Agent skill

Connect Recommend

by fossasia in fossasia/eventyay

A skill your agent uses when the user asks about Stripe Connect configuration, charge patterns, Dashboard access, or how to get started with Connect, is building a marketplace, platform…

Apache-2.0Auto-check: warningsBackend & APIs

Install Connect Recommend

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add fossasia/eventyay --skill connect-recommend -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install fossasia/eventyay connect-recommend --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/fossasia/eventyay.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/connect-recommend .claude/skills/connect-recommend && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
connect-recommend
GitHub stars
1.7k
Used in
1 other repo
Token cost
~5.9k tokens
SKILL.md length
2,578 words
Files
9 (incl. references)
Skills in repo
21
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when the user asks about Stripe Connect configuration, charge patterns, Dashboard access, or how to get started with Connect, is building a marketplace, platform…

  • Works in 7 steps: Show progress → Learn about the business (ALWAYS runs… → Auto-detect project context → …
  • The user asks about Stripe Connect configuration
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Charge patterns

What it does

Connect Recommend is an agent skill from fossasia/eventyay. 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…

Its SKILL.md is about 5.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/account-types.md`, `references/charge-patterns.md` and `references/company-researcher.md`).

It sits in Backend & APIs. It works with Stripe. The repository describes itself as: Open Source Event Management, Ticketing and Checkins, Talks and Schedules, Video and Interpretations, Badges, Exhibitions and more https://eventyay.com. The licence is Apache-2.0.

When your agent uses it

  • The user asks about Stripe Connect configuration
  • Charge patterns
  • Dashboard access
  • How to get started with Connect

Example prompts

  • “/connect-recommend”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Show progress
  2. Learn about the business (ALWAYS runs first)
  3. Auto-detect project context
  4. Ask remaining discovery questions
  5. Generate recommendation
  6. Generate recommendation plan
  7. Explain what belongs in code vs Dashboard, and next actions

What it can do on your machine

Read from SKILL.md and the folder at commit 26ab310. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.stripe.com
    • stripe.com
    • dashboard.stripe.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Connect Recommend loads about 5.9k tokens when it runs, and up to ~41k if it reads all its reference files. Until then it costs about 206 tokens; SKILL.md has 2,578 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~206
When it runs · the whole SKILL.md, loaded when a task matches
~5.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~41k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: warnings

The automated check found patterns that need a careful read before installing.

  • WarningTells the agent its actions are pre-authorized / not to stop for confirmationSKILL.md:26
    **Auto-act on low-cost actions**. Never ask permission for:

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from fossasia/eventyay at commit 26ab310, republished under its Apache-2.0 licence (© fossasia). 2,578 words, ~5,925 tokens.

Download SKILL.mdSave it as .claude/skills/connect-recommend/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
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 pre-fill 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]                  │
  └──────────────────────────┴────────────────────────────────┘

Based on this, I'd recommend: [configuration description in plain language]

I'll proceed with this unless you'd like to correct anything.

For MEDIUM confidence items, append: “I’m also assuming [X] — sound right?”

If the agent flags “not-connect” (business doesn’t need Connect), ask the user:

Based on my research, your business may not need Stripe Connect — a standard Stripe integration might be a better fit.

Options:

  • “Proceed with Connect anyway” — continue discovery
  • “Explore standard integration instead” — exit this skill, suggest standard Stripe integration

Update the checklist:

  [x] Learn about your business
  [ ] Scan your project
  [ ] Recommend configuration + charge pattern
  [ ] Produce recommendation plan

1f. Validate fee economics (ALWAYS runs, even on auto-filled values)

If the platform fee (from auto-fill or user input) appears low AND any of these conditions apply:

  • Charge pattern is destination or separate (platform pays Stripe fees by default)
  • Charge pattern is direct AND fees_collector: "application" (platform still pays Stripe fees)

Then:

