📊 Full opportunity report: The Skills Marketplace Nobody Is Building Yet on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
While an open standard and reference implementations for AI skills exist, a comprehensive marketplace with monetization, vetting, and discovery tools has not been built. This gap presents a strategic opportunity for companies to capture the future value layer of AI infrastructure.
Despite the formalization of an open standard for AI skills and multiple reference implementations, there is no dedicated marketplace for buying, selling, or vetting skills as of May 2026. This gap leaves a significant opportunity for firms to develop a scalable, secure, and monetized skills marketplace, which could become a critical layer in the AI ecosystem.
Since December 2025, the open standard for AI skills has been published at agentskills.io, with implementations adopted by Anthropic, OpenAI, and others. These skills are simple configuration files with YAML frontmatter, enabling interoperability across different AI models and runtimes. However, there is no marketplace infrastructure that supports discovery, vetting, security audits, or monetization. Existing directories such as SkillsMP, ClaudeWorld, and GitHub host community skills, but they lack formal vetting or revenue sharing mechanisms.
Major tech companies like Microsoft, Google, and Vercel are publishing skill collections, but these are primarily developer resources rather than commercial marketplaces. The current ecosystem is fragmented, with skills existing as open-source artifacts without a unified platform for distribution, trust, or monetization. The only notable gaps are in security verification, author vetting, and discoverability, which are critical for enterprise adoption.
The skills marketplace.
The directory exists. The marketplace doesn’t. Here’s the gap — and who closes it.
There are 140+ free Agent Skills on community marketplaces today. 17 official Anthropic skills under Apache 2.0. A published open standard at agentskills.io that OpenAI’s Codex CLI adopted. Microsoft, Google, Vercel publishing skill collections. And no skills equivalent of the App Store. No revenue share. No vetted-author verification. No security audit pipeline. No paid skills at all.
Folder. Frontmatter. Instructions.
A skill is a directory containing a SKILL.md file with YAML frontmatter and Markdown instructions, plus optional scripts and templates. Progressive disclosure: the agent loads only metadata into context until the skill becomes relevant. The format is simple. The implication is significant.
AI skills marketplace platform
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The directory exists. The marketplace doesn’t.
Five layers, in roughly the order they emerged. The first five are real and growing. The last five are the capture gaps — each is a real product, each is uncaptured, and any company that solves four of five wins the layer.
agentskills.io · Anthropic + OpenAI · Dec 2025
AI Express: Leading the Future of Learning
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The platform owner’s incentives do not align with the developer’s.
Same structural problem that produced the App Store / Play Store / Steam separation in mobile and gaming. The platform owner extracts rent at the marketplace layer; the developer wants to publish once and distribute everywhere. The two only align if a third party owns the marketplace.
Skills as a platform retention feature.
- Cross-surface friction is a soft retention mechanism, not a bug
- Partner directory is curated to drive distribution into their stack
- Revenue share competes with the lab’s own enterprise sales motion
- Verified-publisher status is awkward when the auditor is also the model vendor
- Skills tied to one model = same problem the standard was built to solve
Three fronts the labs cannot credibly compete on.
- Cross-surface neutrality — “publish once, run on any model”
- Verified-publisher status as a paid security service
- 70/30 revenue share creates incentives for vertical specialists
- Trust calculation is cleaner: auditor ≠ model vendor
- Wins by being the only neutral broker between labs and enterprise
AI-Powered Software Audits: Revolutionizing Audit, Compliance, Risk, Security, and Governance for Organizations: Harnessing AI to Automate Compliance, and Strengthen Governance in the Digital era
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Smaller than you assumed. Closer than you think.
~20 engineers · $30–50M Series A · founded 2026 H2 / 2027 H1. Reference: Replicate’s positioning in model hosting — neutral, multi-vendor, developer-first. The challenge is distribution.
GitHub (= Microsoft, conflict). Cursor. Replit. Linear. The most legible path is “GitHub Skills” — but Microsoft competes at the model layer, reproducing the original problem.
Harvey in legal · a healthcare-AI company yet to emerge · Bloomberg in finance. Slower path, structurally stronger trust position. Customer never has to ask “is this skill safe?”
AI developer skill directory
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The 2026 H2 author looks like the 2007 YouTube creator.
