Stripe Connect Integration Advisor
Recommends Stripe Connect account, responsibility, and payment-flow configurations for platform businesses.
Pure advisory recommendation flow: only reads local reference files, scans the codebase, and fetches a user-provided URL. No destructive operations, no credential exposure; auto-actions are limited to low-cost steps (plan generation, scan, reading references), every decision point requires numbered user confirmation, and the fee-economics check is mandatory. Deductions: WebFetch/WebSearch send user business data externally without explicit data-flow disclosure; no rollback concept (low impact here); publisher unverified, attribution limited to the repository itself.
SKILL.md and five reference files are internally consistent: decision matrix, compatibility matrix and template cross-reference coherently; BLOCKED/CAUTION/SALES-GATED rules align across files; failure paths (research unavailable, URL 403, conflicting signals) have clear degradation and messaging. Deductions: static review cannot execute anything; no test suite or CI evidence covering key paths; actual WebFetch-failure behavior depends on the host agent, so determinism is unproven — capped at the static anchor.
Trigger conditions are very specific (Connect configuration, split payments, marketplaces, KYC), with explicit non-fit exclusions (non-payment-routing SaaS, not-connect businesses); boundaries (on_behalf_of, OAuth, international expansion) are declared out of scope with redirect paths. Deductions: content depends entirely on Stripe overseas services and English docs, no Chinese-language support; mainland-China network reachability is undeclared, and company-researcher depends on WebFetch/WebSearch availability that is uncertain in the target environment.
Well-layered docs (SKILL.md main flow plus references with progressive disclosure), mature terminology rules, concise output and decision-point design, MIT license via the repository, and version awareness of v1/v2 API. Deductions: no skill-level version number, changelog, known-limitations list, or FAQ; maintenance responsibility is only inferable at the repository level, with no explicit skill-level update path.
Output usability is well designed: structured recommendation plan, optional write to connect-recommend-plan.md, clear code-side vs Dashboard responsibility split — clear marginal value over manually reading Stripe docs. Deductions: static review cannot verify actual correctness of recommendations; correctness rests on compatibility assertions in the references (e.g., blocked rules for Express + stripe losses) that are not independently corroborated, so the anchor cap applies.
Key claims link to official Stripe docs (docs.stripe.com, stripe.com/pricing); facts vs inference are separated via HIGH/MEDIUM/LOW confidence levels and required source lists. Deductions: no execution evidence or test reproducibility; whether parts of the compatibility matrix match Stripe's current GA policy cannot be verified statically; third-party corroboration is thin.
- The skill sends user-provided company URLs/descriptions to external services (WebFetch/WebSearch); data-sensitive users should be aware of this flow before use.
- All core content depends on Stripe overseas services and English documentation; reachability of WebFetch/WebSearch and some Stripe pages from mainland-China networks is unverified and may hinder Chinese users.
- BLOCKED/CAUTION rules in the compatibility matrix are author-compiled; static review cannot confirm they match Stripe's current GA policy — re-check against official docs before implementing.
- The skill files carry no version number or changelog; compare repository revision diffs when updating.
- Publisher is unverified in the FollowSkills registry; identity is treated as unknown, which is neither a deduction nor a trust signal.
What does this skill do, and when should you use it?
This Agent Skill from Stripe’s ai repository helps platform businesses choose a Stripe Connect integration shape. It targets marketplaces, multi-vendor stores, gig platforms, subscription platforms, and SaaS products that route money between parties. It gathers business context, scans project signals, validates configuration compatibility, and produces a recommendation plan. It also identifies relevant embedded components and implementation priorities.
Asks sequential questions about the business, parties, money flow, account management, risk, and fee structure; scans the project for existing Connect plans and patterns involving accounts, transfers, payouts, charges, fees, and webhooks; maps findings to dashboard, responsibility, fee-ownership, and charge-pattern recommendations; checks blocked and cautionary combinations; recommends embedded components for onboarding, notifications, account management, payments, disputes, payouts, and reporting; generates a recommendation plan and can write it to connect-recommend-plan.md at the project root.
- A marketplace needs to pay sellers or service providers.
- A multi-vendor store needs split payments or revenue distribution.
- A gig, booking, invoicing, or similar platform routes money between parties.
- A SaaS product has independent sellers who own customer relationships and needs Connect onboarding and payment guidance.
- A team needs to evaluate merchant onboarding, KYC, connected-account dashboards, or payment responsibility settings.
What are this skill's strengths and limitations?
- Covers business discovery, project scanning, configuration recommendations, compatibility checks, and plan generation.
- Targets concrete marketplace, SaaS, and multi-party payment decisions.
- Addresses margin economics, negative-balance liability, disputes, onboarding, and embedded components.
- The repository is licensed under MIT.
- The skill explicitly relies on AskUserQuestion, Task, and reference files, so hosts without equivalent support may require adaptation.
- The source provides no test suite, version compatibility matrix, or independent performance evidence.
- The source does not document a standalone installation flow for this individual skill.
- Recommendations depend on project scans and user answers; the source does not define exact failure behavior when those inputs are unavailable.
How do you install this skill?
This skill is one of 24 skills in stripe/ai. The README documents this manual installation command: npx skills add https://docs.stripe.com. It also documents official Stripe plugin installation for Claude Code, Codex, and Cursor. Manually installed skills do not auto-update; the README says to run npx skills update -y. No standalone installation command for connect-recommend is documented.
How do you use this skill?
In an Agent with the skill installed, describe the business or provide a company URL, for example: “We are building a marketplace connecting customers with freelancers and need to pay the providers.” The skill then asks questions, scans the project, and creates a Connect recommendation plan. The source does not document a more specific host-level trigger format.
How does this skill compare with similar options?
The README documents official plugin installation for Claude Code, Codex, and Cursor, as well as manual installation. It does not provide a feature comparison with another Connect recommendation tool.