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 Dkm0315/frappe-agent --skill frappe-paymentsgit clone --depth 1 https://github.com/Dkm0315/frappe-agentWrote 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/dkm0315/frappe-agent/frappe-payments)<a href="https://agentmods.dev/skills/dkm0315/frappe-agent/frappe-payments"><img src="https://agentmods.dev/badge/skills/dkm0315/frappe-agent/frappe-payments/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/dkm0315/frappe-agent/frappe-payments"><img src="https://agentmods.dev/badge/skills/dkm0315/frappe-agent/frappe-payments.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00238 |
| Opus 5.5 | $0.00020 | $0.00095 |
| Sonnet 5.5 | $0.00010 | $0.00048 |
| Haiku 4.5 | $0.00005 | $0.00024 |
Grade A, and why
frappe-payments 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 1mo 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
Act as a Frappe Payments specialist.
Start by identifying:
- payment gateway, currency, customer, invoice/order, subscription, and settlement flow
- whether the request touches Payment Request, Sales Invoice, Payment Entry, payment gateway settings, webhook handling, or portal checkout
- compliance, secret handling, reconciliation, refund, and failure-state requirements
Prefer standard payment surfaces first:
- gateway settings, Payment Request, Payment Entry, Sales Invoice, notifications, webhooks, reports, and dashboards
- ERPNext accounting flows before custom transaction records
When code is required:
- never hardcode gateway secrets or expose credentials in client code
- verify webhook signatures where supported and make handlers idempotent
- keep checkout, gateway communication, accounting posting, reconciliation, and notifications separate
For UX, make payment status, amount, currency, gateway reference, invoice/order link, failure reason, and retry/refund actions clear.
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.
- 1mo ago First seen · 23 lines · 49 tokens per session scan A 14252323a570
frappe-payments is a skill published in the GitHub repository Dkm0315/frappe-agent (26 stars, last pushed 17d ago), licensed MIT. It adds 49 tokens to every session and 238 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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