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Notion Research Documentation

OpenAIOfficialCreated by Notion Labs, IncDistributed by OpenAI

  • Skill
  • Content generator
  • Automation and integrations
  • MIT
  • No issues found

From the author

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

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a systematic approach to gathering, analyzing, and documenting information stored within Notion. It guides the user through searching for relevant pages, extracting key facts and metrics, and synthesizing findings into structured formats such as quick briefs, comparisons, or comprehensive reports. The workflow includes specific steps for citation management and creating final documents directly within Notion, ensuring that all synthesized content remains linked to its original source material.

What it does

  • Searches and fetches content from multiple Notion pages.
  • Synthesizes research findings into structured document formats.
  • Provides templates for briefs, summaries, comparisons, and reports.
  • Manages citations and links back to original source pages.
  • Supports updating existing Notion pages with new research or status changes.
  • Includes a setup procedure for connecting the Notion MCP.

When to use it

  • When you need to aggregate information from various Notion pages into a single report.
  • When performing competitor analysis or technical investigations stored in Notion.
  • When you need to compare options or features documented across different project pages.
  • When creating executive-ready summaries or briefs from raw research notes.

Advantages

  • Ensures consistent documentation structure across different research tasks.
  • Maintains traceability by linking findings to original source pages.
  • Reduces manual effort in formatting and organizing research data.
  • Facilitates collaborative review by keeping synthesized reports within Notion.

Usage examples

“Research our recent project meeting notes in Notion and create a summary of the key decisions made.”
The agent searches for relevant meeting pages, extracts decision points, and creates a new summary page in Notion with citations.
“Compare the two product feature proposals I have saved in Notion and draft a comparison report.”
The agent fetches both proposals, identifies key tradeoffs, and generates a structured comparison document in Notion.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/openai/notion-research-documentation-lzcb/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip notion-research-documentation.zip -d .agents/skills

Documentation by Notion Labs, Inc

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:notion-search using targeted queries; confirm scope with the user.

  2. Fetch pages via Notion: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.

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 sources
  • Search first (Notion:notion-search); refine queries, and ask the user to confirm if multiple results appear.

  • Fetch relevant pages (Notion: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).

Files

reference/advanced-search.md

Advanced Search Techniques

Search Filtering

By Date Range

Use created_date_range to find recent content:

filters: {
  created_date_range: {
    start_date: "2024-01-01",
    end_date: "2025-01-01"
  }
}

When to use:

  • Finding recent updates on a topic

  • Focusing on current information

  • Excluding outdated content

By Creator

Use created_by_user_ids to find content from specific people:

filters: {
  created_by_user_ids: ["user-id-1", "user-id-2"]
}

When to use:

  • Research from subject matter experts

  • Team-specific information

  • Attribution tracking

Combined Filters

Stack filters for precision:

filters: {
  created_date_range: {
    start_date: "2024-10-01"
  },
  created_by_user_ids: ["expert-user-id"]
}

Scoped Searches

Teamspace Scoping

Restrict search to specific teamspace:

teamspace_id: "teamspace-uuid"

When to use:

  • Project-specific research

  • Department-focused information

  • Reducing noise from irrelevant results

Page Scoping

Search within a specific page and its subpages:

page_url: "https://notion.so/workspace/Page-Title-uuid"

When to use:

  • Research within a project hierarchy

  • Documentation updates

  • Focused investigation

Database Scoping

Search within a database's content:

data_source_url: "collection://data-source-uuid"

When to use:

  • Task/project database research

  • Structured data investigation

  • Finding specific entries

Search Strategies

Broad to Narrow
  1. Start with general search term

  2. Review results for relevant teamspaces/pages

  3. Re-search with scope filters

  4. Fetch detailed content from top results

Example:

Search 1: query="API integration" → 50 results across workspace
Search 2: query="API integration", teamspace_id="engineering" → 12 results
Fetch: Top 3-5 most relevant pages
Multi-Query Approach

Run parallel searches with related terms:

Query 1: "API integration"
Query 2: "API authentication"
Query 3: "API documentation"

Combine results to build comprehensive picture.

Temporal Research

Search across time periods to track evolution:

Search 1: created_date_range 2023 → Historical context
Search 2: created_date_range 2024 → Recent developments
Search 3: created_date_range 2025 → Current state

Result Processing

Identifying Relevant Results

Look for:

  • High semantic match: Result summary closely matches query intent

  • Recent updates: Last-edited date is recent

  • Authoritative sources: Created by known experts or in official locations

  • Comprehensive content: Result summary suggests detailed information

Prioritizing Fetches

Fetch pages in order of relevance:

  1. Primary sources: Direct documentation, official pages

  2. Recent updates: Newly edited content

  3. Related context: Supporting information

  4. Historical reference: Background and context

Don't fetch everything - be selective based on research needs.

Handling Too Many Results

If search returns 20+ results:

  1. Add filters: Narrow by date, creator, or teamspace

  2. Refine query: Use more specific terms

  3. Use page scoping: Search within relevant parent page

  4. Sample strategically: Fetch diverse results (recent, popular, authoritative)

Handling Too Few Results

If search returns < 3 results:

  1. Broaden query: Use more general terms

  2. Remove filters: Search full workspace

  3. Try synonyms: Alternative terminology

  4. Search in related areas: Adjacent teamspaces or pages

Search Quality

Effective Search Queries

Good queries (specific, semantic):

  • "Q4 product roadmap"

  • "authentication implementation guide"

  • "customer feedback themes"

Weak queries (too vague):

  • "roadmap"

  • "guide"

  • "feedback"

Over-specific queries (too narrow):

  • "Q4 2024 product roadmap for mobile app version 3.2 feature X"

User Context

Always use available user context:

  • Query should match their terminology

  • Scope to their relevant teamspaces

  • Consider their role/department

  • Reference their recent pages

Connected Sources

Notion Integrations

Search extends beyond Notion pages to:

  • Slack messages (if connected)

  • Google Drive documents (if connected)

  • GitHub issues/PRs (if connected)

  • Jira tickets (if connected)

Be aware results may come from these sources.

Source Attribution

When citing results from connected sources:

  • Note the source type in documentation

  • Use appropriate mention format

  • Verify user has access to the source system

Requirements and compatibility

Written for: OpenAI Codex

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

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Attribution and licence

Created by
Notion Labs, Inc
Publisher
OpenAI (Official)
Distributed by
OpenAI
Source
openai/skills · skills/.curated/notion-research-documentation · commit 49f948f
Licence
MIT License (redistribution allowed)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Notion Labs, Inc or OpenAI.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download notion-research-documentation.zip