Declarative Agents

Agent systems require configuration defining behaviors, tools, and workflows. Declarative agents specify agent capabilities through configuration rather than code, enabling rapid agent creation, behavior modification, and workflow orchestration without programming. This skill generates declarative agent definitions enabling non-developers to create and customize AI agents.

What Is This?

Overview

Declarative Agents produces configuration-based agent definitions. It generates YAML or JSON specifications declaring agent capabilities, defines tool access and permissions, specifies workflow and conversation patterns, configures context and memory settings, outlines decision-making logic, sets guardrails and constraints, and creates agent orchestration patterns enabling agent deployment without custom code.

The skill understands agent frameworks supporting declarative configuration including LangChain agents, AutoGen systems, and custom agent platforms. Generated configurations follow framework conventions while remaining human-readable and maintainable. This makes configurations easy to review, audit, and modify across teams with varying technical backgrounds.

Who Should Use This

Product managers defining agent behaviors. Non-technical teams creating automation. Platform engineers standardizing agents. Operations teams deploying workflows. Business analysts configuring processes. Citizen developers building solutions.

Why Use It?

Problems It Solves

Agent development requires programming expertise. Declarative configuration enables non-developers to create agents through structured specifications without writing a single line of code.

Agent behavior changes need code updates and redeployment. Configuration changes apply without code modification or complex deployment, reducing iteration time significantly.

Agent creation involves repetitive implementation. Templates and patterns accelerate agent development across teams, promoting consistency and reducing duplicated effort.

Testing agent variations requires code branches. Configuration variants enable A/B testing and experimentation without code changes, making it straightforward to compare different behavioral approaches.

Core Highlights

YAML or JSON agent definitions. Tool and permission specification. Workflow pattern configuration. Context and memory settings. Decision logic declaration. Guardrail and constraint definition. Agent orchestration patterns. Version control friendly. Framework agnostic design.

How to Use It?

Basic Usage

Describe agent purpose and required capabilities. The skill generates declarative configuration defining agent behavior.

Create declarative agent for customer support
with knowledge base access and escalation workflow

Generate agent configuration handling
order tracking queries with database access

Specific Scenarios

For multi-agent systems, define coordination.

Create declarative configuration for three agents:
researcher, writer, and reviewer with handoffs

For tool access, specify permissions.

Generate agent with read-only database access
and API calling capabilities

For workflows, declare steps.

Create agent configuration with decision tree
for routing queries to appropriate handlers

Real World Examples

A product manager designs customer service agent without developer help. Technical implementation is blocker. Declarative agent configuration is generated specifying agent responds to support queries, accesses knowledge base for answers, escalates to human when uncertain, logs all interactions, and follows brand voice guidelines. Agent deploys from configuration without custom code.

A platform team standardizes agents across organization. Each team implements agents differently causing inconsistency. Generated declarative templates define common patterns for data query agents, API integration agents, and workflow automation agents with tool specifications, permission models, and error handling. Teams customize configurations rather than building from scratch.

An operations team experiments with agent workflows. Code changes for testing variations is slow. Declarative configurations enable multiple variants with different decision thresholds, tool selection strategies, and escalation criteria. A/B testing proceeds by deploying configuration variants and measuring outcomes against defined performance benchmarks.

Advanced Tips

Version control agent configurations. Use configuration inheritance for variants. Validate configurations before deployment. Monitor agent performance metrics. Document configuration options clearly. Create configuration templates for common patterns such as support routing or data retrieval. Test configurations in staging. Use configuration management tools.

When to Use It?

Use Cases

Customer service automation. Data query agents. Workflow orchestration. Multi-agent coordination. Rapid prototyping. Configuration management. A/B testing variations. Non-developer agent creation.

Related Topics

Agent frameworks and platforms. YAML and JSON configuration. Workflow orchestration. Agent communication patterns. Configuration management. Infrastructure as code. Prompt engineering. Agent evaluation.

Important Notes

Requirements

Agent framework supporting declarative config. Clear agent requirements. Understanding of available tools. Knowledge of workflow patterns. Access to deployment infrastructure.

Usage Recommendations

Start with simple configurations. Test thoroughly before production. Version control all configurations. Document configuration schema. Validate against framework requirements. Use templates for common patterns. Monitor deployed agents. Update configurations iteratively. Maintain configuration documentation.

Limitations

Framework capabilities limit what can be configured. Complex logic may still need code. Performance depends on framework implementation. Debugging can be harder than code. Not all agent patterns support declarative definition. May have learning curve for configuration syntax.