chatbot-flow-design

chatbot-flow-design is a skill for Claude Code from rampstackco/claude-skills. It costs 157 tokens per session (4,164 once invoked), scanned A, original, MIT.

A design guide for planning how website chatbots and AI agents understand requests, choose replies, handle uncertainty, and pass conversations to people.

In plain words
What is it for?
Defining user intents, branching conversation paths, fallback replies, human escalation, and conversation measurement.
Why use it?
It helps avoid rigid scripts that fail on unexpected wording and open-ended bots that make up answers.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the rampstack-skills plugin — 103 skills shipped together

Good fit Defining user intents, branching conversation paths, fallback replies, human escalation, and conversation measurement.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rampstackco/claude-skills/chatbot-flow-design
Install

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.

Any agent
npx skills add rampstackco/claude-skills --skill chatbot-flow-design
Clone the repo
git clone --depth 1 https://github.com/rampstackco/claude-skills

Made for: Claude Code.

Or install rampstack-skills, the plugin that ships this one along with the rest of its 103 skills.

Wrote 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.

agentmods badge for chatbot-flow-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/rampstackco/claude-skills/chatbot-flow-design.svg)](https://agentmods.dev/skills/rampstackco/claude-skills/chatbot-flow-design)
Your own site
<a href="https://agentmods.dev/skills/rampstackco/claude-skills/chatbot-flow-design"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/chatbot-flow-design.svg" alt="Measured on agentmods" height="20"></a>
Per session 157 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,164 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
SkillSpector: 1 finding, up to low

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • low Excessive Agency · line 220
    Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.
    Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00157 $0.04164
Opus 5 $0.00078 $0.02082
Sonnet 5 $0.00031 $0.00833
Haiku 4.5 $0.00016 $0.00416

Measured 8d ago against content hash 57a6f2a29ba1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

chatbot-flow-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 8d 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.

skills/chatbot-flow-design/SKILL.md · 267 lines

How it starts

The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Chatbot Flow Design

A senior growth practitioner's playbook for designing conversational flows for website chatbots and AI agents. Intent recognition architecture, branching logic, fallback handling, escalation to human, conversation analytics. The discipline of building a bot that knows what it knows and routes appropriately when it does not.

Most chatbots on the web fail in one of two ways. Scripted bots break the moment a user phrases something the script did not anticipate; the user gets pushed through a decision tree that does not fit their situation. LLM-powered bots without structure hallucinate; they confidently answer questions about pricing, policy, or capabilities and frequently make up answers, creating support burden and trust damage.

The chatbots that work do something different. They have an intent architecture that defines what the bot can and cannot handle. They ground their responses in a knowledge base so they do not invent facts. They have explicit fallback paths for unclear or out-of-scope intents. They escalate to humans cleanly when the bot's job is done. The audience trusts the bot because the bot is honest about its scope.

The voice is the senior growth practitioner who has watched chatbots become trusted brand surfaces and watched them become liability risks. Practical, opinionated about the architecture that distinguishes the two outcomes, willing to call out when a chatbot is the wrong investment or when an existing chatbot needs to be redesigned rather than tuned.

When to use this skill: scoping a chatbot for the first time, auditing a chatbot that hallucinates or fails edge cases, designing the intent architecture and fallback patterns, or deciding when to escalate to humans.


What this skill covers

This skill spans chatbot design as conversational flow architecture, not chatbot implementation. The growth-tooling distinctions:

  • ai-content-collaboration covers AI in content workflows. This skill covers AI in customer-facing conversations.
  • integration-orchestrator covers cross-team coordination for chatbot deployment. This skill is the conversational design itself.
  • pm-spec-writing covers the spec for engineers building the bot. This skill is about WHAT the conversation should be; pm-spec-writing is about communicating it.
  • discovery-research-synthesis covers customer research that informs intent architecture. Input to this skill, not part of it.
  • chatbot-flow-design (this skill) is intent architecture, knowledge-base grounding, fallback patterns, and escalation discipline.

Read the full file on GitHub · 267 lines

Changes

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.

  1. 8d ago First seen · 267 lines · 157 tokens per session scan A 57a6f2a29ba1

Subscribe to this mod's changes

chatbot-flow-design is a skill published in the GitHub repository rampstackco/claude-skills (826 stars, last pushed 10d ago), licensed MIT. It adds 157 tokens to every session and 4,164 once invoked, about $0.0008 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.

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