Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add appeeky/stripe-skills --skill dispute-refund-auditgit clone --depth 1 https://github.com/appeeky/stripe-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/appeeky/stripe-skills/dispute-refund-audit)<a href="https://agentmods.dev/skills/appeeky/stripe-skills/dispute-refund-audit"><img src="https://agentmods.dev/badge/skills/appeeky/stripe-skills/dispute-refund-audit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/appeeky/stripe-skills/dispute-refund-audit"><img src="https://agentmods.dev/badge/skills/appeeky/stripe-skills/dispute-refund-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.00338 |
| Opus 5 | $0.00024 | $0.00169 |
| Sonnet 5 | $0.00010 | $0.00068 |
| Haiku 4.5 | $0.00005 | $0.00034 |
Grade A, and why
dispute-refund-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Dispute & Refund Audit
Stripe MCP Setup
Requires Stripe MCP connected via OAuth or restricted key. Docs: https://docs.stripe.com/mcp
GetMcpToolswithserver: "user-Stripe"(orplugin-stripe-stripe) before any call- Prefer
stripe_api_search→stripe_api_details→stripe_api_readfor list/retrieve - Always paginate —
limit: 100, followhas_morewithstarting_after - Amounts are in cents unless noted
- Never expose secret keys in output
Workflow
GetDisputes— recent, paginateGetRefundsor failed/succeeded charges withrefunded: true- Group by reason, amount, status (
needs_response,lost,won)
Benchmarks
Dispute rate < 0.75% of charges (card network threshold).
Output Template
Disputes & Refunds ([period])
Disputes: [n] | $[amount] | Win rate: [%]
Refunds: [n] | $[amount]
Action items:
1. Respond to [n] needs_response before [date]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 41 lines · 49 tokens per session scan A 7b1a18779879
dispute-refund-audit is a skill published in the GitHub repository appeeky/stripe-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 338 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
stock-liquidity
Analyze stock liquidity using bid-ask spreads, volume profiles, order book depth, market impact estimates, and turnover ratios via Yahoo Finance data. Use this skill whenever the user asks about liquidity, trading costs, bid-ask spread, market depth, volume analysis, slippage, market impact, turnover ratio, or how…
company-valuation
Estimate the intrinsic value of a public company using DCF, relative (peer multiple) and sum-of-parts (SOTP) methods, then triangulate to an implied share price with upside/downside versus the current market price. Use this skill whenever the user asks: "what is AAPL worth", "valuation of NVDA", "fair value of TSLA"…
fintel-data
Query Fintel (fintel.io) institutional market intelligence via the REST API at https://api.fintel.io/v1 with FINTELAPIKEY (X-API-KEY header), or the official MCP server at https://mcp.fintel.io/mcp. Read-only data: short interest, borrow rate/fee and shares available to borrow, daily short volume, fails-to-deliver…
estimate-analysis
Deep-dive into analyst estimates and revision trends for any stock using Yahoo Finance data. Use when the user wants to understand analyst estimate direction, how EPS or revenue forecasts changed over time, compare estimate distributions, or analyze growth projections across periods. Triggers: "estimate analysis for…
earnings-preview
Generate a pre-earnings briefing for any stock using Yahoo Finance data. Use this skill whenever the user wants to prepare for an upcoming earnings report, understand what analysts expect, review a company's beat/miss track record, or get a quick overview before an earnings call. Triggers include: "earnings preview…
earnings-recap
Generate a post-earnings analysis for any stock using Yahoo Finance data. Use when the user wants to review what happened after earnings, understand beat/miss results, see stock reaction, or get an earnings recap. Triggers: "AAPL earnings recap", "how did TSLA earnings go", "MSFT earnings results", "did NVDA beat…