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 cs-chatbot-designgit 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/cs-chatbot-design)<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/cs-chatbot-design"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/cs-chatbot-design/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/cs-chatbot-design"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/cs-chatbot-design.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 | $0.00083 | $0.01175 |
| Opus 5 | $0.00042 | $0.00588 |
| Sonnet 5 | $0.00017 | $0.00235 |
| Haiku 4.5 | $0.00008 | $0.00118 |
Grade A, and why
"cs-chatbot-design" 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
94% identical to cs-chatbot-design — 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chatbot Design
Framework
IRON LAW: Intent First, Response Second
A chatbot must UNDERSTAND what the user wants (intent) before crafting
a response. Building response templates without intent classification
produces a keyword-matching FAQ, not a chatbot.
Flow: User message → Intent classification → Slot extraction → Response
Core NLU Pipeline
| Stage | What It Does | Example |
|---|---|---|
| Intent Classification | Identify what the user wants to do | "What time do you close?" → intent: check_hours |
| Entity/Slot Extraction | Extract key information from the message | "Book a table for 4 on Friday" → slots: {party_size: 4, date: Friday} |
| Dialogue Management | Decide the next action (ask for missing info, confirm, execute) | Missing slot time → ask "What time would you like?" |
| Response Generation | Produce the reply | "I've booked a table for 4 on Friday at 7pm. See you then!" |
Intent Design
- Start with 10-15 core intents covering 80% of user queries
- Each intent needs 10-20 training examples (varied phrasings)
- Include a
fallbackintent for unrecognized inputs - Group related intents:
order_status,order_cancel,order_modifyunder "Order Management"
Dialogue Flow Patterns
| Pattern | When to Use | Example |
|---|---|---|
| Single-turn | Simple Q&A, no context needed | "What are your hours?" → respond immediately |
| Multi-turn (slot filling) | Need multiple pieces of info | "Book a table" → ask party size → ask date → ask time → confirm |
| Branching | Different paths based on user's answer | "Do you have an account?" → Yes: login flow / No: registration flow |
| Confirmation | Before executing actions | "I'll cancel order #12345. Is that correct?" |
| Handoff | Bot can't handle the request | "Let me connect you with a human agent" |
Response Design Principles
- Acknowledge first: "Got it, you want to check your order status."
- Be concise: Answer the question, then stop. Don't add unnecessary information.
- Offer next steps: "Is there anything else I can help with?" or suggest related actions.
- Use quick replies/buttons: Reduce typing, guide the conversation.
- Personality: Define a consistent tone (friendly, professional, casual) and stick to it.
What ships with it
2 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 · 105 lines · 83 tokens per session scan A 8a3476e5cd94
"cs-chatbot-design" is a skill published in the GitHub repository charlieviettq/awesome-agent-skill (26 stars, last pushed 1mo ago), licensed MIT. It adds 83 tokens to every session and 1,175 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to cs-chatbot-design, differing in 8 lines, and is treated as a copy.
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