  • ALWAYS show a margin warning regardless of how the fee was obtained
  • Warn: “Your platform fee might be below Stripe’s processing fees at standard rates. Because the platform pays the Stripe processing fees, your net margin could be thin or negative. Check stripe.com/pricing for your region’s rates.”
  • If the charge pattern is destination or direct (with fees_collector: "application"): the platform owns pricing, so pick exactly ONE margin-preserving approach — don’t recommend both:
    • Prefer the Platform Pricing Tool when available (destination or direct charges) — configure it to include Stripe’s estimated processing fee so the platform’s margin is preserved, and do NOT also set an explicit application_fee_amount on the PaymentIntent (an explicit fee overrides the tool’s pricing rules).
    • Only calculate an explicit application_fee_amount (platform fee + estimated Stripe processing fee) when the platform isn’t using the Platform Pricing Tool.
  • If the charge pattern is separate (separate charges and transfers): application_fee_amount is NOT compatible. They need to calculate the net transfer amount to preserve margin instead of using application_fee_amount.
  • Recommend monitoring the margin report in the Stripe Dashboard

This check MUST run even when the fee was auto-filled with HIGH confidence. The user needs to understand the fee economics before proceeding.

Step 2 — Auto-detect project context

Run this AFTER Step 1 (or in parallel if the user said “scan my codebase”). Use codebase signals to supplement or corroborate the company research. Don’t ask before scanning — just scan.

  1. Existing Connect config: Check for connect-recommend-plan.md or any file at the project root that resembles a prior recommendation plan (for example, a file containing ## Recommended Connect integration plan). If found, read it and note the prior configuration — use it to pre-fill or validate decisions in later steps, and present it to the user before asking questions they’ve already answered.
  2. Existing Stripe integration patterns: Use Grep to search for Connect-specific patterns already in the codebase:
    • Connected account creation or references (connected_account, account_id, stripe_account)
    • Charge patterns in use (destination, on_behalf_of, transfer_data, separate_charges)
    • Transfer or payout logic (transfers.create, payouts.create)
    • Webhook handlers for Connect events (account.updated, capability, payout)
    • Existing application_fee_amount usage

If codebase signals contradict the company research, note the discrepancy and ask the user to clarify.

Present findings briefly (don’t repeat what Step 1 already covered):

Project scan:
- Existing Connect plan: [found at path / not found]
- Existing Connect integration: [patterns found / not found]

If a prior plan was found, ask the user:

I found an existing Connect recommendation plan at [path].

Options:

  • “Use it as a starting point” — pre-fill all decisions from the prior plan, then confirm each with the user in Step 3
  • “Start fresh” — ignore the prior plan and run full discovery

Update the checklist:

  [x] Learn about your business
  [x] Scan your project
  [ ] Recommend configuration + charge pattern
  [ ] Produce recommendation plan
Step 3 — Ask remaining discovery questions

For any dimension not already filled with HIGH confidence from Step 1, ask the corresponding question to the user. Skip dimensions that were auto-filled or explicitly confirmed.

Read references/discovery-questions.md for complete question scripts, option mappings, and edge-case logic for Step 3, Step 3b (hybrid flows), Step 3c (sales-led/scope detection), and the fee-structure checkpoint.

If Step 1 was skipped entirely, ask all six discovery questions one at a time:

  • Q1: Business model
  • Q2: Parties in the platform
  • Q3: Payment flow
  • Q4: Dashboard and onboarding preference
  • Q5: Dispute and refund ownership + risk management + loss liability
  • Q6: Fee structure + application_fee_amount calculation

Critical guardrails (must enforce in all discovery paths):

