📊 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 and reference implementations for AI skills are in place, a dedicated marketplace layer has not yet been built. This gap could define the future of AI ecosystem development and value capture.
Despite the existence of an open standard and several reference implementations for AI skills, there is currently no dedicated marketplace layer where these skills can be discovered, verified, or monetized, representing a significant gap in the AI ecosystem.
In May 2026, over 140 free AI skills are available across community directories, with major players like Anthropic, OpenAI, Microsoft, Google, and Vercel publishing collections of skills. These skills are built on a shared open standard, SKILL.md, which enables interoperability across different AI models and runtimes. However, despite this technical foundation, there is no dedicated marketplace akin to an App Store where users can find, vet, or buy skills. The current ecosystem relies on GitHub stars, community word-of-mouth, and trust in source, with no formal security audits, verification, or monetization pathways.
This gap leaves a significant strategic opportunity for companies to build a marketplace layer that can facilitate discovery, security, and monetization, potentially capturing the most defensible position in the post-model-commoditization AI stack. The absence of such a marketplace means that, for now, the ecosystem remains fragmented and dependent on informal discovery methods, limiting growth and the potential for scalable 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 2025
Computer Aided Verification: 31st International Conference, CAV 2019, New York City, NY, USA, July 15-18, 2019, Proceedings, Part I (Lecture Notes in Computer Science Book 11561)
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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
Secure AI Agents with LangChain, MCP, and Tool-Using LLMs: A Developer’s Guide to Safe Invocation,Prompt Defense, and Context-Aware Generative Workflows
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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 Guide for Beginners: Join me on my self-discovery journey of AI: I will share visual examples, and helpful tips on what to type in the AI prompt box!
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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 Critical for AI Ecosystem Growth
The development of a dedicated skills marketplace is crucial because it would enable discovery, vetting, and monetization of AI skills at scale. Without it, the ecosystem risks remaining siloed, with trust and security gaps that hinder enterprise adoption and commercial viability. A marketplace would also serve as a strategic moat, allowing early entrants to control distribution and establish standards for security and quality assurance, which are currently unaddressed.
The Evolution of AI Skills and Ecosystem Infrastructure
Since the publication of the open standard at agentskills.io in December 2025, multiple companies have adopted and integrated the format into their products, including Anthropic and OpenAI. Several community directories and GitHub repositories host hundreds of free skills, but these are discovery layers without monetization or vetting mechanisms. The ecosystem has progressed from model-centric products to a focus on portable, reusable artifacts—skills—that can be swapped across models and runtimes. However, the missing piece remains a marketplace platform that can organize, verify, and facilitate transactions involving these skills.
“The marketplace layer does not exist yet, and this is the gap that will define the next phase of AI ecosystem development.”
— Thorsten Meyer
Unclear Timing and Adoption of a Skills Marketplace
It is not yet clear when a dedicated skills marketplace will emerge or gain widespread adoption. While the open standard and initial implementations are in place, the ecosystem’s fragmentation and lack of monetization pathways could delay or slow the development of a centralized platform. The timeframe of 9–18 months is an estimate based on current trends, but actual progress depends on industry players’ strategic priorities and market demand.
Next Steps for Building and Scaling the Skills Marketplace
Key developments to watch include the emergence of early marketplace prototypes, efforts to establish security and verification standards, and potential industry consortiums to formalize the ecosystem. Companies that invest early in building a trusted, discoverable, and monetizable platform could capture a defensible position, shaping the future of AI infrastructure. Monitoring industry moves and community adoption will be critical over the next year and a half.
Key Questions
Why is there no existing marketplace for AI skills yet?
While the open standard and reference implementations exist, the ecosystem has yet to develop a dedicated platform for discovery, vetting, and monetization, partly due to the complexity of security, verification, and trust issues.
Who stands to benefit most from a skills marketplace?
Companies that build, curate, and verify skills—especially smaller or innovative firms—could capture significant value, establishing a strategic position in AI ecosystem infrastructure.
What are the main challenges in creating a skills marketplace?
Key challenges include establishing security and verification pipelines, enabling cross-surface portability, creating monetization mechanisms, and gaining industry-wide adoption.
When might we see a fully operational skills marketplace?
Experts estimate a window of approximately 9 to 18 months for the emergence of a robust marketplace, but this depends on industry momentum and strategic investments.
Source: ThorstenMeyerAI.com
