📊 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 for AI skills has been established and several reference implementations exist, a formal, monetized marketplace has not yet emerged. This gap presents a strategic opportunity for companies to shape the future AI ecosystem.
Despite the existence of an open standard for AI skills and multiple reference implementations, there is no dedicated marketplace for these skills as of May 2026. This gap represents a significant opportunity for companies to establish a dominant ecosystem in the evolving AI infrastructure landscape.
In May 2026, over 140 free AI skills are available on community platforms, with several major tech firms like Anthropic, OpenAI, Microsoft, Google, and Vercel publishing their own collections. The open standard for skills, defined at agentskills.io in December 2025, enables skills to be portable across different AI models and runtimes. However, no commercial marketplace exists that aggregates, verifies, or monetizes these skills, creating a significant gap in the ecosystem.
Current infrastructure includes reference implementations by Anthropic and OpenAI, free discovery directories such as SkillsMP and GitHub, and partner directories like Anthropic’s partner list. Yet, there is no revenue-sharing model, no vetting process, and no security pipeline beyond trust in source. Skills uploaded to one platform are not portable to others, and there is no monetization or paid skills marketplace. This fragmentation limits discovery, security, and enterprise adoption, leaving the space open for a new entrant to build a comprehensive marketplace layer.
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
The Journalist’s Toolbox
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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
Auditing Artificial Intelligence
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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?”
CHATGPT MASTERY GUIDE 1: A Solution for Content Creators Looking to Save Time and Earn Millions using CHATGPT AI (CHATGPT MASTERY GUIDES)
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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 Matters for AI Ecosystems
The absence of a dedicated skills marketplace hampers the growth, security, and monetization of AI skills, delaying widespread enterprise adoption and ecosystem development. A well-structured marketplace could become the core infrastructure for AI customization, enabling organizations to package, share, and monetize their expertise, thus capturing significant value in the AI stack. Companies that establish this layer early could secure a defensible position in the post-model-commoditization era, shaping future AI deployment and innovation.The Evolution of AI Skills Infrastructure
Since late 2025, the AI skills ecosystem has rapidly developed around an open standard, with multiple reference implementations and discovery directories. The standard, published at agentskills.io, allows skills to be portable and reusable across different models and runtimes. Major AI providers like Anthropic and OpenAI have adopted the format, but the market has yet to build a dedicated platform for buying, selling, or vetting skills. The ecosystem remains fragmented, with discovery limited to community repositories and no monetization channels.
This landscape reflects a broader shift in AI infrastructure, where the model itself is becoming commoditized, and the value shifts toward reusable, organizational, and customer-specific artifacts—skills—that can survive model swaps. The next step is establishing a marketplace that can support security, verification, discovery, and monetization at scale.
“The marketplace layer does not exist yet, despite the open standard and reference implementations. This is the critical gap that companies can capitalize on.”
— Thorsten Meyer
Unresolved Challenges in Building the Marketplace
It is still unclear which company or ecosystem will take the lead in building the first comprehensive AI skills marketplace. Questions remain about how to implement vetting, security, monetization, and cross-surface portability at scale. The regulatory and enterprise compliance implications are also still evolving, and it is uncertain how quickly these barriers will be addressed.
Next Steps for Ecosystem Development
Within the next 9 to 18 months, expect efforts from smaller firms and startups to attempt building the first viable marketplace layer, leveraging the open standard. Major AI providers may also introduce their own marketplaces or integrations. Key milestones include establishing vetting processes, security audits, and monetization models, which will determine the ecosystem’s future shape and dominance.
Key Questions
Why is there no marketplace for AI skills yet?
While the open standard and reference implementations exist, the ecosystem lacks a dedicated platform that offers discovery, vetting, security, and monetization. Building such a marketplace involves technical, security, and business challenges that have yet to be fully addressed.
Who is most likely to build the first AI skills marketplace?
Smaller startups or niche ecosystem players are currently best positioned to develop the initial marketplace, given their agility and focus. Larger providers may launch their own platforms later, once the ecosystem proves viable.
What are the main barriers to creating a skills marketplace?
Key barriers include establishing trust through vetting and security, developing monetization models, ensuring cross-surface portability, and managing enterprise compliance and security standards.
How will a skills marketplace impact AI adoption in enterprises?
A dedicated marketplace would streamline discovery, verification, and deployment of skills, reducing friction and increasing enterprise confidence. This could accelerate AI integration across industries and enable organizations to monetize their expertise.
Source: ThorstenMeyerAI.com