  • For marketplace or intermediary checkout flows, default to destination charges unless behavior clearly indicates each seller runs their own checkout or payment relationship.
  • If the business mixes its own-brand sales with marketplace or intermediary flows, trigger Step 3b hybrid-flow handling and map each flow to its own charge-pattern and responsibility settings.
  • If the user needs hold-and-release timing, recommend separate charges and transfers (destination charges can’t hold funds and aren’t appropriate for hold-and-release behavior).
  • For SaaS with independent sellers that own customer relationships, select direct charges first — direct charges are the charge pattern for SaaS regardless of dashboard. Then choose the dashboard from the connected accounts’ operational needs: self-serve or low-operations sellers → Express dashboard (dashboard: "express"), paired with Stripe-managed pricing and Stripe-managed negative balance liability (SES) as the low-operations default, or platform-managed pricing with Stripe-managed negative balance liability (PES) when the platform wants pricing control. Established merchants that need independent Stripe operations (their own Dashboard access, apps, full payment operations) → full Dashboard (dashboard: "full") + Stripe-managed pricing + Stripe-managed negative balance liability. When recommending SES or PES: (1) include a concise public-preview disclosure (these Express + Stripe-managed-negative-balance-liability configurations for direct charges are in public preview), (2) state that they require the current Connect preview API version and link to the preview changelog, (3) recommend enabling Radar for Platforms alongside Managed Risk, and (4) confirm during discovery whether the platform is onboarding new accounts or trying to migrate existing accounts — SES/PES only work for newly onboarded accounts and the dashboard choice is permanent per account (see the discovery question in references/discovery-questions.md).
  • If the user asks “what account type should I use?”, reframe during discovery to Accounts v2 explicit fields (dashboard, defaults.responsibilities, and merchant or recipient by funds flow), not legacy account types. Read references/account-types.md for the full v2 configuration reference.
  • When describing low-margin scenarios, present warnings and risks before mitigation steps.
  • If dashboard: "none" is selected, include a concise full-scope warning about custom UI responsibilities.
  • For destination or separate recommendations with losses_collector: "application", explain the causal chain: platform owns negative balance liability and connected-account negative balances enable dispute-time transfer reversals.
  • Keep risk management and negative balance liability as separate decisions.
  • Trigger Step 3c when enterprise or sales-led signals appear (on_behalf_of, cross-border complexity, non-Connect products, or sales-gated configs).

Fee structure checkpoint before Step 4:

  1. Confirm fee type and fee amount
  2. Confirm how application_fee_amount is calculated
  3. Confirm whether a margin warning is required
  4. Include stripe.com/pricing link in output context
Show full SKILL.md (982 more words)Show less
Step 4 — Generate recommendation

Read the decision matrix at references/decision-matrix.md and apply it to the user’s answers. For charge pattern details, read references/charge-patterns.md.

Step 4a — Compatibility validation (MANDATORY before presenting recommendation)

Read references/compatibility-matrix.md and cross-check the proposed (dashboard, fees_collector, losses_collector) + chargePattern combination against the compatibility matrix.

  1. BLOCKED combination? Do NOT present it. Output a visible BLOCKED warning with ALL of these:

    • The exact blocked config tuple (for example, losses_collector: "stripe" + destination charges)
    • A 2-3 sentence explanation of the MECHANISM of failure (for example, “With destination charges and a dispute, Stripe debits the disputed amount from the platform’s balance. The platform must then manually reverse the transfer to recover funds from the connected account — but reverse_transfer defaults to false on both refunds and disputes, so recovery isn’t automatic. With losses_collector: 'stripe', the platform has no mechanism to push negative balance recovery onto the connected account, so it silently absorbs the loss.”)
    • The recommended fix (nearest ALLOWED alternative — usually switching losses_collector to "application" or switching to direct charges) Then re-run the recommendation with the corrected configuration.
  2. CAUTION combination? Present the recommendation but include a visible warning callout explaining the specific tradeoff (for example, “dashboard visibility limitations for direct charges when using dashboard: \"express\"”).

