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retail-agent-learner

@lavinigam-gcp/build-with-adk
3
20

Learn ADK concepts and understand the retail agent pipeline. Use when asking how the agent works, what ADK is, wanting to understand the architecture, state flow, or individual agent purposes.

Install Skill

Shared

Installs to .agents/skills, used by Codex, Amp, Warp, Cursor, OpenCode, and more.

CodexAmp
Warp
CursorOpenCode
Cline
Gemini CLI
GitHub Copilot
Personal

Available across projects.

$npx skills-installer add @lavinigam-gcp/build-with-adk/retail-agent-learner --client shared
Project

Writes to .agents/skills.

$npx skills-installer add @lavinigam-gcp/build-with-adk/retail-agent-learner -p --client shared
Note: Review the skill instructions before using it.

SKILL.md

name retail-agent-learner
description Learn ADK concepts and understand the retail agent pipeline. Use when asking how the agent works, what ADK is, wanting to understand the architecture, state flow, or individual agent purposes.

Retail Agent Learner

Pipeline Overview

This is an 8-agent pipeline for retail site selection analysis:

User Query
    ↓
IntakeAgent ────────────→ Extract location + business type
    ↓
MarketResearchAgent ────→ Google Search for demographics
    ↓
CompetitorMappingAgent ─→ Google Maps Places API
    ↓
GapAnalysisAgent ───────→ Python code execution (pandas)
    ↓
StrategyAdvisorAgent ───→ Extended thinking synthesis
    ↓
ParallelAgent ──────────→ Concurrent artifact generation
    ├── ReportGenerator ─→ HTML report
    ├── InfographicAgent → Image generation
    └── AudioOverview ───→ TTS podcast audio

What Each Agent Does

Agent Purpose Key Tool/Feature
IntakeAgent Parse user request AgentTool pattern
MarketResearchAgent Find market data google_search built-in
CompetitorMappingAgent Map competitors Google Maps API
GapAnalysisAgent Calculate viability Code execution (pandas)
StrategyAdvisorAgent Synthesize recommendations Extended thinking
ReportGenerator Create HTML report Artifact generation
InfographicAgent Generate visual Image generation
AudioOverview Create podcast audio TTS multi-speaker

Key ADK Concepts

Agents

  • LlmAgent: Single LLM call with tools and instructions
  • SequentialAgent: Runs sub-agents one after another
  • ParallelAgent: Runs sub-agents concurrently

State Flow

Data passes between agents via session state:

IntakeAgent → state["target_location"], state["business_type"]
MarketResearchAgent → state["market_research_findings"]
CompetitorMappingAgent → state["competitor_analysis"]
GapAnalysisAgent → state["gap_analysis"]
StrategyAdvisorAgent → state["strategic_report"]

Tools

Functions that agents can call to perform actions. Access state via ToolContext.

Callbacks

Lifecycle hooks: before_agent_callback and after_agent_callback.

Learning Path

Start with the 9-part tutorial series:

  1. Part 1: Setup + First Agent
  2. Part 2: IntakeAgent
  3. Part 3: MarketResearchAgent
  4. Part 4: CompetitorMappingAgent
  5. Part 5: GapAnalysisAgent (code execution)
  6. Part 6: StrategyAdvisorAgent (extended thinking)
  7. Part 7: ArtifactGeneration (parallel outputs)
  8. Part 8: Testing
  9. Part 9: Production Deployment

[See references/architecture.md for detailed data flow] [See references/adk-concepts.md for ADK deep dive]