Notion Knowledge Capture
JetBrainsOfficialCreated by OpenAIDistributed by JetBrains
- Skill
- Tool integration
- Automation and integrations
- MIT
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a systematic approach to transforming ephemeral chat logs and notes into durable, structured knowledge within Notion. It guides the user through defining the content type, identifying the appropriate database, extracting key information, and creating or updating pages with proper metadata and cross-linking. By leveraging predefined templates and database schemas, it ensures that team wikis, decision logs, and how-to guides remain consistent and discoverable.
What it does
- Converts unstructured conversation data into structured Notion pages.
- Supports multiple content types including decisions, FAQs, how-tos, and wiki entries.
- Facilitates the creation and updating of Notion pages using specific database schemas.
- Ensures proper linking and relationship management between new and existing documentation.
- Provides a clear setup procedure for Notion integration via MCP.
When to use it
- When you need to document a decision made during a team chat.
- When converting a series of troubleshooting steps into a formal how-to guide.
- When building a team wiki from recurring questions or project notes.
- When you need to update existing documentation with new context or status changes.
Advantages
- Reduces knowledge loss by formalizing informal discussions.
- Maintains consistency across documentation using standardized templates.
- Improves discoverability through structured tagging and relational linking.
- Integrates directly with Notion databases for seamless knowledge management.
Usage examples
- “Capture our recent decision about the API migration into the decision log.”
- The agent will extract the rationale and outcome from the chat, locate the decision log database, and create a structured page with the appropriate properties.
- “Turn this troubleshooting conversation into a how-to guide for the team wiki.”
- The agent will structure the steps, prerequisites, and edge cases into a template-based how-to page and link it to relevant project documentation.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/jetbrains/notion-knowledge-capture/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip notion-knowledge-capture.zip -d .agents/skills
Documentation by OpenAI
Knowledge Capture
Convert conversations and notes into structured, linkable Notion pages for easy reuse.
Quick start
Clarify what to capture (decision, how-to, FAQ, learning, documentation) and target audience.
Identify the right database/template in
reference/(team wiki, how-to, FAQ, decision log, learning, documentation).Pull any prior context from Notion with
Notion:notion-search→Notion:notion-fetch(existing pages to update/link).Draft the page with
Notion:notion-create-pagesusing the database’s schema; include summary, context, source links, and tags/owners.Link from hub pages and related records; update status/owners with
Notion:notion-update-pageas the source evolves.
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) 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.mdguides; 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-pageswith the correctdata_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).
Files
- ATTRIBUTION.mdAdded by AutoGineer958 B
- LICENSE.txt1.0 KiB
- SKILL.md3.3 KiB
- agents/openai.yaml512 B
- assets/notion-small.svg15.4 KiB
- assets/notion.png8.3 KiB
- evaluations/README.md3.4 KiB
- evaluations/conversation-to-wiki.json2.0 KiB
- evaluations/decision-record.json2.2 KiB
- examples/conversation-to-faq.md15.9 KiB
- examples/decision-capture.md3.5 KiB
- examples/how-to-guide.md2.8 KiB
- reference/database-best-practices.md2.8 KiB
- reference/decision-log-database.md2.0 KiB
- reference/documentation-database.md2.7 KiB
- reference/faq-database.md2.0 KiB
- reference/how-to-guide-database.md1.2 KiB
- reference/learning-database.md1.3 KiB
- reference/team-wiki-database.md927 B
reference/learning-database.md
Learning/Post-Mortem Database
Purpose: Capture learnings from incidents, projects, or experiences.
Schema
| Property | Type | Options | Purpose |
|---|---|---|---|
| Title | title | - | Event or project name |
| Date | date | - | When it happened |
| Type | select | Incident, Project, Experiment, Retrospective | Learning type |
| Severity | select | Critical, Major, Minor | Impact level (for incidents) |
| Team | people | - | Who was involved |
| Key Learnings | number | - | Count of learnings |
| Action Items | relation | Links to tasks | Follow-up actions |
Content Template
Each learning page should include:
What Happened: Situation description
What Went Well: Success factors
What Didn't Go Well: Problems encountered
Root Causes: Why things happened
Learnings: Key takeaways
Action Items: Improvements to implement
Best Practices
Blameless approach: Focus on systems and processes, not individuals
Document quickly: Capture while memory is fresh
Identify root causes: Go beyond surface-level problems
Create action items: Turn learnings into improvements
Follow up: Track that action items are completed
Share widely: Make learnings accessible to entire team
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
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Attribution and licence
- Created by
- OpenAI
- Publisher
- JetBrains (Official)
- Distributed by
- JetBrains
- Source
- JetBrains/skills · notion-knowledge-capture · 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-knowledge-capture.zip