SS33 Is Building a Marketplace for the Agent Skills Generated by ReadyAI (SN33)

AI agents handle complex work, but tasks require expert capabilities that must operate together across multiple steps. Finding those capabilities becomes harder when instructions, tools, and processes are needed across the full workflow.

Skill Store 33 (SS33) is designed as a discovery and distribution layer for agent skills generated through ReadyAI (SN33). The platform groups capabilities into collections built around practical outcomes, giving builders and agents a way to find skills for complete tasks and workflows. 

What Is SS33?

SS33 (Skill Store 33) is a catalog for discovering and using AI agent skills generated through SN33. The store groups related capabilities into collections built around specific products, creative processes, and complete workflows.

Current collections include:

1. Scheduling Software as a Service (SaaS): The Clone Calendly collection combines skills for selecting a project, finding relevant capabilities, and building a scheduling application.

2. 3D Creation: The Full Blender Pipeline collection covers the major stages of 3D production, including modeling and texturing, lighting and rigging, and rendering.

3. Make a Video: The Short-form Video Factory collection organizes capabilities for turning source footage into a finished short-form video, covering sourcing and clipping, captioning, and publication.

The collection model gives each group a defined outcome and connects the capabilities needed to reach it. 

The Foundation is SN33

SS33 draws its skills from ReadyAI (SN33), which processes unstructured information into structured, machine-readable outputs.

SN33 works with conversations, webpages, documents, transcripts, and other sources to generate tags, annotations, embeddings, and metadata.

Miners compete to produce these outputs, while validators evaluate submissions against reference data and defined evaluation criteria.

For agent skills, miners produce implementations alongside (Test-Driven Development) TDD-style plans and concrete assertions describing the behavior those capabilities should deliver.

The Proof Is readyCal

readyCal provides a working example of what SN33-generated skills can produce when combined into one software development workflow.

An orchestrator described the application’s requirements before requesting the necessary capabilities through the SN33 Jobs API.

Miners generated specialist skills with test assertions, while the orchestrator assembled, tested, corrected, and deployed the resulting application.

readyCal includes timezone handling, conflict management, authentication, calendar integrations, database persistence, and production infrastructure.

Where SS33 Fits

SN33 generates the skills, while SS33 organizes those outputs so builders and agents can locate capabilities for specific tasks.

1. Discovery: Collections group related skills by intended outcome, allowing users to start with an application or workflow rather than individual functions.

2. Test Assertions: Each skill includes explicit checks describing expected behavior, giving developers and agents concrete conditions against which implementations can be tested.

3. Agent MCP: The longer-term plan includes MCP access, allowing agents to search SS33 when their current workflow requires an unavailable capability.

4. Skill Generation: When no suitable skill exists, an approved request could send that requirement back to SN33 for generation.

Together, these features connect SN33’s skill generation with a practical system for discovering, testing, and deploying agent capabilities.

From Skills to Workflows

AI agents need specialized instructions alongside capable models, particularly when completing workflows that span multiple technical or creative tasks. SS33 brings SN33-generated skills together in collections organized around those workflows, while preserving their associated test assertions.

readyCal demonstrates one application of this model, using generated skills across development, testing, correction, integration, and deployment.

As SS33 develops, its role is to make SN33-generated skills easier for builders and agents to find and use.

➛ Register Your Interest in SS33 Here.