Notion Knowledge Capture
OpenAIOfficialCreated by Notion Labs, IncDistributed by OpenAI
- Skill
- Workflow
- 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 for capturing information from ongoing conversations and turning it into structured, linkable content within Notion. It guides the user through defining the content type, identifying the appropriate database, extracting key information, and creating or updating pages using standardized templates. The workflow ensures that knowledge is not lost in chat logs but is instead integrated into a team's wiki, decision logs, or documentation systems.
What it does
- Defines the purpose and audience for captured information.
- Identifies the correct Notion database and schema for the content type.
- Extracts key facts, decisions, and rationale from conversations.
- Creates or updates structured pages using predefined templates.
- Links new content to existing hub pages and related records.
- Handles initial setup and authentication for the Notion integration.
When to use it
- When you need to turn a brainstorming session into a formal decision log.
- When converting technical discussions into a reusable how-to guide.
- When summarizing team chats into FAQ entries or wiki pages.
- When documenting learnings or project notes for future reference.
Advantages
- Ensures consistency across documentation through standardized templates.
- Reduces information fragmentation by linking new content to existing hubs.
- Provides a clear, repeatable process for knowledge management.
- Facilitates better team collaboration by making information discoverable.
Usage examples
- “Can you turn our recent discussion about the API migration into a decision log entry?”
- The agent will extract the alternatives, rationale, and final decision from the chat and create a structured page in your Notion decision log database.
- “Create a how-to guide for setting up the local environment based on our chat.”
- The agent will identify the how-to database, structure the steps and prerequisites, and create a new page in Notion with the appropriate tags and links.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/openai/notion-knowledge-capture-lh2r/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 Notion Labs, Inc
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 AutoGineer1017 B
- LICENSE.txt1.0 KiB
- SKILL.md3.2 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
examples/decision-capture.md
Example: Decision Record Capture
User Request: "Document our decision to move from REST to GraphQL API"
Workflow
1. Extract Decision from Context
From conversation, identified:
Decision: Migrate customer-facing API from REST to GraphQL
Context: REST endpoints becoming unwieldy (50+ endpoints)
Alternatives: Keep REST, try gRPC, adopt GraphQL
Rationale: Better client experience, type safety, single endpoint
2. Find Decision Log
Notion:notion-search
query: "architecture decisions" or "ADR"Found: "Architecture Decision Records" database
3. Fetch Schema
Notion:notion-fetchGot properties: Decision (title), Date, Status, Domain, Impact, Deciders, Stakeholders
4. Create Decision Record
Notion:notion-create-pages
parent: { data_source_id: "decision-log-collection-id" }
pages: [{
properties: {
"Decision": "Migrate to GraphQL API",
"date:Date:start": "2025-10-16",
"date:Date:is_datetime": 0,
"Status": "Accepted",
"Domain": "Architecture",
"Impact": "High"
},
content: "[Full decision record with context, rationale, alternatives...]"
}]Content sample:
# Migrate Customer-Facing API to GraphQL
## Context
Our REST API has grown to 50+ endpoints with inconsistent patterns. Frontend and mobile teams request new endpoints frequently, leading to:
- API bloat and maintenance burden
- Over-fetching/under-fetching data
- Slow iteration on client features
- Inconsistent error handling
## Decision
Migrate customer-facing API from REST to GraphQL while maintaining REST for internal services.
## Rationale
**Why GraphQL**:
- Clients fetch exactly what they need (no over/under-fetching)
- Single endpoint, self-documenting schema
- Type safety with code generation
- Better developer experience
- Industry standard for client-facing APIs
## Options Considered
### Option A: Keep REST (Status Quo)
**Pros**: No migration cost, team familiar
**Cons**: Doesn't solve core problems, maintenance keeps growing
**Decision**: Rejected - doesn't address root cause
### Option B: gRPC
**Pros**: Performance, strong typing
**Cons**: Browser support issues, steeper learning curve, not designed for client-facing
**Decision**: Rejected - better for internal services
### Option C: GraphQL
**Pros**: Solves over/under-fetching, great DX, strong ecosystem
**Cons**: Learning curve, caching complexity, migration effort
**Decision**: **Accepted**
## Consequences
**Positive**:
- Faster frontend/mobile development
- Reduced API maintenance burden
- Better type safety and tooling
- Single endpoint simplifies deployment
**Negative**:
- 3-4 month migration timeline
- Team needs training
- Need to solve caching strategy
- Monitoring/debugging patterns different
## Implementation Plan
1. GraphQL server setup (Apollo Server)
2. Schema design workshop
3. Gradual migration (start with new features)
4. Dual-run period (both REST and GraphQL)
5. Deprecate old REST endpoints
**Timeline**: Start Q4 2025, complete Q1 2026
**Owner**: Backend team lead
## Success Metrics
- API response times improve 30%
- Client fetch efficiency (less data transferred)
- Reduced new endpoint requests
- Developer satisfaction scores5. Make Discoverable
Added link from Architecture Wiki and notified team in Slack.
Key Success Factors
Captured decision while context fresh
Documented alternatives considered
Included both pros and cons
Clear implementation plan
Saved to decision log for future reference
Made discoverable for team
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-knowledge-capture · 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-knowledge-capture.zip