📊 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 for portable AI skills exists and some reference implementations are in place, a formal marketplace with discovery, security, and monetization features has not yet been built. This gap presents opportunities for early movers in AI infrastructure.
Despite the existence of an open standard for AI skills and multiple reference implementations, no dedicated marketplace for these skills has been built yet, leaving a critical gap in the AI ecosystem that could determine future industry leaders.
In May 2026, over 140 free AI agent skills are available across community repositories, with official skills from companies like Anthropic, OpenAI, Microsoft, Google, and Vercel. The open standard, published at agentskills.io in December 2025, enables skills to be portable across different AI models and runtimes, supporting configuration and instruction files in YAML frontmatter.
However, the marketplace layer — where skills could be discovered, vetted, monetized, and securely managed — remains absent. Currently, discovery relies on GitHub stars and word-of-mouth, with no revenue sharing, vetting, or security audit pipelines in place. Skills are free, with no monetization or formal verification process, and cross-surface portability is limited, as skills uploaded to one platform are not accessible via others’ APIs.
Industry insiders see this as a significant opportunity. The lack of a marketplace means the ecosystem is fragmented, with no centralized platform for organizations to build, share, or monetize skills at scale. Smaller companies and developers could seize this opportunity to establish dominance if they develop a secure, discoverable, and monetized marketplace soon.
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
Winning Without Persuading: A New Framework for Leading with Curiosity and Story Discovery
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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-Powered Software Audits: Revolutionizing Audit, Compliance, Risk, Security, and Governance for Organizations: Harnessing AI to Automate Compliance, and Strengthen Governance in the Digital era
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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?”
The Future of Video Platforms: AI, Streaming, and the Next Digital Revolution (Smarter Content Creation & Monetization)
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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.
Potential Industry Shift Toward a Skills Marketplace
The absence of a dedicated skills marketplace represents a strategic gap that could influence which companies dominate AI infrastructure in the coming years. A marketplace would facilitate discovery, vetting, security, and monetization, making it easier for organizations to leverage and protect their custom skills. Early entrants could establish a competitive moat, especially if they implement enterprise-grade security and compliance features.
This gap also means that current AI models and runtimes remain largely siloed, limiting interoperability and the full potential of portable skills. The companies that build the first robust, secure, and scalable marketplace could capture a significant share of the value in AI services, shaping the post-model-commoditization landscape.
Evolution of the AI Skills Ecosystem and Open Standards
The concept of portable AI skills gained traction in late 2025, with Anthropic publishing the open standard in December. Several reference implementations, including Anthropic’s own products and OpenAI’s Codex CLI, have adopted the format. Community directories like SkillsMP, ClaudeWorld, and GitHub host hundreds of free skills, but these serve primarily discovery purposes and lack monetization or security features.
Prior to this, the AI industry focused heavily on model development and APIs, with little emphasis on portable, reusable artifacts. The open standard aims to change that by establishing a common format for skills that can be loaded into various agents and runtimes, enabling interoperability. Despite these advances, the marketplace infrastructure—discovery, vetting, monetization—remains unbuilt, representing a critical missing layer in the ecosystem.
„The standard exists. The marketplace does not. The window is roughly 9–18 months.“
— Thorsten Meyer
Unclear Timing and Market Adoption of a Skills Marketplace
It remains uncertain when a fully functional, secure, and monetized skills marketplace will emerge. While the open standard is established, no major company has yet committed to building the platform, and the timing for widespread adoption is unclear. Additionally, questions remain about how security, vetting, and enterprise compliance will be integrated at scale.
Next Steps for Building a Viable Skills Ecosystem
The next 12–18 months will be critical for startups and established companies to develop and launch marketplaces that support discovery, vetting, and monetization of AI skills. Key milestones include establishing security protocols, enterprise integrations, and user-friendly discovery tools. Early success could define industry standards and establish market dominance.
Key Questions
Why is there no marketplace for AI skills yet?
While the open standard exists and reference implementations are in place, companies have not yet built or launched dedicated marketplaces that support discovery, vetting, or monetization of skills at scale.
Who stands to benefit most from a skills marketplace?
Early movers who build secure, scalable, and discoverable marketplaces could establish a dominant position in AI infrastructure, capturing significant value as the ecosystem matures.
What are the main challenges in creating a skills marketplace?
Key challenges include establishing security and vetting processes, enabling cross-surface portability, integrating enterprise compliance, and creating user-friendly discovery and monetization features.
When might a skills marketplace become mainstream?
Industry insiders suggest a window of roughly 9–18 months for a viable, widely adopted marketplace to emerge, but timing remains uncertain and depends on industry momentum and investment.
Source: ThorstenMeyerAI.com
