Notion Research Documentation
JetBrainsOfficialCreated by OpenAIDistributed by JetBrains
- Skill
- Content generator
- Automation and integrations
- MIT
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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 agent through searching for relevant pages, fetching content, selecting an appropriate output format, and drafting structured documents such as briefs, summaries, or reports. The workflow emphasizes accuracy by requiring inline citations and direct links back to the original source material, ensuring that all synthesized findings are verifiable and well-organized.
What it does
- Searches and retrieves relevant content across Notion workspaces.
- Synthesizes raw information into structured formats like briefs or reports.
- Provides templates for various documentation needs including comparisons and deep dives.
- Ensures traceability by linking findings to their original source pages.
- Supports the creation of actionable tasks or checklists within the generated documents.
- Includes a setup procedure for connecting the Notion MCP client.
When to use it
- When you need to consolidate information from multiple Notion pages into a single report.
- When performing research that requires verifiable citations from internal documentation.
- When creating executive summaries, competitor analyses, or technical investigations.
- When you need to present findings in a standardized, professional format.
Advantages
- Reduces manual effort in aggregating scattered information.
- Improves documentation quality through standardized templates.
- Increases transparency by maintaining clear links to source data.
- Facilitates better decision-making by organizing findings into clear, actionable insights.
Usage examples
- “Research our recent meeting notes in Notion and create a summary of all action items.”
- The agent searches for relevant meeting pages, extracts action items, and compiles them into a structured summary document with links to the original meeting notes.
- “Compare the two project proposals I have in Notion and create a comparison report.”
- The agent fetches both proposal documents, identifies key tradeoffs, and generates a comparison report using the designated template.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/jetbrains/notion-research-documentation/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip notion-research-documentation.zip -d .agents/skills
Documentation by OpenAI
Research & Documentation
Pull relevant Notion pages, synthesize findings, and publish clear briefs or reports (with citations and links to sources).
Quick start
Find sources with
Notion:notion-searchusing targeted queries; confirm scope with the user.Fetch pages via
Notion:notion-fetch; note key sections and capture citations (reference/citations.md).Choose output format (brief, summary, comparison, comprehensive report) using
reference/format-selection-guide.md.Draft in Notion with
Notion:notion-create-pagesusing the matching template (quick, summary, comparison, comprehensive).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:
Add the Notion MCP:
codex mcp add notion --url https://mcp.notion.com/mcp
Enable remote MCP client:
Set
[features].rmcp_client = trueinconfig.tomlor runcodex --enable rmcp_client
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.mdfor 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-pagewhen 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
- ATTRIBUTION.mdAdded by AutoGineer983 B
- LICENSE.txt1.0 KiB
- SKILL.md3.4 KiB
- agents/openai.yaml497 B
- assets/notion-small.svg15.4 KiB
- assets/notion.png8.3 KiB
- evaluations/README.md4.2 KiB
- evaluations/basic-research.json1.7 KiB
- evaluations/research-to-database.json1.6 KiB
- examples/competitor-analysis.md8.0 KiB
- examples/market-research.md1.9 KiB
- examples/technical-investigation.md6.4 KiB
- examples/trip-planning.md3.7 KiB
- reference/advanced-search.md4.5 KiB
- reference/citations.md5.0 KiB
- reference/comparison-format.md870 B
- reference/comparison-template.md911 B
- reference/comprehensive-report-format.md1.1 KiB
- reference/comprehensive-report-template.md1.2 KiB
- reference/format-selection-guide.md2.7 KiB
- reference/quick-brief-format.md767 B
- reference/quick-brief-template.md473 B
- reference/research-summary-format.md841 B
- reference/research-summary-template.md1.1 KiB
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
Start with general search term
Review results for relevant teamspaces/pages
Re-search with scope filters
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 pagesMulti-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 stateResult 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:
Primary sources: Direct documentation, official pages
Recent updates: Newly edited content
Related context: Supporting information
Historical reference: Background and context
Don't fetch everything - be selective based on research needs.
Handling Too Many Results
If search returns 20+ results:
Add filters: Narrow by date, creator, or teamspace
Refine query: Use more specific terms
Use page scoping: Search within relevant parent page
Sample strategically: Fetch diverse results (recent, popular, authoritative)
Handling Too Few Results
If search returns < 3 results:
Broaden query: Use more general terms
Remove filters: Search full workspace
Try synonyms: Alternative terminology
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
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
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- OpenAI
- Publisher
- JetBrains (Official)
- Distributed by
- JetBrains
- Source
- JetBrains/skills · notion-research-documentation · commit 3f53782
- Licence
- MIT License (redistribution allowed)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by OpenAI or JetBrains.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download notion-research-documentation.zip