  3. Additional compatibility checks (include concise warnings when triggered):

    • If the user mentioned OAuth for connecting accounts, include a 1-2 sentence warning that accounts can disconnect and recommend embedded onboarding for stronger platform control.
    • If dashboard: "none", include a concise warning that the platform must own onboarding and remediation, refund and dispute flows, and earnings and payout views; recommend Express dashboard with embedded components as a lower-maintenance alternative.
    • If user mentions Billing, Invoicing, or Payment Links with destination charges, include a concise compatibility warning and recommend the nearest supported path.
    • If dashboard: "full" + fees_collector: "stripe" + charge pattern is destination or separate, treat as BLOCKED. Do NOT present this configuration. Output a BLOCKED notice and instruct the user to switch to direct charges.
    • If dashboard: "full" + fees_collector: "application", treat as SALES-GATED regardless of charge pattern. Do NOT recommend for self-serve paths. Redirect to Stripe sales.
    • If dashboard: "express" + fees_collector: "stripe" + losses_collector: "stripe" (SES) with direct charges, this is a supported public-preview path — do NOT block it. Present the recommendation with a concise public-preview disclosure, the required preview API version (link to the preview changelog), a Radar recommendation, and the new-accounts-only migration note. Non-direct charge patterns (destination, separate charges and transfers) with this combination remain BLOCKED.
    • If dashboard: "express" + fees_collector: "application" + losses_collector: "stripe" (PES) with direct charges, this is also a supported public-preview path — do NOT block it. Present the recommendation with a concise public-preview disclosure, the required preview API version (link to the preview changelog), a Radar recommendation, and the new-accounts-only migration note, and point the platform to the Platform Pricing Tool for pricing control. Non-direct charge patterns with this combination remain BLOCKED.
    • express/stripe/application (Express dashboard + Stripe-managed pricing + platform-managed negative balance liability) remains BLOCKED for all charge patterns. Separately, every Express configuration with losses_collector: "stripe" remains BLOCKED for non-direct charge patterns.
  4. Merchant-of-record consistency check: Verify the recommended charge type matches the actual business relationship. Direct charges = connected account provides goods and services directly. Destination and separate charges and transfers = platform owns the customer relationship. Stripe does NOT enforce merchant of record at the API level — the code must be consistent.

  5. Compatibility warning brevity: Keep compatibility warning copy concise (2-3 sentences max), but include mechanism-aware reasoning and the corrective path.

Step 4b — Recommend embedded components

Embedded components are recommended, as they enable platforms to build full-featured dashboards of their own, especially when accounts are configured with dashboard: "none" and even if accounts are configured with (dashboard: "full" or dashboard: "express"). Select components based on user needs:

Baseline (always include):

  • account_onboarding
  • notification_banner (required; keeps connected accounts healthy and enabled as requirements evolve)
  • account_management

Common additions:

  • Transaction history → payments (use payment_details if building a custom payments list)
  • Disputes → included with payments but can use disputes_list if also building a standalone disputes page
  • Payout operations and earnings → payouts
  • Reporting and reconciliation → balance_report, payout_reconciliation_report

Charge-pattern compatibility caveats:

  • Destination charges: payment and dispute views show reduced detail.
  • Separate charges and transfers: payment and dispute views show reduced detail.
  • Direct: payment and dispute views operate with full fidelity.

Out of scope component families:

  • Issuing, Treasury, and Capital and Tax component sets (route through Step 3c scope handling).

Be prepared to output a list of embedded components in the next step.

Update the checklist:

  [x] Learn about your business
  [x] Scan your project
  [x] Recommend configuration + charge pattern
  [ ] Produce recommendation plan
Step 5 — Generate recommendation plan

Read references/recommendation-template.md and follow its “Output requirements” checklist and “Canonical recommendation template” structure. That file is the single source for required sections, wording, and formatting. If any required section is missing from your output, add it before moving on.

Then ask the user:

Does this recommendation look right?

Options (max 4 — options hard limit):

  • “Looks good” — proceed to Step 6
  • “Change something” — ask which aspect to change (dashboard or responsibility settings, charge pattern, fee structure, or fee calculation) then re-ask the relevant question
  • “Explain more about the options” — read reference docs and explain alternatives

Generate the final recommendation plan. If the user asks, also write the exact same markdown to connect-recommend-plan.md at the project root.

When they accept the plan, update the checklist:

  [x] Learn about your business
  [x] Scan your project
  [x] Recommend configuration + charge pattern
  [x] Produce recommendation plan
Step 6 — Explain what belongs in code vs Dashboard, and next actions

Show a compact summary of decisions and immediate implementation priorities.

Briefly explain:

  • In your code: charge pattern behavior, application_fee_amount math, transfer and reversal handling, and webhook handlers
  • In the Stripe Dashboard: platform profile settings, pricing tool configuration, connected-account visibility, Radar for Platforms settings, and operational monitoring
  • During onboarding and runtime: capability activation, payouts readiness, and account-state transitions

IMPORTANT: Always end with AskUserQuestion. Never end with passive text.

Use AskUserQuestion:

What would you like to do next?

