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 coleschaffer/copywritingskills-rmbc --skill thank-you-pagegit clone --depth 1 https://github.com/coleschaffer/copywritingskills-rmbcWrote 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/coleschaffer/copywritingskills-rmbc/thank-you-page)<a href="https://agentmods.dev/skills/coleschaffer/copywritingskills-rmbc/thank-you-page"><img src="https://agentmods.dev/badge/skills/coleschaffer/copywritingskills-rmbc/thank-you-page/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/coleschaffer/copywritingskills-rmbc/thank-you-page"><img src="https://agentmods.dev/badge/skills/coleschaffer/copywritingskills-rmbc/thank-you-page.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 | $0.00037 | $0.01591 |
| Opus 5 | $0.00018 | $0.00796 |
| Sonnet 5 | $0.00007 | $0.00318 |
| Haiku 4.5 | $0.00004 | $0.00159 |
Grade A, and why
thank-you-page 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.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
thank-you-page
Purpose
Generate complete thank you / order confirmation page copy structured around RMBC principles. The thank you page is the most underused conversion asset in DTC funnels — the customer just bought, trust is at its absolute peak, and they're actively looking for confirmation they made the right decision. This page must do three things: confirm their purchase, set expectations, and (optionally) present one more offer while the buying window is wide open. Structure: order confirmation → "what happens next" → surprise bonus → upsell offer → social share prompt.
Inputs
| Input | Required | Description |
|---|---|---|
product_purchased |
Yes | What the customer just bought — name, price, core promise |
target_audience |
Yes | Who the buyer is — demographics, pain points, desires |
delivery_details |
Yes | What happens next — shipping timeline, digital access instructions, onboarding steps |
upsell_product |
No | Optional next offer — name, price, how it complements the purchase |
Execution Protocol
Step 1 — Load Framework Context
Read rmbc-context/SKILL.md to load RMBC framework definitions. Thank you pages apply RMBC in post-purchase mode — Research validates what buyers need to hear after committing, Mechanism reinforces why their purchase decision was smart, Brief structures the page for both confirmation and conversion, Copy executes with warmth first, sell second.
Step 2 — Map Post-Purchase Psychology
The buyer is in a unique emotional state. Map the psychology driving this page:
- Validation hunger — They just spent money and need confirmation it was smart
- Peak trust — Payment is complete; they have nothing left to fear from you
- Consumption anxiety — "Did I make the right choice? Will this actually work for me?"
- Reciprocity window — You delivered on the sale; they feel inclined to give back (share, review, buy more)
- Attention spike — They're actively reading this page, not passively scrolling
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 · 164 lines · 37 tokens per session scan A 37116e4c9785
thank-you-page is a skill published in the GitHub repository coleschaffer/copywritingskills-rmbc (30 stars, last pushed 5mo ago), licensed MIT. It adds 37 tokens to every session and 1,591 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 2026-08-30.
Other skills, from other repositories
amazon-reviews-api-skill
This skill helps users automatically extract Amazon product reviews via the Amazon Reviews API. Agent should proactively apply this skill when users express needs like getting reviews for Amazon product with ASIN B07TS6R1SF, analyzing customer feedback for a specific Amazon item, getting ratings and comments for a…
amazon-competitor-analyzer
Scrapes Amazon product data from ASINs using browseract.com automation API and performs surgical competitive analysis. Compares specifications, pricing, review quality, and visual strategies to identify competitor moats and vulnerabilities.
asc-subscription-localization
Bulk-localize subscription, subscription-group, and in-app purchase display names across App Store locales using asc, including API 4.4.1 version-scoped v2 resources. Use when filling or updating subscription/IAP names and descriptions without App Store Connect UI work.
food-order
Reorder previous Foodora orders, preview cart contents, and track delivery ETA/status with ordercli. Use when the user wants to reorder food, check delivery status, or browse recent Foodora order history. Never confirm an order without explicit user approval.
product-description-generator
E-commerce product description generator for any platform. Generates optimized titles, bullet points, descriptions, and backend keywords using competitor research + keyword scoring + FABE copywriting. Two modes: (A) Create — generate listing from product specs with optional competitor analysis, (B) Optimize — improve…
amazon-price-tracker
Amazon price monitoring and competitive pricing intelligence. Real-time price tracking, Buy Box analysis, promotion detection, and dynamic pricing strategy optimization. Use when the user asks about price monitoring, competitor pricing, Buy Box tracking, or pricing strategy.