Agensi vs Skillfully: marketplace sales or an author-led paid skill?

Agensi is a strong candidate when you want to list an agent skill in a public marketplace where people can discover and purchase it. Skillfully is a candidate when you have an established method and an audience, and want to publish a paid skill that readers access inside their AI workspace. The decision is about distribution, delivery, and ongoing responsibility together.

There is an important correction to a simple download-versus-subscription comparison: Agensi now describes both file installation and hosted skill execution, including subscriptions. MCP support and recurring billing alone do not distinguish these products.

This comparison is published by Skillfully. We reviewed public primary sources on September 30, 2026, and checked Skillfully’s relevant product implementation. We did not purchase an Agensi skill, complete seller onboarding, or test its runtime. Vendor descriptions below are documented claims, not independent performance findings.

The Agensi homepage presents a browsable store organized by task and agent. Its creator page describes packaging a skill, submitting it for review, setting a price, and distributing it through the store and MCP. It advertises one-time purchases and subscriptions, a 30% platform fee on net price, and 70% for creators. Its review and protection descriptions are vendor claims we have not independently audited.

Skillfully focuses on authors and experts who have a method and can reach their readers directly. Publishing begins through application and onboarding. It is not an open marketplace promising a stream of buyers from category listings. That makes audience fit a prerequisite rather than an incidental detail.

These are fit questions. Neither column establishes better output quality or a higher probability of earning money.

The Agensi MCP page distinguishes run_skill, which runs on its servers and returns a result, from install_skill, which installs files. It says subscription skills use hosted execution. It also describes a limited free-run allowance, paid unlocks, and update checks. Verify the particular listing and current allowance before relying on them.

Skillfully’s integration page describes an authenticated connection that lists accessible published skills, provides their manifests and runtime-safe files, and accepts feedback after explicit user confirmation. Access can depend on ownership, a gift, or current paid entitlement.

Those descriptions point to different execution questions. Does the buyer want a finished result from a hosted run? Does their own agent need instructions while it works interactively with them? Does the workflow require local files, external services, or confidential context? A logo for the same AI client does not answer any of these.

Ask for a demonstration with the actual task. A sales-call preparation skill should be evaluated with an incomplete account brief and conflicting goals, not just an ideal example. Notice whether the workflow asks useful questions, exposes uncertainty, and produces something the buyer can inspect.

A marketplace can help when the buyer starts with a task rather than an author’s name. Someone searching for a narrow code-review workflow may happily compare several unfamiliar creators. Clear compatibility information, examples, and a bounded promise matter in that purchase.

An author’s audience behaves differently. A reader may specifically want to apply the method from a book, workshop, or consulting engagement. The author’s identity and reasoning are part of what they are buying. An alternative with a similar task description may not be interchangeable.

This is why Agensi can be the better first experiment for a self-contained utility with no established audience, while Skillfully can fit an author extending an existing relationship. Both still need a convincing product. Marketplace placement does not guarantee qualified traffic; an email list does not guarantee willingness to pay.

Measure the first useful action, not only the sale. Can a new buyer reach the intended task, provide the necessary input, and understand what to do with the output? If people repeatedly need private rescue, include that support in the cost of delivery.

Imagine Maya, a fictional consultant with a weekly newsletter for agency owners. She has two possible products.

The first checks a proposal against a fixed checklist and produces a revision list. It requires little knowledge of Maya’s wider method. Buyers can evaluate it with a sample proposal, and the result is useful immediately. A marketplace listing could explain the product without a long introduction to its author. Agensi deserves a pilot for this use case, including its hosted route if Maya wants to evaluate that delivery model.

The second guides an owner through a recurring positioning review. Its value depends on distinctions Maya teaches in her workshops, and she expects to refine the method after seeing where readers struggle. Skillfully deserves an onboarding conversation for that product. Recurring payment still needs a recurring reason to use it; the workshop’s reputation cannot substitute for continuing value.

Maya should not combine both products simply to justify a larger subscription. She should write a separate promise for each: who it helps, what the buyer supplies, what they receive, what remains their responsibility, and when they will need it again.

For the proposal checker, success might mean buyers can identify three actionable revisions without contacting Maya. For the positioning review, it might mean readers can revisit the process with new evidence and understand why their recommendation changed. These are hypothetical evaluation criteria, not observed platform results.

Suppose Maya sets an illustrative net price of $40. Applying Agensi’s advertised 70% creator share gives $28 before Maya’s own business costs. This arithmetic is not a payout quote or a prediction of sales. Refunds, currency treatment, taxes, eligibility, and the precise agreement still need checking.

Do not place an invented Skillfully percentage beside that figure. Ask for the actual proposed terms and calculate both offers on the same basis. Include preparation, support, updates, and acquisition effort. Twenty minutes of help per buyer can matter more than a small commission difference.

Use three scenarios: no repeat use, occasional repeat use, and regular repeat use. Estimate the time you can support each scenario before considering optimistic revenue. Our guide to a paid pilot for an expertise product gives a practical way to bound this experiment.

Use this short worksheet with both providers:

1. Buyer and task: Name one buyer and one result they can inspect.
2. Delivery: Specify a local installation, hosted result, or connected interactive workflow.
3. Access: Ask what happens after purchase, refund, cancellation, and loss of account access.
4. Updates: Demonstrate how an existing buyer reaches a revised version.
5. Support: Identify who handles setup problems and who handles an inaccurate result.
6. Economics: Obtain the fee basis, payout conditions, and refund treatment in writing.
7. Proof: Run the same realistic task and retain the result and limitations.

No delivery model guarantees that instructions or outputs cannot be copied. Ask what the system actually controls, and treat protection claims as one part of the decision.

Choose Agensi when public discovery and a clearly packaged utility are central to your plan. Consider Skillfully when your method, reader relationship, and continuing improvement are central. For the wider field, read agent skills marketplaces compared; for packaging and commercial preparation, read how to sell a SKILL.md. If the Skillfully model fits, start with the application on the homepage and bring a working example.