What version of the Looplia schema does this skill support?

The skill generates workflows following the v0.7.0 architecture, featuring selective plugin loading, while maintaining support for v0.6.x features like input-less steps.

How are user preferences incorporated into the workflow?

It parses 'User clarifications' from enriched prompts and injects specific constraints regarding platforms, counts, and formats directly into the relevant step missions.

Does it support workflows that start without an input file?

Yes, it detects input-less capable skills (like browser-research) and configures the first step to operate autonomously without an 'input' field.

How does it handle data passing between different workflow steps?

It automatically maps output paths to the sandbox and uses the 'needs' field to resolve dependencies, allowing subsequent steps to reference data from previous ones.

Can I define custom names for my generated workflows?

Yes, if the --name flag is provided during the build process, the skill will use that exact string for both the filename and the internal workflow metadata.

Workflow Schema Composer

Name: Workflow Schema Composer
Author: memorysaver

bymemorysaver

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생산성 및 워크플로

Generates valid, production-ready Looplia agentic workflow definitions from skill recommendations and user requirements.

소개

The Workflow Schema Composer is a specialized skill for the Looplia CLI that automates the generation of complex agentic workflow files. It transforms abstract skill recommendations and user preferences into structured Markdown files with YAML frontmatter, strictly adhering to the latest v0.7.0 schema. By intelligently handling dependency resolution, input/output data flows, and selective plugin loading, it ensures that your AI automation pipelines are correctly configured and ready for immediate execution without manual syntax debugging.

주요 기능

Injects interactive user preferences directly into step-specific missions for tailored results.
Generates v0.7.0 compliant workflow schema with explicit skill declarations for optimized loading.
Supports autonomous, input-less workflow steps for skills like web search and data fetching.
Generates built-in validation rules to ensure required data fields are present across step transitions.
11 GitHub stars
Automatically resolves data flow dependencies and ensures proper topological step ordering.

사용 사례

Converting a conceptual automation prompt into a runnable .md workflow file.
Creating autonomous research workflows that execute without requiring an initial input file.
Building multi-step AI pipelines that require data passing between specialized agentic skills.

소개

주요 기능

Injects interactive user preferences directly into step-specific missions for tailored results.
Generates v0.7.0 compliant workflow schema with explicit skill declarations for optimized loading.
Supports autonomous, input-less workflow steps for skills like web search and data fetching.
Generates built-in validation rules to ensure required data fields are present across step transitions.
11 GitHub stars
Automatically resolves data flow dependencies and ensures proper topological step ordering.

사용 사례

Converting a conceptual automation prompt into a runnable .md workflow file.
Creating autonomous research workflows that execute without requiring an initial input file.
Building multi-step AI pipelines that require data passing between specialized agentic skills.