I Published Skills to 5 AI Marketplaces in One Week — Here's the Brutal Automation Ceiling Test

I've spent months building agent skills (SKILL.md files) that turn AI coding agents into specialists — stock scanners, content pipelines, document tools. Earlier this year I made the leap from "tools for myself" to "products for sale." In one week I published skills and MCP servers to five AI marketplaces: Agensi, Xiaping, Apify, MCPize, and Capafy.

The revenue so far: $0. And I'm not ashamed to say it, because the real product of that week wasn't sales — it was a decision framework I now use before writing a single line of code. I call it the automation ceiling test, and it would have saved me days of work if I'd known it earlier.

The automation ceiling: check this BEFORE you build

Every marketplace falls into one of three tiers. Ask one question first: can a program publish to this platform end-to-end, or does a human have to click at some point?

Here's the trap: I built an entire skill package for Agensi first — ZIP, cover art, pricing research — before discovering it has no publish API. Everything was ready except the one step that can't be automated. The lesson: never do five rounds of workarounds around a platform that a 30-second API check would have disqualified. Map the ceiling first, then decide how much effort the platform deserves.

What I learned from each marketplace

Xiaping (xiaping.coze.com) — the most automation-friendly of the five. Full REST API: multipart upload, category via Unicode-escaped JSON arrays, pledge confirmation in the payload. After publishing, each skill enters a 30-day trial period while security and duplicate detection run. One practical gotcha: the file field must end in .zip or the API rejects it with "File must be a ZIP file."

Apify — building the Actor (a Python MCP server) was fully scriptable with apify-cli. Publishing to the Store is half-automated: after you accept the Store terms once in the console, isPublic: true + categories work via the API. 80% revenue share, and they pay monthly — about $1.4M a month to developers across the platform.

MCPize — a marketplace for MCP servers specifically, with a CLI (npx mcpize has login/deploy/publish commands). Also 80% share, and they handle hosting, payments, and tax. Same product can be listed here and on Apify — no exclusivity.

Capafy — lets you publish an agent (a bundled collection of skills) rather than single skills. I published one with 100 sanitized skills as a single agent.

Agensi — the best-looking onboarding (70% share, $3–$59 pricing, Stripe connected) and the worst automation. Web-UI-only publishing. It's a fine marketplace if you're a human who enjoys filling forms; it's a dead end for a pipeline that should run unattended.

The part nobody advertises: trial periods and promotion

Getting a skill listed is not the finish line. On Xiaping, a new skill sits in a 30-day community trial — no storefront listing until moderation and duplicate checks pass. That's a second pipeline to monitor: polling notifications, checking review status, fixing rejections.

And then there's the hard truth that no marketplace will tell you: distribution is 80% of the work. I spent one unit of effort building skills and two units promoting them — GitHub issues, README badges, cross-posts to Dev.to, community engagement. A skill with zero discoverability is a file that happens to be on a server. If you publish and walk away, you've shipped a product to an empty room.

The concrete publish flow (Xiaping, fully automated)

# Build the skill ZIP locally, then:
curl -X POST https://xiaping.coze.com/api/skills \
  -H "Authorization: Bearer $XIAIPING_KEY" \
  -F 'file=@a-share-stock-analyzer.zip' \
  -F 'name=A-Share Stock Analysis Expert' \
  -F 'description=Three-pillar A-share scanner: technical + fundamental + sentiment' \
  -F 'trigger=["stock","a-share","scan"]' \
  -F 'category=["\u6548\u7387\u5de5\u5177"]' \
  -F 'pledge={"agreed":true}'
# Then poll GET /api/notifications for security/duplicate-check results.

(Yes, that category is "efficiency tools" in Unicode — the API rejects raw Chinese in that field. The kind of detail you only learn by hitting the error.)

What I'd do differently

1. Automation ceiling first, product second. A 2-minute API doc skim would have saved me a full day on Agensi.
2. One marketplace to start. I spread five listings across five platforms in a week — five moderation queues, five notification systems, five marketing problems. One platform, done well, beats five platforms, half-finished.
3. Treat trial periods as a product phase, not a waiting room. The 30-day trial is when you iterate on the skill based on community feedback — not when you stop looking at it.
4. Revenue split matters less than automation. 80% of a sale that happens automatically beats 70% of a sale you must remember to upload by hand.

None of this made me money yet. But I now have a repeatable, mostly-automated pipeline — skills built, zipped, published, and monitored with a single script — and the marketplaces where that pipeline actually works. The money comes from volume, and volume comes from automation.

Everything I build is open source: https://github.com/Felixwang007 (MIT). The A-Share Stock Analysis Expert skill (three-pillar system: MACD/KDJ/RSI/volume-price + ROE/PEG fundamentals + capital-flow sentiment) is live on xiaping.coze.com — search "A-Share Stock Analysis" to try it.

Have you hit an automation ceiling on a marketplace I haven't listed? Tell me in the comments — I'm building a public table of which platforms are actually automatable, and real-world data beats my five data points.