ai-smooth-talker: Instructions file for Claude Code

CLAUDE.md

ai-smooth-talker CLAUDE.md is an instructions file for Claude Code from calderbuild/ai-smooth-talker. It costs 2,349 tokens per session, scanned A, original, MIT.

Project instructions for a React web chat assistant that suggests tactful replies and stores conversations through external services.

In plain words
What is it for?
They help maintain the chat simulator, AI customer-service window, administration and history pages, 3D homepage section, and related helper utilities.
Why use it?
They document the app’s architecture, APIs, storage, pages, and components so a coding agent can work within its existing design.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md; mentions Claude Code.

This is calderbuild/ai-smooth-talker's own configuration. It tells Claude Code how to work on ai-smooth-talker itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-smooth-talker configures →

Reuse

Borrowing it

Nothing to install: this file belongs to calderbuild/ai-smooth-talker. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/calderbuild/ai-smooth-talker/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/calderbuild/ai-smooth-talker

Made for: Claude Code.

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README.md
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Per session 2,349 This file is loaded in full into every session.
When invoked 2,349 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.02349 $0.02349
Opus 5 $0.01175 $0.01175
Sonnet 5 $0.00470 $0.00470
Haiku 4.5 $0.00235 $0.00235

Measured 9d ago against content hash 10e6a7976192, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

ai-smooth-talker CLAUDE.md 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.

CLAUDE.md · 210 lines

How it starts

The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

项目概述

这是一个基于 React + Trickle 平台的 AI 聊天助手 Web 应用,专注于提供智能化的高情商回复建议。项目使用纯前端架构(无构建系统),通过 CDN 加载 React、Babel 和 TailwindCSS,依赖 Trickle 平台的数据存储和 SiliconFlow API 的 AI 能力。

核心架构

技术栈

  • 前端框架: React 18 (UMD 版本,通过 CDN 加载)
  • UI 样式: TailwindCSS (CDN) + CSS 变量系统
  • 图标: Lucide Icons
  • 3D 组件: Spline Viewer
  • AI 服务: SiliconFlow API (Qwen/Qwen2.5-72B-Instruct 模型)
  • 数据存储: Trickle 平台对象存储 API
  • 代理服务: Trickle Proxy API (https://proxy-api.trickle-app.host)

项目结构

EP_Agent/
├── index.html          # 主页面入口
├── admin.html          # 管理后台
├── history.html        # 聊天历史页面
├── app.js              # 主应用入口
├── admin-app.js        # 管理后台入口
├── history-app.js      # 历史记录入口
├── components/         # React 组件库
│   ├── ChatSimulator.js      # 核心聊天模拟器
│   ├── AICustomerService.js  # AI 客服窗口
│   ├── HeroSection.js        # 首页英雄区(含 3D 组件)
│   ├── SuccessStories.js     # 成功案例展示
│   ├── Admin*.js             # 管理后台组件
│   └── ...
├── utils/              # 工具函数
│   ├── chatHelper.js         # AI 回复生成、聊天记录存储
│   ├── customerService.js    # 客服 AI 对话逻辑
│   └── adminHelper.js        # 管理统计数据处理
└── trickle/
    ├── notes/          # 项目文档和改进记录
    ├── rules/          # 设计规范(色彩一致性等)
    └── assets/         # 静态资源配置(JSON 数据)

数据流

  1. 用户输入ChatSimulator 组件
  2. AI 请求chatHelper.js:generateReplies() → SiliconFlow API (通过 Trickle Proxy)
  3. 回复生成 → 解析 JSON 响应 → 展示多种回复建议
  4. 用户选择 → 保存至 Trickle 数据库 (chat_history 对象)
  5. 管理查看adminHelper.js 读取聊天记录 → 统计分析

关键依赖和 API

Trickle 平台 API

所有数据存储操作都通过 Trickle 平台的全局方法:

  • trickleCreateObject(type, data): 创建对象(如聊天记录)
  • trickleListObjects(type, limit, reverse): 查询对象列表
  • 数据类型: chat_history (存储用户输入、AI 建议、反馈)

SiliconFlow AI API

  • 端点: https://api.siliconflow.cn/v1/chat/completions
  • 模型: Qwen/Qwen2.5-72B-Instruct (中文优化)
  • API Key: 存储在 utils/chatHelper.js:2 (生产环境应移至环境变量)
  • 代理: 所有请求通过 https://proxy-api.trickle-app.host 转发
  • 降级策略: API 失败时使用 invokeAIAgent() (Trickle 内置 AI)

Read the full file on GitHub · 210 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. 9d ago First seen · 210 lines · 2,349 tokens per session scan A 10e6a7976192

Subscribe to this mod's changes

ai-smooth-talker CLAUDE.md is an instructions file published in the GitHub repository calderbuild/ai-smooth-talker (5 stars, last pushed 10mo ago), licensed MIT. It adds 2,349 tokens to every session, about $0.0117 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 2026-08-31.

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