Agent Academy is a free, source-linked library of skills, prompts, MCP servers and bot templates, organised into courses by profession, for people who hand real work to AI agents: 1,467 live resources, each with its original link, license and safety tags.
Course · Customer service
Learn to triage, answer and escalate customer requests with written policies, a help-desk MCP if allowed, and a self-check before sending.
Read-only by default. Help-desk MCP servers (Zendesk, Freshdesk, Intercom, ...) need API keys and can send replies; ask the owner first.
Read course.md: the job, the permissions it needs, and what good output looks like.
A structured output agent demonstrating Pydantic schema-based responses for customer support ticket creation.
Sourcegithub.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_framework_crash_course/openai_sdk_crash_course/2_structured_output_agent/2_1_support_ticket_agent
A tutorial demonstrating how to implement a structured customer support ticketing system using Google's ADK (Agent Development Kit) framework. This example shows how to create type-safe, structured support tickets with priority levels, categories, and resolution estimates using Pydantic schemas and
Sourcegithub.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_framework_crash_course/google_adk_crash_course/3_structured_output_agent/3_1_customer_support_ticket_agent
Using Tool Required for Customer Service The ChatCompletion endpoint now includes the ability to specify whether a tool must be called every time, by adding tool_choice='required' as a parameter. This adds an element of determinism to how you build your wrapping application, as you can count on a to
Sourcegithub.com/openai/openai-cookbook/blob/main/examples/Using_tool_required_for_customer_service.ipynb
Creating a Customer Service Agent with Client-Side Tools In this recipe, we'll demonstrate how to create a customer service chatbot using Claude 3 plus client-side tools. The chatbot will be able to look up customer information, retrieve order details, and cancel orders on behalf of the customer. We
Sourcegithub.com/anthropics/claude-cookbooks/blob/main/tool_use/customer_service_agent.ipynb
Choose one style, platform or channel from the reference library. Only one.
The **Retail AI Plugin** bundles two end-to-end Google Cloud retail skills for AI coding assistants (Gemini CLI, Claude Code, Antigravity, Codex) following the [Google Agent Plugins v1.0.0 specification][spec] (`plugin.json` + `skills/<skill-name>/SKILL.md`):
Sourcegithub.com/google/adk-recipes/tree/main/plugins/retail
Handles refunds and disputes, drafts support messages
Sourcebotsdots.site/templates/customer-care
Drafts review replies in your shop's own voice, star-sorted, with you approving each one
Sourcebotsdots.site/templates/review-desk
Digs through your inbox receipts for refunds, settlements and unclaimed money
Sourcebotsdots.site/templates/claims-finder
Lost Package Desk for a store: tracks missing, stalled, and delivered-but-not-received shipments, runs carrier playbooks, and never files or refunds
Sourcebotsdots.site/templates/noshipsherlock
Read the required skills, prompts and standards in order.
Creates product search agents with semantic search and RAG on Google Cloud (Vector Search on Gemini Enterprise Agent Platform, BigQuery, embeddings). Use when the user wants to "build a product search agent", "create an e-commerce search", "make a shopping assistant", "set up semantic catalog discov
Sourcegithub.com/google/adk-recipes/blob/main/plugins/retail/skills/product-search/SKILL.md
At the beginning of the conversation, you have to authenticate the user identity by locating their user id via email, or via name + zip code. This has to be done even when the user already provides the user id.
Sourcegithub.com/sierra-research/tau2-bench/blob/main/data/tau2/domains/retail/policy.md
Creates virtual try-on agents supporting image and video (catwalk animation) try-ons on Google Cloud (Gemini image models and Veo on Gemini Enterprise Agent Platform). Handles resource setup, user photo uploading, image/video generation pipelines, local testing, and evaluation.
Sourcegithub.com/google/adk-recipes/blob/main/plugins/retail/skills/virtual-tryon/SKILL.md
The current time is 2024-05-15 15:00:00 EST.
Sourcegithub.com/sierra-research/tau2-bench/blob/main/data/tau2/domains/airline/policy.md
The current time is 2025-02-25 12:08:00 EST.
Sourcegithub.com/sierra-research/tau2-bench/blob/main/data/tau2/domains/telecom/main_policy.md
Generates comprehensive legal and policy documents (ToS, Privacy Policy, Cookie Policy, Community Guidelines, Content Policy, Refund Policy) tailored to a product or service.
Sourceprompts.chat/prompts/cmmx2ya3s000hic04l0i60mil_legal-document-generator-agent-role
Follow a workflow or case. Install a skill or MCP server only if you have permission.
This Streamlit app implements an AI-powered customer support agent for synthetic data generated using GPT-4o. The agent uses OpenAI's GPT-4o model and maintains a memory of past interactions using the Mem0 library with Qdrant as the vector store.
Sourcegithub.com/Shubhamsaboo/awesome-llm-apps/tree/main/advanced_ai_agents/single_agent_apps/ai_customer_support_agent
This repository contains a demo of a Customer Service interface built on top of the [OpenAI Agents SDK](https://openai.github.io/openai-agents-python/).
Sourcegithub.com/openai/openai-cs-agents-demo
A Model Context Protocol server for Zendesk.
Sourcegithub.com/reminia/zendesk-mcp-server
A [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server that provides AI assistants with structured access to the [Freshdesk](https://www.freshdesk.com) customer support platform — tickets, contacts, companies, agents, groups, the knowledge base, and SLA/business-hours configuratio
Sourcegithub.com/WYRE-AI/freshdesk-mcp
Go through the checklist and report the result to your owner.
τ-bench family benchmark (MIT) that simulates user–agent conversations in customer-service domains (retail, airline, telecom, banking) with tools, policies and automatic task evaluation.
Sourcegithub.com/sierra-research/tau2-bench
Package an escalation for engineering, product, or leadership with full context. Use when a bug needs engineering attention beyond normal support, multiple customers report the same issue, a customer is threatening to churn, or an issue has sat unresolved past its SLA.
Sourcegithub.com/anthropics/knowledge-work-plugins/blob/main/customer-support/skills/customer-escalation/SKILL.md