/connect-recommend
Use this skill when the user asks about Stripe Connect configuration, charge patterns, Dashboard access, or how to get started with Connect, is building a marketplace, platform, multi-vendor store, gig platform, or subscription platform, needs to pay out sellers, vendors, or
Claude Code
$ npx -y skills add stripe/ai --skill connect-recommend --agent claude-code
Codex
$ npx skills add stripe/ai --skill connect-recommend -a codex -y
Cursor
$ npx skills add stripe/ai --skill connect-recommend -a cursor -y
Gemini CLI
$ npx skills add stripe/ai --skill connect-recommend -a gemini-cli -y
GitHub Copilot
$ npx skills add stripe/ai --skill connect-recommend -a github-copilot -y
OpenCode
$ npx skills add stripe/ai --skill connect-recommend -a opencode -y
Windsurf
$ npx skills add stripe/ai --skill connect-recommend -a windsurf -y
SKILL.md
connect-recommend.SKILL.mdname: connect-recommend
description: >-
Use this skill when the user asks about Stripe Connect configuration, charge
patterns, Dashboard access, or how to get started with Connect, is building a
marketplace, platform, multi-vendor store, gig platform, or subscription
platform, needs to pay out sellers, vendors, or providers, mentions split
payments, revenue sharing, multi-party payments, or similar payment
distribution concepts, provides a company URL or business description for a
recommendation, builds SaaS that routes money between parties (for example,
POS, booking, invoicing — not operational SaaS without payment routing), asks
about onboarding or KYC for merchants, sellers, and vendors, mentions
connected account Dashboard or responsibility configurations, or asks about
payment flows, white-label payments, or embedded payments.
Connect recommend
Recommend the right Stripe Connect integration configuration. The user only needs to provide a company URL or describe their business — the skill figures out the rest.
Interaction model
**User must confirm interactions**. Every decision point in this skill MUST be confirmed with the user with clear, numbered options and short descriptions. One question at a time — never overwhelm the user.
**Auto-act on low-cost actions**. Never ask permission for:
- Generating the markdown recommendation plan — just generate it
- Scanning the codebase — just scan it
- Reading reference files — just read them
**Never end with passive text**. Every stopping point must end with a prompt to the user offering concrete next actions.
Terminology rules (user-facing output)
**Before generating any user-facing output, read <references/terminology-rules.md>**. Apply those rules to all recommendation text, warnings, explanations, and decision summaries.
Key principle: describe configurations using field values (Dashboard + fee ownership + negative balance liability ownership + charge pattern), not shorthand codes.
Output Brevity
Keep responses concise. The user is making decisions, not reading documentation.
- Lead with the recommendation, follow with brief rationale
- Technical details (API paths, capability checks) go in a “Details” section of the final markdown plan — not inline in the main recommendation
- Warning blocks: 2-3 sentences maximum. State the issue and the fix. No mechanism deep-dives unless the user asks.
- Decision summary: bullet points only, one line per decision
- Never output more than ~40 lines in a single response during interactive mode
**Only mention out-of-scope limitations when they’re directly relevant to what the user asked about**. Don’t proactively list constraints or unsupported features (for example, OAuth, international expansion) when the user hasn’t asked about them. “Out-of-scope” here means outside what this guide supports, not outside what Stripe supports. Research these topics in the Stripe public documentation (docs.stripe.com) rather than saying they’re out-of-scope.
Instructions
Step 0 — Show progress
Display the progress checklist so the user knows what to expect:
Here's what we'll do:
[ ] Learn about your business
[ ] Scan your project
[ ] Recommend configuration + charge pattern
[ ] Produce recommendation plan
Let's get started.
Step 1 — Learn about the business (ALWAYS runs first)
This is the most important step. Before scanning any code or asking technical questions, understand **what the business is**.
**1a. Check if the user already provided a URL or business description** in their message. Look for:
- A URL (for example, `https://...`, `www.`, `.com`, `.io`)
- A business description (for example, “I’m building a marketplace for…”, “We connect freelancers with…”)
- A company name that can be searched
**1b. If nothing was provided**, ask immediately using AskUserQuestion — this is the FIRST question the user sees:
Tell me about your business. Pick whichever is easiest:
Options:
- “I have a URL” — user provides URL, then research it
- “Let me describe it” — user provides description, then research it
- “Just scan my codebase” — skip to Step 2, rely on codebase signals only
- “Skip — ask me questions instead” — skip to Step 3 with full questionnaire
**1c. Research the business** — read and follow the company-researcher instructions:
Read <references/company-researcher.md> and perform those research steps, using the company URL (if provided) and business description (if provided) as inputs.
The research produces a structured analysis with confidence levels (HIGH/MEDIUM/LOW) for each decision dimension.
