📊 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 several reference implementations for AI skills exist, a dedicated, monetized marketplace has not been built. This gap presents a strategic opportunity for companies to define the future AI ecosystem.
Despite the existence of an open standard and several reference implementations for AI skills, a dedicated marketplace for hosting, discovering, and monetizing these skills has not yet been built, creating a significant gap in the AI ecosystem.
In May 2026, over 140 free AI agent skills are available across community directories, with official skills published by companies like Anthropic, Microsoft, Google, and Vercel. An open standard for skills, defined at agentskills.io, has been adopted by major AI platforms, enabling interoperability and portability of skills across different models and runtimes.
However, despite these technical foundations, there is no dedicated marketplace akin to an app store for AI skills. Current discovery relies on GitHub stars and word of mouth, with no revenue-sharing, vetting, or security audit pipeline beyond source trust. Skills are all free, and cross-surface portability remains limited, as skills uploaded to one platform are not available on others.
This gap means that companies and developers lack a centralized, secure, and monetized platform to showcase, verify, and sell skills, which could hinder the growth of a vibrant AI ecosystem and slow innovation and 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
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
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
Unpacking AI – Why Artificial Intelligence Matters: Your Practical Introduction and Roadmap to Leveraging AI Ethically in Everyday Life and Career … Pioneering the Future Together)
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
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
Hands-On APIs for AI and Data Science: Python Development with FastAPI
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
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?”
![Express Rip Free CD Ripper Software - Extract Audio in Perfect Digital Quality [PC Download]](https://m.media-amazon.com/images/I/41xx28xHa+L._SL500_.jpg)
Express Rip Free CD Ripper Software – Extract Audio in Perfect Digital Quality [PC Download]
Perfect quality CD digital audio extraction (ripping)
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
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.
Implications of the Missing Skills Marketplace
The absence of a dedicated skills marketplace limits the ability for developers and organizations to monetize their AI artifacts, reducing incentives for creating high-quality skills. It also hampers discovery, security verification, and enterprise compliance, which are critical for broader adoption in business environments. Establishing such a marketplace could become a strategic advantage, enabling a new layer of value capture in the AI stack and fostering a more open, secure, and competitive ecosystem.
Evolution of AI Skills Ecosystem and Standardization
The concept of AI skills has gained traction as a way to modularize and reuse AI capabilities across models and platforms. The open standard published by Anthropic in December 2025 has formalized the format, making skills portable and interoperable. Major AI companies have integrated skills into their products, but the ecosystem remains fragmented without a unified marketplace or monetization layer. Currently, discovery is limited to community directories, and security or vetting mechanisms are minimal, relying on source trust.
This situation contrasts with the rapid growth of app stores and marketplaces in other tech sectors, which have driven innovation, monetization, and user trust. The current state reflects a foundational infrastructure layer that is ripe for commercial development but has yet to be realized.
“The marketplace layer does not exist yet, despite the open standard and reference implementations. This is the key gap that companies can capitalize on.”
— Thorsten Meyer
Unresolved Challenges in Building a Skills Marketplace
It is not yet clear which company or consortium will successfully develop and dominate the skills marketplace, or how security, verification, and monetization mechanisms will be implemented at scale. The regulatory and enterprise compliance hurdles remain unaddressed, and the timeline for a fully operational platform is uncertain, estimated to take between 9 to 18 months.
Next Steps Toward a Viable Skills Ecosystem
Key developments include the formation of dedicated platforms or consortia to host skills, the development of security and verification protocols, and the integration of monetization features. Industry players and startups are expected to begin launching pilot marketplaces within the next year, with broader adoption contingent on establishing trust, standards, and value capture mechanisms.
Key Questions
Why is there no marketplace for AI skills yet?
While the open standard and reference implementations exist, the ecosystem has yet to develop a commercial platform that hosts, verifies, and monetizes skills, due to technical, security, and business model gaps.
Who could benefit most from a dedicated skills marketplace?
Developers, organizations, and AI platform providers who want to monetize, discover, and securely share AI skills would benefit, enabling a more vibrant and open ecosystem.
When might a skills marketplace become operational?
Industry estimates suggest a viable marketplace could emerge within 9 to 18 months, as companies address security, verification, and monetization challenges.
What are the main obstacles to building this marketplace?
Key challenges include establishing security and vetting protocols, creating standards for monetization, and achieving cross-surface portability and enterprise compliance.
Source: ThorstenMeyerAI.com
