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Cloudskill
Govern and manage AI agent skill catalogs securely.
What it does
• Creates a centralized catalogue for AI agent instruction and skill files through direct authoring or file uploads. • Enforces version control and one-click rollbacks for every edit made to team AI skills and workflows. • Manages per-person access policies and permissions via a simple policy matrix across organizational roles. • Maintains a searchable, append-only compliance audit log tracking all skill changes, submissions, and approvals.
Why it works
Centralized cataloging eliminating scattered, unmanaged instruction files across team environments. Built-in human-in-the-loop review and approval workflows before changes ship. Granular access control policies ensuring users only see authorized agent skills. Comprehensive audit logging providing compliance tracking for enterprise security teams.
Category: AI & Automation
Team Size: 1
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As of 2026
AI & Automation
Revenue: 0-$100k ARR
Govern and manage AI agent skill catalogs securely.
Overview
Cloudskill is a specialized platform designed to bring order, version control, and compliance to the AI agent instruction files your team depends on. It turns scattered custom skill files for tools like Claude, Cursor, and GitHub Copilot into a centralized, managed catalogue with role-based access policies and audit logs. By introducing automated review pipelines and version histories, the platform prevents conflicting instructions and mitigates prompt-injection risks across your organization.
Funding status: Bootstrapped
Revenue source: Subscriptions
Customer type: B2B
Pricing: Freemium
Tech stack: TypeScript, React, Node.js, Cloud Infrastructure
Platform: Web
Integrations: Claude, Cursor, Codex, Gemini CLI, GitHub Copilot
Founder story
Cloudskill was founded in 2026 by Tom Palmer to address the growing chaos of unmanaged AI agent instruction files piling up across organizations. Recognizing that tools like Claude and Cursor depend heavily on scattered skill files that lack security oversight, the platform was built to treat AI skills like managed production software.
What it does
- • Creates a centralized catalogue for AI agent instruction and skill files through direct authoring or file uploads
- • Enforces version control and one-click rollbacks for every edit made to team AI skills and workflows
- • Manages per-person access policies and permissions via a simple policy matrix across organizational roles
- • Maintains a searchable, append-only compliance audit log tracking all skill changes, submissions, and approvals.
Who it's for
- AI Engineers
- DevOps Teams
- Engineering Managers
- Compliance Officers
Why it works
- Centralized cataloging eliminating scattered, unmanaged instruction files across team environments
- Built-in human-in-the-loop review and approval workflows before changes ship
- Granular access control policies ensuring users only see authorized agent skills
- Comprehensive audit logging providing compliance tracking for enterprise security teams.
Growth strategies
- Targeted launches and community engagement on platforms like Product Hunt
- Content marketing focused on AI agent security, governance, and prompt injection risks
- Direct outreach to engineering leads managing multi- developer AI tool stacks
- Open collaboration and sharing within developer- focused automation communities
Alternatives
Comparison overview
- [Cloudskill provides a dedicated management layer for versioning, access control, and auditing AI agent instruction files across multiple coding assistants , whereas traditional LLMOps platforms focus primarily on model observability, prompt playgrounds, and application deployment pipelines]