菜单
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.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
Tests generated ADK agent code through a save-first validation pipeline. Saves code to disk FIRST, then tests the saved code via start_agent and talk_to_agent. Drives the iterative refinement loop.
FastAPI development best practices and conventions. Use when building, reviewing, or debugging FastAPI applications, REST APIs, or Pydantic models.
Reviews Python code for quality, style, and common bugs. Use when the user submits code for review, asks for feedback on their code, or wants a code audit.
Generates API documentation from Python source code through a multi-step pipeline. Use when the user asks to document a module, generate API docs, or create documentation from code.
Plans a new software project by gathering requirements through structured questions before producing a plan. Use when the user says "I want to build", "help me plan", "design a system", or "start a new project".
Generates structured technical reports in Markdown. Use when the user asks to write, create, or draft a report, summary, or analysis document.
基于 SOC 职业分类
| 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. |
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
| 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 |
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"]
Functions that agents can call to perform actions. Access state via ToolContext.
Lifecycle hooks: before_agent_callback and after_agent_callback.
Start with the 9-part tutorial series:
[See references/architecture.md for detailed data flow] [See references/adk-concepts.md for ADK deep dive]