📊 Full opportunity report: The Skills Marketplace Nobody Is Building Yet on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
An open standard for portable AI skills has been established, but no dedicated marketplace exists yet. This gap represents a key opportunity for ecosystem development and value capture.
While an open standard for AI agent skills has been established and several reference implementations exist, there is currently no dedicated marketplace platform to host, discover, or monetize these skills. This gap leaves the ecosystem fragmented and limits the potential for widespread adoption and value capture, making it a critical development to watch.
In December 2025, Anthropic published the Agent Skills standard at agentskills.io, creating a common format for portable AI skills. This standard, adopted by OpenAI’s Codex CLI and other major players, enables skills to be shared across different models and runtimes, with the core format comprising YAML frontmatter, instructions, and optional scripts. Despite this progress, there is no dedicated marketplace akin to an app store for AI skills, with no revenue sharing, vetting, or discovery mechanisms beyond GitHub stars and word of mouth. The existing ecosystem includes free directories such as SkillsMP, ClaudeWorld, and GitHub repositories, but these are discovery layers, not capture or monetization platforms. The industry is at a pivotal point: the infrastructure for portable skills exists, but the marketplace layer that would facilitate discovery, trust, and commercial activity has yet to be built. This represents a significant opportunity for smaller players to establish a defensible position, as the standard provides a foundation for a new ecosystem that could reshape AI application deployment and monetization.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 discovery tool
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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 Monetization Mastery(English) : Earning from AI Skills – Build Smart Income Streams Using Artificial Intelligence (Book no:6) (AI Automation Series)
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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?”

Technical Innovation, solving the Data Spaces and Marketplaces Interoperability Problems for the Global Data-Driven Economy (River Publishers Series … and Information Science and Technology)
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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 Missing Piece
The absence of a dedicated skills marketplace limits the ecosystem’s growth potential, hindering discovery, vetting, and monetization of AI skills. Without a platform, organizations and developers cannot easily share, trust, or monetize their skills, which slows innovation and adoption. Building this layer could unlock new revenue streams, enable organizational control over proprietary skills, and foster a vibrant ecosystem that extends the value of AI models beyond simple APIs. Smaller companies and startups are positioned to capitalize on this opportunity, potentially establishing a competitive advantage as the industry matures.
Progress and Gaps in the AI Skills Ecosystem
Since the open standard was published in December 2025, multiple reference implementations and directories have emerged, but these are primarily discovery tools without monetization capabilities. Major AI companies like Anthropic, OpenAI, Microsoft, Google, and Vercel have published skills collections and adopted the standard within their tooling. However, the marketplace layer—where skills can be hosted, discovered, and monetized—is still absent. The ecosystem resembles the early days of app stores before the launch of Apple’s App Store: the infrastructure exists, but the platform to connect creators and users is missing. Industry insiders suggest that the next 9 to 18 months will be critical for building this marketplace, which could become the dominant layer in the AI stack for enterprise and consumer applications.
“The standard exists. The marketplace does not. The window to build it is roughly 9 to 18 months.”
— Thorsten Meyer
Unresolved Challenges in Building the Skills Marketplace
It remains unclear which company or consortium will lead the development of the marketplace platform, or whether it will be built by a single entity or a coalition. Additionally, questions about security, vetting, monetization, and cross-surface compatibility are still open. The regulatory and enterprise compliance requirements for such a marketplace are also not yet defined, creating uncertainty about how quickly and widely it will be adopted.
Next Steps Toward a Functional Skills Marketplace
Key industry players are expected to begin investing in marketplace infrastructure over the next 9 to 18 months, with potential pilot platforms emerging from smaller firms or open-source communities. Major AI companies may also collaborate or develop proprietary solutions. The focus will likely be on establishing security protocols, vetting mechanisms, and discovery features. Monitoring these developments will be crucial to understanding how the ecosystem will evolve and which players will emerge as leaders in this space.
Key Questions
Why is there no marketplace for AI skills yet?
While the open standard for portable AI skills exists, a dedicated marketplace platform has not been built due to technical, security, and commercial challenges, and the lack of a clear industry leader to drive its development.
Who benefits most from a skills marketplace?
Developers, organizations with proprietary skills, and AI platform providers stand to benefit by enabling discovery, trust, and monetization, which can accelerate innovation and adoption.
When is a marketplace likely to emerge?
Industry sources suggest that a functional marketplace could be built within the next 9 to 18 months, with initial pilots and prototypes already in development.
What are the main challenges to building this marketplace?
Key challenges include establishing security and vetting protocols, ensuring cross-surface portability, creating discovery and ranking mechanisms, and developing a sustainable revenue model.
Source: ThorstenMeyerAI.com