# Commonset > Commonset gives teams one place to see what AI capabilities exist, who owns them, and which ones the organization actually trusts and uses. Commonset is an AI capability management platform for reusable AI skills, instructions, tools, workflows, and related capability artifacts across teams and AI platforms. ## Core - [Commonset](https://commonset.ai/): See what reusable AI work exists, who owns it, and which versions are approved. - [About Commonset](https://commonset.ai/about/): What Commonset is and the organizational problem it addresses. - [AI skills registry](https://commonset.ai/ai-skills-registry/): How teams can inventory, version, review, and distribute reusable AI skills. - [AI skill governance](https://commonset.ai/ai-skill-governance/): Govern AI skills across teams and AI platforms. - [How to govern AI skills](https://commonset.ai/govern-ai-skills/): A practical workflow for ownership, provenance, review, approval, distribution, and drift. - [Security and trust](https://commonset.ai/security/): Commonset security controls, trust evidence, and governance boundaries. - [Pricing](https://commonset.ai/pricing/): Commonset plans and commercial packaging. - [Privacy Policy](https://commonset.ai/privacy/): How Commonset collects, uses, retains, and protects information. - [Terms of Service](https://commonset.ai/terms/): Terms governing access to and use of Commonset websites and services. ## Resources - [Resources](https://commonset.ai/resources/): Research, guides, white papers, and practical Commonset material. - [Governing Reusable AI Capabilities](https://commonset.ai/resources/governing-reusable-ai-capabilities/): A researched framework for managing reusable AI capabilities as operational assets, with 18 references, a worked example, and a practical adoption plan. - [Do You Really Know What Your Teams Are Doing With AI?](https://commonset.ai/resources/do-you-really-know-what-your-teams-are-doing-with-ai/): Companies are asking everyone to use AI while struggling to see what their teams have built. Visibility reveals what deserves more investment, what should become a shared standard, and where accountability is missing. - [What Is an AI Skill Registry? Managing Reusable AI Skills Across Teams and Models](https://commonset.ai/resources/ai-skill-registry/): An AI skill registry connects reusable skills to their owners, sources, versions, and review history. Learn how it differs from a repository and when teams need one. - [Managing Claude Skills Across an Enterprise](https://commonset.ai/resources/managing-claude-skills-across-an-enterprise/): A practical guide to managing Claude skills across teams, from inventory and ownership to approved versions, testing, distribution, and retirement. - [What 250 Security Test Cases Taught Us About AI Agent Skill Security](https://commonset.ai/resources/ai-agent-skill-security-testing/): We tested AI agent skill security across 250 cases and compared deterministic scanning with an LLM-driven security review Skill, revealing where context, false positives, and risk composition matter most. - [Getting Started with Commonset](https://commonset.ai/resources/getting-started-with-commonset/): Learn the core Commonset workflow for adding, reviewing, approving, distributing, versioning, and understanding reusable AI capabilities. - [Creating and Publishing a Capability](https://commonset.ai/resources/creating-and-publishing-a-capability/): Learn how to create a Commonset capability, build a version, pass trust checks, request review, and publish an approved version to a supported provider. - [Reviewing and Approving Capabilities](https://commonset.ai/resources/reviewing-and-approving-capabilities/): Learn how Commonset reviews capability versions, evaluates changes and security findings, records immutable decisions, and separates approval from publication. - [Understanding Capabilities, Skills, and Commonsets](https://commonset.ai/resources/understanding-capabilities-skills-and-commonsets/): Learn the core Commonset vocabulary for capabilities, skills, versions, providers, distributions, ownership, provenance, access, and governed Commonsets. - [Versioning and Comparing Changes](https://commonset.ai/resources/versioning-and-comparing-changes/): Learn how Commonset versions capabilities, keeps approved content immutable, compares changes, and tracks local and provider state over time. - [Understanding Trust Status](https://commonset.ai/resources/understanding-trust-status/): Learn how Commonset separates lifecycle, review, security/trust, availability, and publication readiness instead of relying on one ambiguous status. - [Managing Access](https://commonset.ai/resources/managing-access/): Learn how Commonset separates approval from access, grants discover/use/review/manage permissions, and handles provider audience mismatches. - [Connecting AI Providers](https://commonset.ai/resources/connecting-ai-providers/): Learn how Commonset connects to provider surfaces, protects credentials, discovers provider capabilities, and keeps provider scope separate from Commonset governance. - [Commonset for Security and IT Teams](https://commonset.ai/resources/commonset-for-security-and-it-teams/): Security and IT need more than a list of approved AI applications. Commonset provides an organizational layer for understanding which reusable AI capabilities exist, who owns them, which versions are trusted, who can use them, and where they are distributed. - [Commonset for Developers](https://commonset.ai/resources/commonset-for-developers/): A developer guide to discovering trusted capabilities, creating versioned drafts, using Commonset MCP, running security checks, and moving changes through review. - [Why AI Capability Management Should Be Model-Agnostic](https://commonset.ai/resources/why-ai-capability-management-should-be-model-agnostic/): AI providers will continue to evolve, but the organizational capabilities built on top of them should not have to be recreated every time the underlying model, platform, or format changes. - [Governing Shadow AI Without Blocking Adoption](https://commonset.ai/resources/governing-shadow-ai-without-blocking-adoption/): If registering an AI capability makes it harder to use, employees have an incentive to keep it invisible. A better model separates visibility from approval and lets restrictions follow actual risk. - [Commonset Security Model](https://commonset.ai/resources/commonset-security-model/): Commonset's security model combines conventional application security with controls that preserve the meaning of ownership, provenance, review, approval, and distribution as AI capabilities change over time. - [AI Capabilities Are Becoming Enterprise Assets](https://commonset.ai/resources/ai-capabilities-are-becoming-enterprise-assets/): Organizations are moving from ad hoc AI conversations toward reusable capabilities that encode how work gets done. Those capabilities increasingly need ownership, versioning, governance, portability, and visibility. - [Governance Above the Model Layer](https://commonset.ai/resources/governance-above-the-model-layer/): As reusable AI capabilities spread across models, providers, teams, and workflows, governance cannot live inside any one model platform. Organizations need a durable layer for ownership, versions, provenance, policy, access, approval, and trust. ## Notes - Commonset is provider-neutral. Provider-specific skills are implementations of a broader organizational capability. - Public marketing and resource pages are intended for search and real-time AI retrieval. Commonset does not grant permission for model training through its robots.txt content signals.