📊 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 exist, no marketplace with discovery, security, or monetization features has been built yet. This gap represents a strategic opportunity in AI infrastructure.
As of May 2026, there is a confirmed open standard for AI skills and several reference implementations, but no marketplace layer exists to facilitate discovery, security, or monetization, representing a significant gap in AI infrastructure.
Multiple organizations, including Anthropic, OpenAI, Microsoft, Google, and Vercel, have published open standards and reference implementations for AI skills based on the SKILL.md format. These skills are portable across different models and runtimes, enabling configuration-based, model-agnostic artifacts that users and organizations create and keep.
Despite this progress, there is no dedicated marketplace akin to an app store for these skills. The current ecosystem relies on community directories, GitHub repositories, and word-of-mouth discovery, with no formal discovery, vetting, security auditing, or monetization mechanisms in place. Skills remain free, with no revenue share or official verification process, and cross-surface portability is limited by technical and policy gaps.
This absence creates a strategic opportunity for a company to build a marketplace layer that could serve as the primary distribution, security, and monetization hub for AI skills, potentially capturing significant value in the evolving AI stack.
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 skill discovery 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
AI security auditing software
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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 monetization solutions
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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 lack of a dedicated marketplace hampers the growth and adoption of AI skills by limiting discovery, security, and monetization options. Without a formal platform, organizations and developers face challenges in sharing, vetting, and monetizing their skills, which could slow innovation and create fragmentation.
Building this marketplace could establish a new infrastructure layer, enabling more secure, discoverable, and monetizable AI artifacts. Such a platform would also help establish standards for security audits and verification, reducing risks for enterprise adoption. The company that develops this layer first could dominate the post-model-commoditization AI ecosystem, gaining a defensible position in the value chain.
Current State of AI Skills Ecosystem and Standards
Since the open standard for AI skills was published by Anthropic in December 2025, a handful of reference implementations and community directories have emerged, hosting over 140 free, open-source skills. Major AI companies like Anthropic, OpenAI, Microsoft, Google, and Vercel have adopted or support the standard, enabling portability across models and runtimes.
However, despite the technical progress, the ecosystem remains fragmented. No marketplace exists to facilitate discovery, vetting, or monetization. Skills are mostly shared via GitHub or community sites, with no formal security or revenue-sharing mechanisms. The ecosystem’s current discovery relies on community reputation metrics like GitHub stars and word-of-mouth, which are insufficient for enterprise adoption.
“The marketplace layer for AI skills does not exist yet, despite the open standard and reference implementations. This is the critical gap that companies can fill.”
— Thorsten Meyer
Uncertainties Around Marketplace Development and Adoption
It remains unclear when a comprehensive marketplace layer will be built and adopted at scale. The technical, security, and business challenges—such as vetting, monetization, and cross-surface compatibility—are significant. Additionally, the competitive landscape and which company will lead this development are still uncertain.
Next Steps for Building and Scaling the Skills Marketplace
In the coming 9 to 18 months, expect efforts to emerge from smaller players or startups aiming to build a dedicated marketplace platform. Key milestones include establishing security standards, enabling discovery and ranking mechanisms, and developing monetization models. Large AI firms may also integrate marketplace features into their existing ecosystems, but the primary driver will likely be a dedicated, independent platform that can serve as the core infrastructure layer.
Key Questions
Why is there no existing marketplace for AI skills yet?
While standards and reference implementations exist, building a marketplace involves complex challenges around discovery, security, vetting, and monetization, which have not yet been addressed comprehensively by any platform.
How could a skills marketplace impact AI development and adoption?
A dedicated marketplace would facilitate discovery, security, and monetization, accelerating innovation and enterprise adoption of AI skills, and establishing a new infrastructure layer in the AI ecosystem.
Who is likely to develop the first successful AI skills marketplace?
Smaller companies or startups with a focus on infrastructure and standards are best positioned, as they can move quickly to address the current gaps and capture strategic value.
What are the main challenges in building this marketplace?
Challenges include establishing security and vetting standards, enabling cross-surface portability, creating discovery and ranking mechanisms, and developing sustainable monetization models.
When might we see a fully operational AI skills marketplace?
Industry insiders estimate it could take between 9 and 18 months for a viable, scalable marketplace to emerge and gain enterprise traction.
Source: ThorstenMeyerAI.com
