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 charlieviettq/awesome-agent-skill --skill ecom-conversationalgit clone --depth 1 https://github.com/charlieviettq/awesome-agent-skillWrote 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/charlieviettq/awesome-agent-skill/ecom-conversational)<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/ecom-conversational"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/ecom-conversational/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/charlieviettq/awesome-agent-skill/ecom-conversational"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/ecom-conversational.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 | $0.00096 | $0.01130 |
| Opus 5 | $0.00048 | $0.00565 |
| Sonnet 5 | $0.00019 | $0.00226 |
| Haiku 4.5 | $0.00010 | $0.00113 |
Grade A, and why
"ecom-conversational" 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 9d 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.
This is a copy
97% identical to ecom-conversational — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conversational Commerce
Framework
IRON LAW: Conversation First, Commerce Second
Conversational commerce works because it meets customers WHERE THEY
ALREADY ARE (messaging apps). Forcing a sales pitch into a chat channel
kills trust. The conversation must provide genuine value (answering questions,
solving problems) BEFORE introducing products or purchases.
The sequence: Help → Trust → Recommend → Convert
Platform Comparison (Asia-Pacific Focus)
| Platform | Users (Taiwan) | Commerce Features | Best For |
|---|---|---|---|
| LINE | 21M+ (95% penetration) | LINE Shopping, Rich Menu, LIFF, payment | Taiwan, Japan, Thailand primary channel |
| Instagram DM | ~10M | Shop tags, quick replies, product stickers | Visual products, younger demographic |
| Facebook Messenger | ~18M | Shops integration, automated responses | Broad reach, older demographic |
| Limited in Taiwan | Catalog, cart, payment (select markets) | SEA, India, Brazil | |
| ~1M (Taiwan) | Mini Programs, WeChat Pay | China-connected businesses |
Conversation Flow Design
1. Entry Points — How customers start the conversation
- QR code in store, ad click-to-message, website chat widget, social media link
2. Welcome Flow — First 3 messages
- Greet warmly, set expectations, offer navigation options
- Rich menu (LINE) or quick reply buttons — don't ask open-ended questions early
3. Product Discovery — Help them find what they need
- Guided questions: "What are you looking for?" → category → product
- Product cards with image, price, and "Buy" button
- AI-powered recommendations based on conversation context
4. Purchase Flow — Minimize friction
- In-chat checkout where possible (LINE Pay, in-app payment)
- If redirecting to website, deep-link to the specific product (not homepage)
- Order confirmation message with tracking
5. Post-Purchase — Retain and upsell
- Shipping updates via message
- Follow-up: "How's the product?" (7 days after delivery)
- Personalized recommendations based on purchase history
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 110 lines · 96 tokens per session scan A 1485b9d9fe74
"ecom-conversational" is a skill published in the GitHub repository charlieviettq/awesome-agent-skill (26 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 1,130 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to ecom-conversational, differing in 8 lines, and is treated as a copy.
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