📊 Full opportunity report: The Skills Marketplace Nobody Is Building Yet on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
A new standard for AI skills exists with open specifications and reference implementations, but no dedicated marketplace has yet emerged. This gap represents a significant opportunity for innovation and value capture in AI ecosystems.
As of May 2026, a formal open standard for AI skills exists, along with reference implementations and community directories, yet no dedicated marketplace or ecosystem layer has been built to facilitate discovery, monetization, or security verification of these skills.
The open standard for AI skills was published by Anthropic in December 2025 at agentskills.io, enabling interoperability across multiple AI models such as Claude, GPT, and Codex CLI. Despite this, the marketplace layer—where skills could be discovered, vetted, and monetized—remains absent. Currently, skills are hosted on directories like SkillsMP, ClaudeWorld, and GitHub, with discovery primarily based on community reputation and GitHub stars. There are no revenue-sharing models, no vetting beyond source trust, and no cross-surface portability between different AI providers. This fragmentation limits the potential for scalable, secure, and monetized skills ecosystems.
Major AI companies like Anthropic, OpenAI, Microsoft, Google, and Vercel are publishing collections of skills and standards, but the actual marketplace infrastructure—akin to an app store—is missing. This gap is significant because it represents the next frontier for value creation, where customer-specific knowledge, procedural expertise, and organizational judgment can be packaged into portable, durable artifacts that become the core units of value in AI services. The absence of a marketplace hampers discoverability, security, and monetization, leaving a critical layer of AI infrastructure underdeveloped.
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
The AI Business Analyst Playbook: Discovery, Requirements, and Human Judgment in Practice
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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
Model Context Protocol (MCP) in Agentic RAG Systems: Building, Scaling, and Securing Agentic AI with MCP: Dynamic RAG, Tool Discovery, Interoperability, and Observability
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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 Programming Made Practical: A Step-by-Step Guide to Building AI-Powered Applications, Writing Better Code Faster, and Using Modern AI Tools with Confidence
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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 Layer
The lack of a dedicated skills marketplace limits the ability for organizations to discover, verify, and monetize their AI skills in a secure, scalable manner. This gap constrains the growth of a vibrant ecosystem where skills can be shared, vetted, and integrated seamlessly across different AI models and platforms. Building this marketplace could unlock new revenue streams, improve security and compliance, and accelerate innovation by enabling organizations to leverage their proprietary procedural knowledge as portable assets. The eventual development of such a marketplace could define the next major phase of AI infrastructure, shifting value from models alone to the packaged expertise embedded in skills.
Emergence of the Skills Standard and Ecosystem Layers
Since late 2025, a formal open standard for AI skills has been established, with the publication of the agentskills.io specification by Anthropic. Multiple reference implementations have been integrated into major AI platforms, including Anthropic’s Claude and OpenAI’s Codex CLI. Community directories such as SkillsMP and GitHub host hundreds of free, open-source skills, but these serve primarily discovery and community-building functions. Despite this progress, the marketplace layer—where skills could be securely bought, sold, and vetted—remains undeveloped. This situation mirrors early internet standards where infrastructure existed but a marketplace had yet to emerge, representing a significant opportunity for innovation.
“The marketplace layer does not exist yet, and that gap is where the most defensible position in the post-model-commoditization AI stack will form.”
— Thorsten Meyer
Uncertainties About Market Adoption and Security
It remains unclear when a fully functional, secure, and monetized skills marketplace will emerge, and which company or consortium will lead its development. Key challenges include establishing vetting processes, security audits, and cross-surface compatibility. The extent to which enterprises will adopt and trust such a marketplace is also uncertain, given current reliance on source trust and lack of formal verification pipelines.
Next Steps for Building a Skills Ecosystem Layer
The next 9 to 18 months will likely see the emergence of early marketplace prototypes, possibly driven by smaller companies or open-source initiatives. Major AI providers may begin integrating marketplace features, including vetting, discovery, and monetization tools. Industry collaboration on standards and security protocols will be crucial to enable widespread adoption. Ultimately, successful development of a secure, scalable marketplace could become a key competitive advantage and the defining infrastructure layer for AI ecosystems.
Key Questions
Why is there no marketplace for AI skills yet?
While standards and reference implementations exist, the marketplace layer—focused on discovery, vetting, and monetization—has not yet been built due to technical, security, and business challenges, as well as the nascent state of the ecosystem.
Who is likely to build the first AI skills marketplace?
It is uncertain, but smaller companies, open-source communities, or industry consortia are best positioned to develop early prototypes. Major AI firms may incorporate marketplace features once initial models prove viable.
What benefits would a skills marketplace bring to organizations?
A dedicated marketplace would improve discoverability, enable secure and verified sharing, facilitate monetization, and accelerate the adoption of proprietary procedural knowledge as portable assets.
How does the lack of a marketplace impact AI ecosystem growth?
Without a centralized marketplace, the ecosystem remains fragmented, limiting scale, security, and monetization opportunities, which could slow innovation and enterprise adoption.
When might we see a fully operational skills marketplace?
Industry estimates suggest that a functional marketplace could emerge within the next 9 to 18 months, but timing depends on technical developments, standards adoption, and enterprise trust-building.
Source: ThorstenMeyerAI.com
