if the tools still do not appear.

After the app is connected, finish your answer and tell the user to retry so they can continue with Step 1.

1) Define the capture

  • Ask purpose, audience, freshness, and whether this is new or an update.
  • Determine content type: decision, how-to, FAQ, concept/wiki entry, learning/note, documentation page.

2) Locate destination

  • Pick the correct database using reference/*-database.md guides; confirm required properties (title, tags, owner, status, date, relations).
  • If multiple candidate databases, ask the user which to use; otherwise, create in the primary wiki/documentation DB.

3) Extract and structure

  • Extract facts, decisions, actions, and rationale from the conversation.
  • For decisions, record alternatives, rationale, and outcomes.
  • For how-tos/docs, capture steps, pre-reqs, links to assets/code, and edge cases.
  • For FAQs, phrase as Q&A with concise answers and links to deeper docs.

4) Create/update in Notion

  • Use Notion:notion-create-pages with the correct data_source_id; set properties (title, tags, owner, status, dates, relations).
  • Use templates in reference/ to structure content (section headers, checklists).
  • If updating an existing page, fetch then edit via Notion:notion-update-page.

5) Link and surface

  • Add relations/backlinks to hub pages, related specs/docs, and teams.
  • Add a short summary/changelog for future readers.
  • If follow-up tasks exist, create tasks in the relevant database and link them.

References and examples

  • reference/ — database schemas and templates (e.g., team-wiki-database.md, how-to-guide-database.md, faq-database.md, decision-log-database.md, documentation-database.md, learning-database.md, database-best-practices.md).
  • examples/ — capture patterns in practice (e.g., decision-capture.md, how-to-guide.md, conversation-to-faq.md).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Notion Knowledge Capture AI skill do?

Capture conversations and decisions into structured Notion pages; use when turning chats/notes into wiki entries, how-tos, decisions, or FAQs with proper linking.

Why use Notion Knowledge Capture on TypingMind?

Because you install it once and use it with any model. Notion Knowledge Capture is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Notion Knowledge Capture in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/beep-effect/beep-effect/tree/main/plugins/notion/skills/notion-knowledge-capture. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Notion Knowledge Capture?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Notion Knowledge Capture?

As many as you like. As long as a model supports skills, you can use Notion Knowledge Capture with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Notion Knowledge Capture AI skill free?

Yes. It is published on GitHub by beep-effect under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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