adhd-output-style
This skill should be used when the user asks for "ADHD output", "fewer output tokens", "short…
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
$ npx -y skills add fcakyon/claude-codex-settings --skill connect-recommend --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/connect-recommendContext preview
The summary Claude sees to decide when to auto-load this skill.
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
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. license: MIT
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.
**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:
**Never end with passive text**. Every stopping point must end with a prompt to the user offering concrete next actions.
**Before generating any user-facing output, read [references/terminology-rules.md](https://docs.stripe.com/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.
Keep responses concise. The user is making decisions, not reading documentation.
**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.
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.
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:
**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:
**1c. Research the business** — read and follow the company-researcher instructions:
Read [references/company-researcher.md](https://docs.stripe.com/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](https://docs.stripe.com/references/decision-matrix.md) and map the findings to a recommended configuration. Then determine pre-fill behavior per dimension:
**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*
Battle-tested Claude Code, OpenAI Codex, Cursor configs, plugins, hooks and agents with Kimi, MiniMax and GLM API support.
Repo: fcakyon/claude-codex-settings
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