📊 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 agent skills have emerged, a comprehensive, monetized marketplace layer has yet to be built. This gap presents opportunities and risks for AI ecosystem players.
There is currently no dedicated marketplace for AI agent skills, despite the existence of open standards, directories, and reference implementations. This gap remains a significant opportunity for companies aiming to capture value in the evolving AI ecosystem.
Since December 2025, an open standard for AI agent skills has been established at agentskills.io, supported by major players like Anthropic, OpenAI, Microsoft, Google, and Vercel. These skills are defined as YAML-based artifacts that can be loaded into different AI models and runtimes, enabling model interchangeability and modularity.
However, despite the standardization and the existence of community directories such as SkillsMP, ClaudeWorld, and GitHub repositories, there is no dedicated marketplace that facilitates discovery, curation, monetization, or security auditing of these skills. The current ecosystem relies on discovery via GitHub stars, word-of-mouth, and free directories, with no revenue sharing, vetting, or security pipelines beyond trust in source.
Industry insiders note that this absence of a marketplace layer leaves a critical gap in the AI stack. The marketplace layer would serve as the primary interface for organizations and developers to find, buy, sell, and verify skills, establishing a new revenue stream and security framework. Without this, the value remains fragmented and largely free, limiting monetization and enterprise adoption.
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 agent 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
Auditing Artificial Intelligence
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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.
Why a Skills Marketplace Is a Critical Missing Piece
The absence of a dedicated skills marketplace hampers the ability of organizations to monetize their custom skills and trust their security and quality. It also limits the ecosystem’s growth, as discoverability and curation are essential for scaling adoption. Building this layer could enable new business models, reduce vendor lock-in, and foster innovation in enterprise AI applications. Companies that establish a trusted, scalable marketplace could gain a defensible position in the post-model-commoditization era of AI.
The Evolution of AI Skills Infrastructure
Since late 2025, the AI industry has seen rapid development of open standards and community-driven directories for agent skills. Anthropic’s open standard at agentskills.io, adopted by OpenAI’s Codex CLI, has created a common format for defining skills. Major tech firms like Microsoft, Google, and Vercel have published their own collections, but no unified marketplace or monetization platform exists. The ecosystem is still in the early stages, with discovery primarily through community channels and no formal vetting or revenue mechanisms.
This fragmentation echoes earlier technology ecosystems where standards precede the creation of marketplaces. The current window, estimated to be 9-18 months, represents a critical opportunity for players to build the marketplace layer that will unlock full ecosystem potential.
“The marketplace layer does not exist yet, despite open standards and directories. This remains the biggest gap in the AI skills ecosystem.”
— Thorsten Meyer
Unclear Next Steps for Building the Marketplace Layer
It remains unclear which companies or consortiums will take the lead in developing a comprehensive marketplace platform. The specific business models, security protocols, and governance structures are still under discussion, and adoption by major players is not yet confirmed. The timeframe for launch and the regulatory or enterprise security standards that will be enforced are also still uncertain.
Expected Developments in the Next 9-18 Months
Key industry players are expected to announce or pilot marketplace initiatives within the next year, aiming to combine discovery, curation, and monetization features. Standardization efforts will likely evolve, and security protocols may be introduced to build trust. The emergence of a dominant platform or a consortium-led ecosystem could accelerate the creation of a full-fledged marketplace, shaping the future of AI skill commercialization.
Key Questions
Why is there no dedicated marketplace for AI skills yet?
While standards and directories exist, the industry has not yet organized a platform for discovery, security, and monetization. Building such a marketplace involves technical, security, and business challenges that are still being addressed.
What benefits would a skills marketplace bring?
A dedicated marketplace would improve discoverability, enable monetization, establish security and trust protocols, and foster ecosystem growth by providing a centralized platform for buying, selling, and verifying AI skills.
Who is likely to build the first major skills marketplace?
Smaller, innovative companies or consortiums that can move quickly are considered the most likely to develop the initial platforms. Major tech firms may also enter as the ecosystem matures.
How will security and trust be managed in the future marketplace?
Potential approaches include vetting and certification processes, security audits, and community-based reputation systems. The exact standards are still under development.
When can we expect a fully operational skills marketplace?
Industry estimates suggest a window of 9 to 18 months for initial launches, with broader adoption and maturity likely taking longer as standards and trust mechanisms evolve.
Source: ThorstenMeyerAI.com
