Notion Research Documentation logo

Notion Research Documentation

Organization
beep-effect
notion-research-documentation

Research across Notion and synthesize into structured documentation; use when gathering info from multiple Notion sources to produce briefs, comparisons, or reports with citations.

Overview

Publisherbeep-effect
Repositorybeep-effect
Skill namenotion-research-documentation
Stars
74
Forks
14
Bundled files
20
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.

  • 20 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 Research Documentation 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-research-documentation .claude/skills/notion-research-documentation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Notion Research Documentation 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 Research Documentation 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 Research Documentation 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.

Research & Documentation

Pull relevant Notion pages, synthesize findings, and publish clear briefs or reports (with citations and links to sources).

Quick start

  1. Find sources with Notion:search using targeted queries; confirm scope with the user.
  2. Fetch pages via Notion:fetch; note key sections and capture citations (reference/citations.md).
  3. Choose output format (brief, summary, comparison, comprehensive report) using reference/format-selection-guide.md.
  4. Draft in Notion with Notion:notion-create-pages using the matching template (quick, summary, comparison, comprehensive).
  5. Link sources and add a references/citations section; update as new info arrives with Notion:notion-update-page.

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.
  • Only fetch Notion page, database, or data-source URLs/IDs. Search results can include external connected-source URLs, which are not valid Notion:fetch inputs.
  • Create output pages with an explicit parent and a pages array.
  • When updating an existing report, fetch it first and use Notion:notion-update-page with update_content, properties: {}, and search-and-replace pairs. For property-only updates, use 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) Gather sources

  • Search first (Notion:search); refine queries, and ask the user to confirm if multiple results appear.
  • Fetch relevant pages (Notion:fetch), skim for facts, metrics, claims, constraints, and dates.
  • Track each source URL/ID for later citation; prefer direct quotes for critical facts.

2) Select the format

  • Quick readout → quick brief.
  • Single-topic dive → research summary.
  • Option tradeoffs → comparison.
  • Deep dive / exec-ready → comprehensive report.
  • See reference/format-selection-guide.md for when to pick each.

3) Synthesize

  • Outline before writing; group findings by themes/questions.
  • Note evidence with source IDs; flag gaps or contradictions.
  • Keep user goal in view (decision, summary, plan, recommendation).

4) Create the doc

  • Pick the matching template in reference/ (brief, summary, comparison, comprehensive) and adapt it.
  • Create the page with Notion:notion-create-pages; include title, summary, key findings, supporting evidence, and recommendations/next steps when relevant.
  • Add citations inline and a references section; link back to source pages.

5) Finalize & handoff

  • Add highlights, risks, and open questions.
  • If the user needs follow-ups, create tasks or a checklist in the page; link any task database entries if applicable.
  • Share a short changelog or status using Notion:notion-update-page when updating.

References and examples

  • reference/ — search tactics, format selection, templates, and citation rules (e.g., advanced-search.md, format-selection-guide.md, research-summary-template.md, comparison-template.md, citations.md).
  • examples/ — end-to-end walkthroughs (e.g., competitor-analysis.md, technical-investigation.md, market-research.md, trip-planning.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 Research Documentation AI skill do?

Research across Notion and synthesize into structured documentation; use when gathering info from multiple Notion sources to produce briefs, comparisons, or reports with citations.

Why use Notion Research Documentation on TypingMind?

Because you install it once and use it with any model. Notion Research Documentation 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 Research Documentation 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-research-documentation. 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 Research Documentation?

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 Research Documentation?

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

Is the Notion Research Documentation 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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