Write the skills now. Capture when the marketplace ships.
The capture mechanism does not yet exist. Skills you write today have no way to charge for themselves. This is a feature, not a bug, for the next 12 months. Write skills, accumulate authorship reputation, build a portfolio that becomes legible the moment a marketplace with revenue share goes live.
The directory exists. The marketplace doesn’t. Whoever builds it captures the most defensible position in the post-model AI stack.
Four assignments. By role.
Start writing skills now.
The marketplace doesn’t exist yet but the reputation system runs on what you publish in 2026. The early-mover advantage when the marketplace ships is real. GitHub stars compound into discoverable authorship.
The window is open. Funding is favorable through Q3.
The standard is set, the demand is forming, the labs won’t build it themselves, and the second-mover penalty in marketplaces is severe. The “App Store of agents” thesis is investable today.
Demand a skill governance roadmap.
If your AI vendor’s answer is “we trust Anthropic to vet skills,” the answer is incomplete. Demand SIEM integration, audit logging, enterprise approval workflows. Current admin controls are a starting line.
The position is winnable in 2026 H2.
Natural fits: GitHub, Cursor, Replit. If you build developer tooling but aren’t one of those, you have 12 months to figure out whether your product becomes a skills publishing channel — or watches the value flow past it.
Why a Skills Marketplace Is a Strategic Missing Layer
The absence of a dedicated skills marketplace limits the commercialization and scaling of AI skills, hindering broader enterprise adoption and ecosystem growth. Building such a marketplace would enable secure, vetted, and monetized skill exchanges, positioning the responsible company to capture significant value in the AI infrastructure stack. As the ecosystem matures, the lack of a marketplace leaves a gap that smaller firms are well-positioned to fill, potentially shaping the future of AI deployment and monetization.Open Standards and Ecosystem Development Since 2025
The formal open standard for AI skills was published in December 2025, establishing a common format (SKILL.md) and enabling interoperability across multiple AI platforms. Major AI providers like Anthropic and OpenAI have integrated these standards into their products, but the marketplace layer—where users can discover, vet, and monetize skills—remains undeveloped. Existing directories serve as discovery tools but lack monetization, vetting, or security pipelines, which are essential for enterprise use and scaling.
Historically, AI ecosystems have relied on proprietary models and closed marketplaces, but the emergence of open standards suggests a shift toward more open, portable, and user-controlled artifacts. Still, without a marketplace infrastructure, the full potential of these standards remains unrealized, and the ecosystem risks fragmentation and reduced trust among enterprise users.
“The marketplace layer does not exist yet, and that’s where the real value will be captured in the post-model-commoditization AI stack.”
— Thorsten Meyer
Unclear Timing and Adoption of a Skills Marketplace
It is not yet clear when a comprehensive, secure, and monetized skills marketplace will be built or widely adopted. While smaller companies and open-source communities are active, major platform players have not yet committed to launching such a marketplace, and enterprise trust and security standards are still evolving.Next Steps for Ecosystem Maturation and Market Development
Over the next 9 to 18 months, smaller firms and open-source projects are expected to experiment with marketplace prototypes that incorporate vetting, security, and monetization features. Larger AI platform providers may eventually formalize and launch their own marketplaces, driven by enterprise demand and the need for secure distribution channels. The development of standards for security, author verification, and discoverability will be critical in shaping the future landscape.
Key Questions
Why is there no existing marketplace for AI skills yet?
While standards and reference implementations exist, the infrastructure for discovery, vetting, security, and monetization has not been developed at scale. Building a trusted, secure marketplace requires addressing technical, security, and trust challenges that are still being worked out.
Who stands to benefit most from a skills marketplace?
Small and medium-sized AI firms, enterprise clients seeking vetted skills, and platform providers who can capture value through discovery and monetization are most positioned to benefit once such a marketplace is established.
What are the main technical challenges in building this marketplace?
Key challenges include establishing security and vetting pipelines, author verification, discoverability algorithms, and cross-surface portability, all while maintaining trust and enabling monetization.
When might we see a fully operational skills marketplace?
Industry estimates suggest a window of roughly 9 to 18 months for initial prototypes and pilot platforms, with broader adoption depending on enterprise trust and standardization progress.
Source: ThorstenMeyerAI.com
