async-io-model
Cooperative async patterns using explicit state machines, completions, and re-entrancy safeguards for Turso's I/O model.
Works with
What it does
Core types: IOResult<T> (returns Done or IO requiring re-call) and Completion for tracking individual operations
CompletionGroup aggregates multiple completions into one, with nesting and cancellation support
State machine pattern encodes progress in enum variants to safely handle re-entry across yield points
Critical pitfall: mutating shared state before y
Installation Guide
How to use async-io-model on Cursor
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Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
async-io-model
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches async-io-model from tursodatabase/turso and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate async-io-model. Access via /async-io-model in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
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Use Cases
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Research competitors, compare features, identify gaps
Example
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Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale