Interactive tutorial that teaches Ouroboros through hands-on experience.
ooo tutorial
/ouroboros:tutorial
details; non-technical users get the interview and plain language.
specification, then ask what they want to build. If they have no idea, use a
task-management CLI as the example.
solves, the main users, the one feature that makes it useful now). Point out
that each answer surfaced an assumption they had not stated.
```
Goal:
Constraints: <2-3 constraints they named>
Acceptance criteria: <2-3 checkable outcomes>
```
Do not invent an ambiguity score. Explain that ooo interview measures
ambiguity and continues until it is low enough to freeze a real Seed.
Interview → Seed → Execute → Evaluate, with evaluationfeeding back into the next Seed generation:
```
ooo interview "your idea" # expose assumptions
ooo seed # freeze the Seed
ooo run # execute it
ooo evaluate # verify against the acceptance criteria
ooo status # check drift
```
ooo unstuck helps when blocked. run, evaluate, evolve, and status
need the Ouroboros MCP server (ooo setup).
project idea"), the full reference (ooo help), or setup (ooo setup`).
If the user asks how this differs from prompting an AI assistant directly:
without a spec, the assistant guesses and you rewrite the prompt until it
matches; with Ouroboros, the interview exposes hidden assumptions first, so the
build starts from an agreed Seed. If it seems complicated, three commands cover
most use: ooo interview, ooo seed, ooo run.
The tutorial is done when the user has experienced the interview, understands
what a Seed is, and has chosen a next step.
End the final response with exactly one line ◆ <current state> → next: <recommended action>. Derive the state from live session state via ouroboros_session_status when available, otherwise from this skill's actual outcome. Never use a linear Step N of M footer; when the next step is a real choice, list 2-3 options.