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wa-build

Generate a runnable WhatsApp agent codebase from a characterization spec.

4|3|Updated Mar 24, 2026
Search Tags:#architecture#fastapi#build#sqlite#webhook#code-generation#tool-registry
One-click install
npx skills add https://github.com/Asher-pro/wa-whatsapp-agent --skill wa-build
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: wa-build
Source: https://github.com/Asher-pro/wa-whatsapp-agent/tree/main/skills/wa-build
Command: npx skills add https://github.com/Asher-pro/wa-whatsapp-agent --skill wa-build

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Building a WhatsApp agent from a characterization spec is error-prone and time-consuming. This skill guarantees a consistent, deploy-ready codebase by enforcing a specific architecture (FastAPI + direct LLM SDK + SQLite + explicit tool registry) and guiding Claude Code to produce readable, maintainable files that downstream skills can modify reliably.

Core Features & Use Cases

  • Converts spec.json into a runnable project skeleton including core files (config, database, prompt, agent, main) and a minimal but complete tool registry.
  • Enforces a fixed architecture so wa-connect, wa-deploy, and wa-maintain have stable file expectations.
  • Provides an end-to-end workflow from spec understanding to a smoke-testable local deployment.

Quick Start

Start the wa-build skill after wa-characterize, when spec.json exists, to generate a deploy-ready WhatsApp agent project.

Frequently Asked Questions about wa-build

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a FastAPI WhatsApp agent codebase from a specification?▼

You can generate a FastAPI WhatsApp agent codebase by processing a characterization spec with a code generation tool, which creates a runnable project skeleton with config, database, prompt, agent, and main files.

What architecture does a generated WhatsApp agent project use for webhooks and tools?▼

A generated WhatsApp agent project uses a fixed architecture combining FastAPI, a direct LLM SDK, SQLite, and an explicit tool registry to ensure stable file layouts for webhooks and maintainable code.

Do I need a spec.json file before building a WhatsApp agent project?▼

Yes, you need a spec.json file from a prior characterization step to build a WhatsApp agent project, as it provides the specific characterization data required to generate the codebase.

Can I customize the tool registry in a generated FastAPI WhatsApp agent?▼

The generated FastAPI WhatsApp agent includes a minimal but complete explicit tool registry, which can be modified reliably by downstream maintenance skills due to the stable project layout.

What's the best way to structure a FastAPI and SQLite WhatsApp agent for deployment?▼

The best way to structure a FastAPI and SQLite WhatsApp agent is by enforcing a fixed architecture with explicit tool registry, ensuring readable, deploy-ready files that downstream skills can modify reliably.

Why does my WhatsApp agent code generation fail without a characterization spec?▼

WhatsApp agent code generation fails without a characterization spec because the build process requires spec.json to transform characterization data into a complete, runnable codebase with a fixed architecture.

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