**1d. Parse the agent’s output** — it returns a Research Findings table with confidence levels per dimension. Read the decision matrix at <references/decision-matrix.md> and map the findings to a recommended configuration. Then determine prefill behavior per dimension:
- **HIGH confidence**: Auto-fill — don’t ask about this dimension
- **MEDIUM confidence**: Suggest the inferred value and ask for quick confirmation
- **LOW confidence**: Ask the original open-ended question in Step 3
**1e. Present what you learned** to the user (use second-person, conversational confirmation tone):
Here's what I gathered about your business — let me know if anything looks off:
┌──────────────────────────┬────────────────────────────────┐
│ *Business type* │ [marketplace or SaaS platform] │
├──────────────────────────┼────────────────────────────────┤
│ *Sellers/providers* │ [who they are] │
├──────────────────────────┼────────────────────────────────┤
│ *Buyers/customers* │ [who they are] │
├──────────────────────────┼────────────────────────────────┤
│ *How money flows* │ [payment flow] │
├──────────────────────────┼────────────────────────────────┤
│ *Fee structure* │ [fee details] │
└──────────────
Read more
name: connect-recommend description: >- Use this skill when the user asks about Stripe Connect configuration, charge patterns, Dashboard access, or how to get started with Connect, is building a marketplace, platform, multi-vendor store, gig platform, or subscription platform, needs to pay out sellers, vendors, or providers, mentions split payments, revenue sharing, multi-party payments, or similar payment distribution concepts, provides a company URL or business description for a recommendation, builds SaaS that routes money between parties (for example, POS, booking, invoicing — not operational SaaS without payment routing), asks about onboarding or KYC for merchants, sellers, and vendors, mentions connected account Dashboard or responsibility configurations, or asks about payment flows, white-label payments, or embedded payments.
Connect recommend
Recommend the right Stripe Connect integration configuration. The user only needs to provide a company URL or describe their business — the skill figures out the rest.
Interaction model
**User must confirm interactions**. Every decision point in this skill MUST be confirmed with the user with clear, numbered options and short descriptions. One question at a time — never overwhelm the user.
**Auto-act on low-cost actions**. Never ask permission for:
- Generating the markdown recommendation plan — just generate it
- Scanning the codebase — just scan it
- Reading reference files — just read them
**Never end with passive text**. Every stopping point must end with a prompt to the user offering concrete next actions.
Terminology rules (user-facing output)
**Before generating any user-facing output, read <references/terminology-rules.md>**. Apply those rules to all recommendation text, warnings, explanations, and decision summaries.
Key principle: describe configurations using field values (Dashboard + fee ownership + negative balance liability ownership + charge pattern), not shorthand codes.
Output Brevity
Keep responses concise. The user is making decisions, not reading documentation.
- Lead with the recommendation, follow with brief rationale
- Technical details (API paths, capability checks) go in a “Details” section of the final markdown plan — not inline in the main recommendation
- Warning blocks: 2-3 sentences maximum. State the issue and the fix. No mechanism deep-dives unless the user asks.
- Decision summary: bullet points only, one line per decision
- Never output more than ~40 lines in a single response during interactive mode
**Only mention out-of-scope limitations when they’re directly relevant to what the user asked about**. Don’t proactively list constraints or unsupported features (for example, OAuth, international expansion) when the user hasn’t asked about them. “Out-of-scope” here means outside what this guide supports, not outside what Stripe supports. Research these topics in the Stripe public documentation (docs.stripe.com) rather than saying they’re out-of-scope.
Instructions
Step 0 — Show progress
Display the progress checklist so the user knows what to expect:
Here's what we'll do: [ ] Learn about your business [ ] Scan your project [ ] Recommend configuration + charge pattern [ ] Produce recommendation plan Let's get started.
Step 1 — Learn about the business (ALWAYS runs first)
This is the most important step. Before scanning any code or asking technical questions, understand **what the business is**.
**1a. Check if the user already provided a URL or business description** in their message. Look for:
- A URL (for example, `https://...`, `www.`, `.com`, `.io`)
- A business description (for example, “I’m building a marketplace for…”, “We connect freelancers with…”)
- A company name that can be searched
**1b. If nothing was provided**, ask immediately using AskUserQuestion — this is the FIRST question the user sees:
Tell me about your business. Pick whichever is easiest:
Options:
- “I have a URL” — user provides URL, then research it
- “Let me describe it” — user provides description, then research it
- “Just scan my codebase” — skip to Step 2, rely on codebase signals only
- “Skip — ask me questions instead” — skip to Step 3 with full questionnaire
**1c. Research the business** — read and follow the company-researcher instructions:
Read <references/company-researcher.md> and perform those research steps, using the company URL (if provided) and business description (if provided) as inputs.
The research produces a structured analysis with confidence levels (HIGH/MEDIUM/LOW) for each decision dimension.
**1d. Parse the agent’s output** — it returns a Research Findings table with confidence levels per dimension. Read the decision matrix at <references/decision-matrix.md> and map the findings to a recommended configuration. Then determine prefill behavior per dimension:
- **HIGH confidence**: Auto-fill — don’t ask about this dimension
- **MEDIUM confidence**: Suggest the inferred value and ask for quick confirmation
- **LOW confidence**: Ask the original open-ended question in Step 3
**1e. Present what you learned** to the user (use second-person, conversational confirmation tone):
Here's what I gathered about your business — let me know if anything looks off: ┌──────────────────────────┬────────────────────────────────┐ │ *Business type* │ [marketplace or SaaS platform] │ ├──────────────────────────┼────────────────────────────────┤ │ *Sellers/providers* │ [who they are] │ ├──────────────────────────┼────────────────────────────────┤ │ *Buyers/customers* │ [who they are] │ ├──────────────────────────┼────────────────────────────────┤ │ *How money flows* │ [payment flow] │ ├──────────────────────────┼────────────────────────────────┤ │ *Fee structure* │ [fee details] │ └──────────────
This repository contains Stripe agent plugins and skills, and benchmarks for building AI-powered products and businesses on top of Stripe.
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Questions about connect-recommend.
- Which coding agents can use connect-recommend?
- connect-recommend installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