Options:

  • “Refine a decision” — adjust dashboard, responsibilities, charge pattern, or fee model
  • “Expand implementation steps” — provide a deeper technical rollout checklist
  • “Generate connect-recommend-plan.md and build” — write the plan to a markdown file and handoff to a coding agent

© fossasia, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references) in .agents/skills/connect-recommend of fossasia/eventyay.

  • SKILL.md
  • references/account-types.md
  • references/charge-patterns.md
  • references/company-researcher.md
  • references/compatibility-matrix.md
  • references/decision-matrix.md
  • references/discovery-questions.md
  • references/recommendation-template.md
  • references/terminology-rules.md

Open the folder on GitHubat commit 26ab310

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in fossasia/eventyay, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Connect Recommend next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Connect Recommend compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Connect Recommend this skillfossasia/eventyay1.7k1 repos~5.9kAutomated safety check: WarnApache-2.0
Firecrawl Build Onboardingfirecrawl/firecrawl190k1 repos~1.4kAutomated safety check: NotesISC
Dinero Currency Patternsdinerojs/dinero.js6.8k—~650Automated safety check: PassMIT
Stripe Best Practiceskanchengw/cnllm1752 repos~925Automated safety check: PassApache-2.0
Cashier Stripe Developmentluadotsh/lua3431 repos~1.2kAutomated safety check: PassMIT
EmulateUsefulSoftwareCo/executor4.1k—~2.2kAutomated safety check: NotesMIT

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  • Stripe Best Practices

    fossasia/eventyay

    Guides Stripe integration decisions across development and test environment planning (separate sandboxes vs the shared test mode sandbox), API selection (Checkout Sessions vs PaymentIntents)…

    1.7k GitHub starsUsed in 1 repo~1.7k tokens
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  • Repo Navigation

    fossasia/eventyay

    Repository layout and where to find code. An agent skill from fossasia/eventyay.

    1.7k GitHub stars~752 tokensUpdated today
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Questions about Connect Recommend

What does Connect Recommend do?

A skill your agent uses when the user asks about Stripe Connect configuration, charge patterns, Dashboard access, or how to get started with Connect, is building a marketplace, platform…. Connect Recommend is an agent skill from fossasia/eventyay.

When should I use Connect Recommend?

Connect Recommend fits situations like: the user asks about Stripe Connect configuration; charge patterns; dashboard access; how to get started with Connect.

How do I install Connect Recommend in Claude Code?

Run `npx skills add fossasia/eventyay --skill connect-recommend -a claude-code`. Or copy the skill folder (.agents/skills/connect-recommend in fossasia/eventyay) into .claude/skills/connect-recommend in your project. Claude Code loads it when a task matches its description.

How do I install Connect Recommend in Codex?

Run `npx skills add fossasia/eventyay --skill connect-recommend -a codex`. Or copy the skill folder (.agents/skills/connect-recommend in fossasia/eventyay) into .agents/skills/connect-recommend in your project. Codex loads it when a task matches its description.

Can I use Connect Recommend in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add fossasia/eventyay --skill connect-recommend -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/connect-recommend, .gemini/skills/connect-recommend, .github/skills/connect-recommend and .opencode/skills/connect-recommend in your project.

What does Connect Recommend need to run?

SKILL.md names no scripts, command-line tools or credentials: Connect Recommend is instructions for the agent only.

Does Connect Recommend access the network?

SKILL.md names 3 domains. As links in the text: docs.stripe.com, stripe.com and dashboard.stripe.com. This is read from the text; nothing was executed.

Is Connect Recommend safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): tells the agent its actions are pre-authorized / not to stop for confirmation. Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Connect Recommend use?

Connect Recommend is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Connect Recommend use?

About 5.9k tokens (SKILL.md is roughly 24k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 35k tokens, read only when the agent opens those files.

What are the alternatives to Connect Recommend?

Skills that share tags, products or a category with Connect Recommend: Firecrawl Build Onboarding (firecrawl/firecrawl, 190k stars), Dinero Currency Patterns (dinerojs/dinero.js, 6.8k stars), Stripe Best Practices (kanchengw/cnllm, 175 stars) and Cashier Stripe Development (luadotsh/lua, 343 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Connect Recommend?

fossasia (a GitHub organization) maintains it in fossasia/eventyay, which has 1,702 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on October 9, 2026.

Source: fossasia/eventyay on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.