📊 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 been established, no dedicated marketplace with monetization, vetting, or discovery features exists yet. This gap represents a significant opportunity for future development.
Despite the existence of open standards and multiple community directories for AI agent skills, there is currently no dedicated, monetized marketplace platform that facilitates discovery, vetting, or secure distribution of these skills, creating a significant infrastructure gap in the AI ecosystem.
Since December 2025, the open standard for AI agent skills has been established at agentskills.io, supported by reference implementations from Anthropic, OpenAI, and others, enabling interoperability across different models and runtimes. However, there is no equivalent of an app store or marketplace that offers discoverability, vetting, security auditing, or revenue sharing for these skills.
Existing directories like SkillsMP, ClaudeWorld, and GitHub list over 140 free skills, but these are primarily discovery layers without monetization or security protocols. The standard itself is a specification, not a capture or monetization platform, and current tooling relies heavily on trust and community reputation.
Major AI companies such as Anthropic, OpenAI, Microsoft, and Google have published skill collections, but they do not operate a unified marketplace. Skills are uploaded to individual models or APIs without cross-surface portability or a shared infrastructure for discovery or commercial transactions.
Experts see this as a critical gap, with the potential to become the most defensible position in the post-model-commoditization AI stack if addressed effectively. The window to build such a marketplace is estimated at roughly 9 to 18 months, with smaller firms positioned to capitalize on this opportunity.
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 2025AI agent skills security auditing tools
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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
Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more
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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 skill vetting and verification tools
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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 Critical Infrastructure Gap
The absence of a dedicated skills marketplace limits the ability for organizations and developers to discover, vet, and monetize AI skills efficiently. This hampers ecosystem growth, creates security risks, and slows innovation by fragmenting distribution channels. Building a trusted, secure, and monetized marketplace could become a key competitive advantage and a foundation for scalable AI deployment.
Emergence of Skills Standards and Ecosystem Fragmentation
Since late 2025, the AI skills ecosystem has matured with open standards and community directories, but these remain primarily discovery tools. The lack of a formal marketplace means that skills are often shared informally via GitHub or community sites, with no consistent vetting or monetization process. Major AI firms have published skills collections, but these are siloed within their platforms, preventing cross-surface portability or commercial scaling. The standard at agentskills.io provides a technical foundation, but the marketplace infrastructure—discovery, vetting, security, and monetization—remains undeveloped, representing a strategic gap in the AI ecosystem.
“The marketplace layer does not exist. No revenue share, no vetting, no security audit pipeline—just a standard and directories. This is the gap that, if filled, could shape the future of AI deployment.”
— Thorsten Meyer
What Specific Features Will a Future Skills Marketplace Include?
It is not yet clear what the definitive design of a monetized, secure skills marketplace will look like. Key questions include how to implement vetting, security audits, revenue sharing, and cross-surface portability at scale. The timeline for development and adoption remains uncertain, and whether smaller firms or larger players will lead the effort is still unresolved.
Next Steps Toward Building a Functional Skills Marketplace
Developers and companies are expected to begin pilot projects around marketplace features such as vetting protocols, security standards, and discoverability tools within the next 9 to 18 months. Major AI firms may collaborate or compete to create integrated platforms, but a widely adopted, monetized marketplace is likely still 1-2 years away. The focus will be on establishing trust, security, and interoperability to facilitate commercial scaling of AI skills.
Key Questions
Why is there currently no marketplace for AI skills?
While standards and directories exist, a dedicated marketplace with features like vetting, security, and monetization has not yet been developed, mainly due to technical, security, and business model challenges.
What are the main barriers to building a skills marketplace?
Key barriers include establishing security and vetting protocols, creating cross-surface portability, implementing revenue sharing models, and gaining industry consensus on standards and trust frameworks.
Who is most likely to lead the development of a skills marketplace?
Smaller, innovative firms with agility and focus on ecosystem standards are positioned to lead, but larger companies like Microsoft, Google, or Anthropic could also play significant roles.
How will a skills marketplace impact AI deployment?
It would streamline discovery, enhance security, enable monetization, and accelerate innovation by providing a trusted infrastructure for deploying and sharing AI capabilities at scale.
Source: ThorstenMeyerAI.com
