stateful user story logic compiler
by nowrich
Converts complex user stories into structured state machine logic with events, guards, and invariants.
Free
Works with the AI tools you already use
See it in action
You say
A user adds items to a cart. Once they click checkout, the cart is locked. If payment succeeds, it becomes an order. If it fails, the cart unlocks for editing.
Your agent does
{ "states": ["editing", "locked", "order"], "events": ["checkout_click", "payment_success", "payment_fail"], "transitions": [ {"from": "editing", "event": "checkout_click", "to": "locked"}, {"from": "locked", "event": "payment_success", "to": "order"} ] }
About this skill
The problem
Vague user stories lead to edge-case bugs and broken state management during implementation. Developers often struggle to translate messy requirements into precise, bug-free business logic for state machines.
What it does
- Identifies implicit and explicit states from plain-text user stories.
- Extracts triggers, conditional guards, and valid transition paths.
- Defines invariants to enforce global constraints and prevent illegal states.
- Generates proof traces to validate logic consistency before writing code.
- Outputs structured JSON or YAML for integration into workflow engines.
Why this beats prompting it yourself
Writing state logic manually often misses hidden transitions or conflicting guards. This skill applies a formal structure that ensures every path is accounted for and every constraint is enforced, providing a machine-readable blueprint that is ready for implementation.
Use cases
- Designing finite state machine (FSM) configurations.
- Specifying event-driven architecture workflows.
- Modeling complex business processes for compliance and audit trails.
- Generating test suites based on formal proof traces.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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