wa-characterize

Interview users to define bot identity, audience, scope, and tools.

4|3|Updated Mar 24, 2026
One-click install
npx skills add https://github.com/Asher-pro/wa-whatsapp-agent --skill wa-characterize
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: wa-characterize
Source: https://github.com/Asher-pro/wa-whatsapp-agent/tree/main/skills/wa-characterize
Command: npx skills add https://github.com/Asher-pro/wa-whatsapp-agent --skill wa-characterize

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Characterize the WhatsApp agent before any code is written. This skill guides a student through structured questions to define identity, audience, scope, knowledge, and tools, and it outputs a spec.json that wa-build uses to generate the bot.

Core Features & Use Cases

  • Guided, Hebrew interactions that elicit one-question-at-a-time answers.
  • Enforces prerequisites (wa-setup completed) and writes a clean spec.json for wa-build.
  • Supports two archetypes (personal assistant and customer service) with tailored defaults and outputs.
  • Produces a compact, testable spec that coordinates identity, audience, scope, knowledge, and tools for end-to-end bot development.

Quick Start

Answer the guided questions to create a complete spec.json that wa-build can use to generate the bot.

Frequently Asked Questions about wa-characterize

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

FAQPage Schema
How do I define a WhatsApp bot specification before coding?

To define a WhatsApp bot specification before coding, you complete a structured interview that establishes identity, audience, scope, knowledge, and tools, outputting a structured spec.json file for subsequent bot generation.

What is the best way to structure a personal assistant bot scope?

The best way to structure a personal assistant bot scope is by enforcing a whitelist mode that explicitly defines authorized contacts, alongside precise in-scope and out-of-scope parameters to control conversation flow and tool configurations.

How does the bot specification process handle customer service versus personal assistant archetypes?

The bot specification process differentiates customer service and personal assistant archetypes by applying tailored defaults and outputs, ensuring each archetype receives the specific scope, knowledge, and tool configurations required for its function.

What prerequisites are needed to generate a bot spec.json file?

Generating a bot spec.json file requires completing the prerequisite wa-setup phase, after which the characterization skill guides one-question-at-a-time interactions to produce the clean spec.json needed for wa-build.

Can I manually edit the spec.json output after the bot design interview?

The spec.json output from the bot design interview is a compact, testable file that coordinates all defined parameters, which wa-build reads directly to generate the bot, though manual edits must maintain the required structure.