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Understanding AI Agents

AI Agents are customizable, sharable agents that can be invoked on selected code or entire files in your IDE. Use prebuilt agents or create your own with specific instructions, tools, and commands.
Agents vs Skills: AI Agents are interactive — you select them explicitly and chat with them. Skills are passive instruction packages that the agent loads automatically based on task context. Use agents for recurring interactive tasks; use skills for domain knowledge and procedural workflows.
At the top of the AI Agents screen, you’ll find tabs that help you filter and navigate between different types of agents:

All

Shows all available agents

Zencoder

Displays prebuilt agents created by Zencoder (with the number indicating how many are available)

Custom

Shows your custom agents (with the number indicating how many you’ve created)
AI Agents Selection This categorization makes it easy to distinguish between default agents and your own custom creations.

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Creating an Agent

1

Adding a New Agent

  1. Click the three dots menu (⋮) at the top right corner.
  2. Select Agents
  3. Click the Add custom agent button in the top right Create a Custom Agent
2

Configuring an Agent

When adding or editing an agent, you’ll need to set these properties:Basic Settings:
  • Name: A descriptive name for your agent (required)
  • Share: Control who can see and use this agent
    • Personal: Visible only to you
    • Shared: Visible to your entire organization (all users within your organization can share agents with others)
Configuration:
  • Command/Alias: The chat command to invoke your agent (required)
  • Instructions: Detailed prompt instructions that define your agent’s behavior (required)
  • Tools: Enable specific tools your agent can access Configuring an Agent
3

Instructions Format

Define clear instructions for your agent that explain its purpose and how it should operate. Here’s an example of instructions for a Repository Analyzer agent:
Consider the currently open project and repository. 
Understand its structure, mutual relations between files, folders, dependencies, and more. 
Please provide me with an in-depth structured understanding of this repo
Your instructions should be specific enough to guide the agent’s behavior, but also flexible enough to work across different contexts.
4

Tool Selection

Agents can access various tools to enhance their capabilities:
  • git
  • File Search
  • Full Text Search
  • Web Search
  • Fetch Webpage Content
  • Semantic Code Search
  • File Editor
  • Execute Shell Command
  • Gather Requirements
  • …
Simply click on the tools your agent should have access to in the Tools section.Configuring Agent tools
5

Sharing Agents

If you’re an admin, you can share agents with your organization:
  1. When editing an agent, find the Share dropdown
  2. Choose between:
    • Personal: Visible only to you
    • Shared: Visible to the whole organization Sharing Agent

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Contributing Your Own Agents

You can submit custom agents to the marketplace via the zenagents-library GitHub repo.

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Using Agents in Your Workflow

Once configured, you can use agents by:
  1. Selecting code in your editor or focusing on an entire file
  2. Invoking the agent using its command (e.g., /unittests, /review)
  3. The agent will perform its specialized task on the selected code

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Example Use Cases

Create an agent with instructions to scan for OWASP Top 10 vulnerabilities, check for hardcoded secrets, and verify authentication/authorization patterns. Give it access to File Editor, Codebase Search, and Shell Commands (to run static analysis tools).
Build an agent that reads recent git commits and generates changelog entries. Give it Git Operations and Web Search (to link to related issues). Set the command to /release-notes.
Create an agent with instructions to generate OpenAPI specs from your route files. Scope it with Codebase Search and File Editor to read route definitions and write .yaml docs.
Share an agent across your org that new team members can invoke to get explanations of project architecture, key modules, and development workflows. Give it read-only tools (Codebase Search, File Search) and reference your repo’s README and architecture docs in its instructions.

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Tips for Custom Agents

An agent should do one thing well. A “Security Scanner” is better than a “Security Scanner + Performance Optimizer + Docs Generator.”
Only enable the tools your agent actually needs. A read-only analysis agent shouldn’t have File Editor or Shell Commands.
Pick short, memorable commands like /review, /docs, or /migrate. These become muscle memory.
Set agents to Shared visibility so your entire org benefits. This is especially powerful for standardized workflows like PR reviews or release processes.

Coding Agent

The primary development agent that your custom agents can complement

Skills

Reusable instruction packages that agents load automatically based on task context

Integrations & MCP

Connect external tools via Model Context Protocol

Supported Models

Choose from 10+ models or bring your own API key