📊 Full opportunity report: The Skills Marketplace Nobody Is Building Yet on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
While open standards and directories for AI skills have emerged, a true marketplace for buying, selling, and vetting skills is not yet built. This gap presents an opportunity for companies to capture a key layer of AI infrastructure.
Despite the existence of an open standard and multiple directories for AI skills, a comprehensive marketplace layer for buying, selling, and vetting these skills has not been built as of May 2026. This gap represents a critical missing piece in the AI ecosystem, with potential implications for industry dominance and innovation.
In May 2026, over 140 free AI skills are available across community directories, with major companies like Anthropic, OpenAI, Microsoft, Google, and Vercel publishing collections of skills. These skills are standardized via the agentskills.io open standard, adopted by OpenAI’s Codex CLI and Anthropic’s Claude platform, enabling interoperability and portability across different AI models and runtimes.
However, despite the technical standard and reference implementations, there is no dedicated marketplace layer akin to an app store. The current ecosystem lacks a central platform for discovery, vetting, monetization, or security auditing of skills. All existing directories are community-driven and free, with no revenue share or formal verification process. Skills are uploaded and discovered primarily via GitHub stars and word of mouth, with no cross-surface portability between major AI providers beyond the standard.
This absence of a marketplace layer means that the value creation and capture are limited to the open-source community and individual organizations. The standard exists, but the marketplace—where users, developers, and organizations can buy, sell, and trust skills—is still missing. Industry insiders see this as a critical gap that, if filled, could establish a dominant position in the post-model-commoditization AI stack.
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![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)
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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
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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?”
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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.
Potential Impact of a Dedicated Skills Marketplace
The lack of a formal marketplace for AI skills limits monetization, security, and discoverability, hindering the ecosystem’s growth. Building such a marketplace could enable new revenue streams, improve trust through vetting, and accelerate AI adoption across industries. Companies that establish this layer early could gain a defensible position in the AI infrastructure landscape, shaping how organizations deploy and customize AI agents for years to come.
Evolution of AI Skills Infrastructure
The concept of skills as portable, configurable artifacts emerged in late 2025, with the publication of the open standard by Anthropic. The format is simple: a YAML frontmatter with instructions, resources, and optional scripts, making it accessible even to non-engineers. Major AI providers quickly adopted the standard in their toolchains, creating reference implementations and directories. Despite this progress, the ecosystem remains fragmented without a marketplace to facilitate discovery, vetting, or monetization.
This situation mirrors early internet infrastructure, where standards existed but marketplaces and ecosystems took time to develop. Industry analysts see the next 9–18 months as critical for establishing this marketplace layer, which could become the core of AI customization and deployment at scale.
“The standard exists. The marketplace does not. The window is roughly 9–18 months.”
— Thorsten Meyer
Unresolved Challenges in Building the Marketplace
It remains unclear which organization or consortium will successfully establish the first comprehensive skills marketplace, and how issues like security, vetting, monetization, and cross-surface portability will be addressed at scale. The regulatory and enterprise compliance aspects are still evolving, and the exact timeline for widespread adoption is uncertain.
Next Steps for Ecosystem Development
Key players are expected to begin building and testing marketplace prototypes within the next 6–12 months, focusing on security, vetting, and discoverability features. Industry consortia or major AI providers may collaborate to establish standards for monetization and trust. The ultimate goal is a scalable, secure platform that supports both open-source and commercial skills, which could emerge as the dominant layer in AI deployment infrastructure by late 2027.
Key Questions
Why is a skills marketplace important for AI development?
A dedicated marketplace would enable better discovery, vetting, and monetization of AI skills, accelerating adoption and allowing organizations to customize AI more effectively.
Who is most likely to build the first successful skills marketplace?
Major AI platform providers like Anthropic, OpenAI, or industry consortia that can coordinate standards and security are the leading candidates.
What are the main challenges in creating this marketplace?
Key issues include establishing security and vetting procedures, enabling cross-surface portability, handling monetization, and gaining enterprise trust.
When can we expect a fully operational skills marketplace?
Industry insiders estimate a 9–18 month window for prototype development, with full-scale deployment possibly by late 2027.
How does this gap affect smaller developers or organizations?
Without a marketplace, smaller players face difficulties in discovery, trust, and monetization, which could limit innovation and ecosystem growth.
Source: ThorstenMeyerAI.com
