skills.rest
YSLAB-ai
YSLAB-aiCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

scenario-lab

Drive Scenario Lab workflows via packaged CLI without loading run artifacts.

306|33|Updated Apr 20, 2026
Search Tags:#automation#cli#claude-code#packaged-runtime#scenario-lab#adapter-workflow
One-click install
npx skills add https://github.com/YSLAB-ai/scenario-lab --skill scenario-lab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scenario-lab
Source: https://github.com/YSLAB-ai/scenario-lab/tree/main/adapters/claude/scenario-lab/skills/scenario-lab
Command: npx skills add https://github.com/YSLAB-ai/scenario-lab --skill scenario-lab

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Claude Code users often need to drive the Scenario Lab workflow without loading large, full run artifacts into active context, reducing memory burden and setup friction.

Core Features & Use Cases

  • Drive the Scenario Lab workflow directly via the packaged CLI from Claude Code, avoiding hydration of heavy run artifacts.
  • Use query-style commands to control runs with deterministic behavior using the packaged runtime.
  • Suitable for adapter workflows, rapid prototyping, and testing scenarios without building complete runs.

Quick Start

From the checked-out Scenario Lab repo, create or activate a Python 3.12+ virtualenv, install the core package, and drive the workflow with the packaged runtime using scenario-lab run-adapter-action.

Frequently Asked Questions about scenario-lab

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run Scenario Lab workflows from Claude Code without loading large artifacts into memory?▼

You can drive Scenario Lab workflows directly via the packaged CLI from Claude Code, avoiding hydration of heavy run artifacts and reducing memory burden. Use query-style commands with the packaged runtime to control runs.

What adapter actions are available for deterministic experiments using the packaged runtime?▼

Adapter actions include start-run, save-intake-draft, draft-conversation-turn, and run-adapter-action, all controlled via root, run-id, revision-id, and action parameters for deterministic behavior across runs.

Do I need a specific Python environment to use Scenario Lab locally?▼

Yes, you need to check out the Scenario Lab repo, create or activate a Python 3.12+ virtualenv, install the core package, and drive the workflow using the scenario-lab run-adapter-action command.

Can I use Scenario Lab for rapid prototyping without building complete runs?▼

Yes, Scenario Lab is suitable for adapter workflows, rapid prototyping, and testing scenarios without building complete runs, applying to adapter-style interactions that require consistent outputs across runs.

How does the Scenario Lab packaged runtime handle deterministic output across multiple runs?▼

The packaged runtime uses query-style commands with controlled parameters like root, run-id, revision-id, and action to ensure deterministic behavior and consistent outputs across multiple runs.

What's the best way to control run parameters when driving adapter workflows from the terminal?▼

Use the packaged CLI to issue commands like run-adapter-action with controlled root, run-id, revision-id, and action parameters, enabling terminal-like control over the adapter workflow.

Related Skills

Explore More Software Engineering Skills→
billynewportbillynewport

Install DataSurface Python Module

Install the DataSurface Python package from a GitLab PyPI registry using pip.

Community
Intermediate
Handy369Handy369

autoagent

Plan and run AutoAgent Harbor benchmark experiments with isolated output directories.

Community
Advanced
merongmerong

cmux

Automate cmux terminal layouts, browser interactions, and notifications via its socket API.

Community
Advanced
saif27217saif27217

composio-cli

Execute Composio CLI tools, link accounts, and script workflows.

Community
Advanced