Converts physical workshop artifacts like photos and notes into professionally structured, editable Miro boards using intelligent frames and stickies.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install miro-workshop-assistant
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install miro-workshop-assistant using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Workshop to Miro Diagram?
This Openclaw Skills integration bridges the gap between physical ideation and digital documentation. It analyzes workshop outputs—whether they are photos of whiteboards or messy text notes—and synthesizes them into a logical Miro diagram. Unlike simple sticky-note importers, this skill prioritizes structural integrity by using native Miro frames as containers for categorized content, ensuring your digital workspace remains organized and readable.
By leveraging Openclaw Skills, teams can maintain a single source of truth that is easy to edit, update, and share without the manual labor of transcribing physical boards. The system enforces strict layout rules and quality gates to ensure that every sticky note is properly assigned to a frame, creating a professional architecture rather than a scattered collection of digital post-its.
Workshop to Miro Diagram Use Cases
- Digitize whiteboard sessions from physical workshops into editable Miro boards.
- Organize unstructured brainstorming notes into categorized frames and logical flows.
- Create architectural diagrams from text descriptions with smart connector routing.
- Maintain idempotent updates to existing Miro boards using stable session keys.
- Automate the transition from high-level workshop concepts to actionable digital diagrams.
How Workshop to Miro Diagram Works
- The AI analyzes the provided input photo or notes, identifying titled containers, individual notes, and relationship flows.
- A mandatory quality gate validates that titled areas are mapped to native Miro frames and at least 95% of stickies are correctly assigned to these frames.
- The skill generates a structured JSON payload containing coordinates, colors, and session metadata for idempotency.
- A local execution script uses the Miro API to apply the changes, creating frames, stickies, and elbowed connectors.
- Users can perform undo operations or iterate on the design using a stable session key, which automatically replaces the previous run to avoid duplicates.
Workshop to Miro Diagram Setup
To get started with this skill, ensure you have your Miro API credentials ready. Openclaw Skills requires specific environment variables to interact with your boards securely.
# Set required environment variables
export MIRO_ACCESS_TOKEN='your_api_token_here'
export MIRO_BOARD_ID='your_target_board_id'
# The skill utilizes a local script to push generated JSON data
node ./workshop-miro/miro-push.mjs apply ./path/to/generated-layout.json
Workshop to Miro Diagram Data Schema & Taxonomy
The skill organizes data into a comprehensive hierarchy to ensure layout precision. Every push is tracked via a session key to maintain consistency across Openclaw Skills operations.
| Component | Description |
|---|---|
| meta | Includes sessionKey (stable) and runId (unique) for idempotent updates. |
| frames | Spatial containers that define grouped areas like 'Vision' or 'Data Hub'. |
| stickies | Individual content nodes assigned to specific frameIds with color coding. |
| connectors | Defines the flow between stickies using shapes like 'elbowed' or 'curved'. |
| warnings | Array of automated alerts regarding ambiguous note placement or layout issues. |
Workshop to Miro Diagram Advanced Features
- Idempotent deduplication ensures that re-running a workshop session replaces the old version instead of creating duplicates.
- Smart layout logic automatically positions inputs on the left, processing in the center, and outputs on the right for architectural clarity.
- Anti-overlap routing creates 'router nodes' for long connections to prevent lines from crossing over unrelated stickies.
- Strict containment detection forces the AI to assign every visual element to a titled frame, preventing disorganized digital workspaces.
- Integrated undo functionality allows for quick rollbacks of specific session keys if the generated diagram needs adjustment.
SKILL.md
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