Agent Skills provides a simple, open format for enhancing agent capabilities. Operations teams can create and share reusable skills, improving agent performance across tasks. Skills integrate with supported agents like Claude, streamlining workflows and reducing training time.
git clone https://github.com/agentskills/agentskills.gitThe agentskills automation skill focuses on the specification and documentation necessary for creating and managing AI agent skills. This intermediate-level skill allows developers and product managers to automate data processing tasks by writing scripts that agents can execute on demand. With a time to implement of just 30 minutes, this skill provides a quick way to enhance the capabilities of AI agents, making them more efficient and effective in various operational contexts. One of the key benefits of using agentskills is its ability to facilitate workflow automation. By enabling agents to access knowledge bases and respond to customer queries efficiently, teams can significantly reduce response times and improve customer satisfaction. Additionally, agentskills supports the integration of various APIs, allowing seamless data exchange and task automation. This means that common tasks can be automated with reusable scripts, which minimizes the configuration required for complex workflows, ultimately saving time and resources. This skill is particularly beneficial for developers, product managers, and AI practitioners who are looking to enhance their teams' productivity. By sharing and adapting these skills across different projects, collaboration becomes easier, allowing teams to leverage existing resources and expertise. Whether you are in a tech startup or a larger organization, agentskills can help streamline your processes and enhance the performance of your AI agents. While the implementation difficulty is rated as intermediate, the practical value it offers makes it worthwhile. With no known time savings quantified, the real benefits lie in the operational efficiencies gained through automation. As businesses increasingly adopt AI-first workflows, integrating agentskills into your automation strategy will position your team to better respond to the demands of modern data-driven environments.
Automate data processing tasks by creating scripts that agents can execute on demand.
Enhance customer support agents with skills that allow them to access knowledge bases and respond to queries efficiently.
Develop skills for agents to integrate with various APIs, enabling seamless data exchange and task automation.
Create reusable scripts for common tasks, allowing agents to perform complex workflows with minimal configuration.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/agentskills/agentskillsCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Create an Agent Skill for [COMPANY] in the [INDUSTRY] sector. The skill should automate [SPECIFIC TASK] using [DATA SOURCES]. Include detailed instructions, required tools, and expected outputs. Ensure the skill is reusable and well-documented.
# Agent Skill: Customer Support Ticket Automation ## Description This skill automates the creation and categorization of customer support tickets for [COMPANY], a retail business in the e-commerce industry. It processes customer emails and chat messages to generate support tickets with relevant details. ## Instructions 1. **Input**: Customer emails and chat messages from [DATA SOURCES] (e.g., Gmail, Zendesk Chat). 2. **Processing**: Extract key information such as customer name, issue description, and urgency level. 3. **Output**: Create a support ticket in the [COMPANY] support system with the extracted information. ## Required Tools - Email processing script - Natural Language Processing (NLP) library - API access to [COMPANY] support system ## Expected Output - A support ticket with the following fields: - Customer Name - Issue Description - Urgency Level (High, Medium, Low) - Date and Time of Creation - Assigned Support Agent (if applicable) ## Usage 1. Run the email processing script to extract customer messages. 2. Use the NLP library to categorize the issue and determine urgency. 3. Create a support ticket in the [COMPANY] support system with the extracted information. 4. Assign the ticket to an appropriate support agent based on urgency and issue type.
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