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sdlc-technical-designer

README.md

Technical Designer

A. Overview & Functionalities

This agent is intended to be used as part of a broader Software Development Life Cycle (SDLC) workflow. For more details on how it integrates with other agents, please see the SDLC Agents Workflow:

Full SDLC Workflow

Agent Details Table

Interaction Type Conversational / Workflow
Complexity Easy
Agent Type Single Agent
Vertical Software Architecture / Engineering
Key Features Architectural analysis, Spanner Code Knowledge Graph exploration, interactive technical clarification, Architecture Decision Record (ADR) creation, Mermaid architecture diagram generation, outputs standardized RFC Technical Design Markdown.

B. Architecture

Architecture Diagram

Example Interaction

User: Here is the refined user story for the Slack notification integration:

[STORY TITLE: Slack Integration for Critical System Alerts]

[...] Please propose a technical design for implementing this.

Agent: I've queried the Code Knowledge Graph and analyzed the current notification architecture. Here is the technical design for the Slack integration:

RFC: Slack Integration for Critical System Alerts

1. Context and Scope

  • Background: The DevOps team needs immediate visibility into critical system alerts via Slack. This requires a workspace-level OAuth flow and a mechanism to post formatted messages.
  • Goals: Implement Slack OAuth, store workspace tokens securely, and extend the existing NotificationService to support Slack as a destination. [...]

2. Proposed Architecture

---
title: Structural Overview
---
flowchart LR
    AlertSystem([Alert System]) --> NotifService[Notification Service]
    NotifService --> SlackAPI[Slack API]
    OAuthFlow([OAuth Flow]) --> CredStore[(Credential Store)]
    NotifService -.-> CredStore
Loading

[...]

C. Setup & Execution

Prerequisites & Installation

  • Python 3.10+

  • uv

    • For dependency management and packaging. Please follow the instructions on the official uv website for installation.
    curl -LsSf https://astral.sh/uv/install.sh | sh

Set up your environment variables by copying the example file:

cp .env.example .env

Populate .env with your GCP project and Spanner details. If left null, the agent will operate without external database queries.

Install dependencies:

uv sync --dev

Running the Agent

Run the agent locally via CLI:

uv run adk web sdlc_technical_designer

Alternative: Using Agent Starter Pack

You can also use the Agent Starter Pack to create a production-ready version of this agent with additional deployment options:

# Create and activate a virtual environment
python -m venv .venv && source .venv/bin/activate # On Windows: .venv\Scripts\activate

# Install the starter pack and create your project
pip install --upgrade agent-starter-pack
agent-starter-pack create my-technical-designer -a adk@sdlc-technical-designer
⚡️ Alternative: Using uv

If you have uv installed, you can create and set up your project with a single command:

uvx agent-starter-pack create my-technical-designer -a adk@technical-designer

This command handles creating the project without needing to pre-install the package into a virtual environment.

The starter pack will prompt you to select deployment options and provides additional production-ready features including automated CI/CD deployment scripts.

D. Customization & Extension

  • Modifying the Flow: Adjust the RFC document structure, diagram types, or required architecture checks in sdlc_technical_designer/prompt.py.
  • Adding Tools: Introduce external integrations like cloud resource estimators or architecture linters in sdlc_technical_designer/tools/.
  • Changing Data Sources: Configure Spanner queries to point to different codebase graph instances or knowledge bases.