📊 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 comprehensive, monetized marketplace layer remains undeveloped. This creates a strategic gap for companies aiming to dominate AI infrastructure.
Despite the existence of an open standard for AI skills and several community directories, no marketplace currently aggregates, verifies, or monetizes these skills across different AI models or platforms.
In May 2026, over 140 free AI agent skills are available through community directories, with official skills published by Anthropic, OpenAI, Microsoft, Google, and Vercel. These skills follow a common open standard at agentskills.io, adopted by major players and enabling cross-model compatibility.
However, there is no dedicated marketplace akin to an App Store that offers vetted, discoverable, and monetized skills. Existing directories are community-driven, with no revenue sharing, vetting, or security auditing beyond trust in source. Skills uploaded to one platform, such as Claude or Codex, are not portable to others, creating fragmentation.
Industry insiders note that this gap represents a strategic opportunity: whoever builds a secure, discoverable, and monetized skills marketplace could establish a dominant position in the post-model-commoditization AI stack. The current ecosystem is characterized by open standards, reference implementations, and free discovery layers, but lacks a marketplace layer that captures value.
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
Mastering Codex for Parallel AI Agents: Run multiple AI agents at once and verify their work — a non-engineer's guide to supervising Codex (Codex Mastery Series Book 2)
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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
Association Rule Mining: Models and Algorithms (Lecture Notes in Computer Science, 2307)
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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?”
Tricks for enterprise-level security monitoring and vulnerability assessment in Python: Using advanced tools and frameworks for security auditing and penetration testing (Japanese Edition)
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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 Dominance
The absence of a dedicated skills marketplace limits the ability of organizations to monetize their AI expertise and hampers interoperability across platforms. Building such a marketplace could shift value from model providers to organizations creating specialized skills, enabling new business models and ecosystem growth.
This gap also presents a competitive advantage for smaller firms or startups that develop secure, discoverable, and monetized skill ecosystems, potentially reshaping AI infrastructure ownership and control in the coming 18 months.
Open Standards and Ecosystem Fragmentation in AI Skills
Since late 2025, the AI community has seen the emergence of an open standard for skills, with multiple reference implementations and community directories. However, the marketplace layer—where skills would be discoverable, secure, and monetized—remains undeveloped.
Major AI firms have published skills collections and adopted the open standard, but interoperability is limited. Skills are currently free, with no vetting or security pipeline, and are siloed within individual platforms. This fragmentation hampers the ecosystem’s growth and the potential for scalable monetization.
Industry analysts suggest that the next critical phase involves building a trusted, cross-surface marketplace that can verify, monetize, and facilitate discovery of skills across the AI ecosystem.
“The standard exists, but the marketplace does not. The window to build it is roughly 9 to 18 months, and whoever captures it first will secure a dominant position.”
— Thorsten Meyer
Unresolved Challenges in Building a Skills Marketplace
It remains unclear which company or consortium will successfully develop a trusted, secure, and monetized skills marketplace within the next 9 to 18 months. Security, vetting, and cross-surface discoverability are still unresolved issues, and the regulatory or enterprise compliance requirements are not yet defined.
Additionally, the actual business models and revenue-sharing mechanisms have yet to be tested or agreed upon.
Next Steps for Ecosystem Builders and Enterprises
In the coming months, industry leaders and startups are expected to experiment with prototype marketplaces, focusing on vetting, security, and discoverability. Standardization efforts will likely evolve to incorporate security and compliance features.
Key milestones include establishing trust frameworks, developing cross-surface discovery tools, and testing monetization models. Companies that succeed in these areas could capture a significant share of the emerging AI skills economy.
Key Questions
What is an AI skills marketplace?
An AI skills marketplace is a platform where organizations can discover, verify, and monetize portable AI skills that can be loaded into different AI models and platforms.
Why hasn’t a skills marketplace been built yet?
While standards and directories exist, challenges around security, vetting, discoverability, and revenue sharing remain unresolved, preventing the development of a trusted, monetized marketplace.
Who stands to benefit most from a skills marketplace?
Smaller firms, startups, and enterprise organizations that develop specialized skills could benefit by capturing value directly, rather than relying solely on model providers or platform vendors.
When is a skills marketplace likely to emerge?
Industry insiders estimate that a functional, secure, and monetized marketplace could emerge within 9 to 18 months, depending on technological and regulatory developments.
What are the main technical challenges?
Key challenges include establishing trust and security, creating cross-surface discoverability, and developing sustainable revenue-sharing or vetting mechanisms.
Source: ThorstenMeyerAI.com
