Characterize a WhatsApp AI agent before writing any code. Use when a student has finished wa-setup and is ready to define what the bot does, or says 'wa-characterize', 'ืืคืืื ืกืืื', 'ืืื ื ืชืื ื ืืช ืืืื', 'ืื ืืืื ืขืืฉื', 'ืืืืจ ืืช ืืืื'. This skill asks the hard questions (who does it answer? what's its knowledge? which tools?) and produces a spec.json that wa-build reads to generate the bot.
Deploy a WhatsApp AI agent to Render.com - automated via Render CLI + API. Use after wa-build (bot's tone is confirmed locally) or when student says 'ืืขืื ืกืืื', 'wa-deploy', 'deploy agent', 'ืชืขืื ืืคืจืืืงืฉื', 'ืชืขืื ืืช ืืกืืื', 'ืืกืืื ืืืื ืื ืขืืฉืื'. Minimizes browser clicks: student provides a Render API key once, Claude Code runs CLI + REST API calls to create the web service, attach disk, optionally provision Postgres (for Outlook), deploy, and wire the Green API webhook. Student only intervenes for one-time GitHubโRender OAuth connection and any payment approval.
Maintain, debug, and update a deployed WhatsApp AI agent. Use when the bot is live and needs changes, or the student says 'wa-maintain', 'ืชืชืงื ืืช ืืกืืื', 'ืืกืืื ืื ืขืืื', 'ืชืฉื ื ืืช ืืกืืื', 'ืชืขืืื ืืช ืืืื', 'ืฉื ื prompt', 'ืืกืืื ืชืงืืข', 'ืืกืืื ืื ืขืื ื', 'ืชืืกืืฃ ืืื', 'ืชืืกืืฃ ืคืืฆ'ืจ'. Routes to the right remedy: prompt tune, scope change, tool add/remove, Google/Microsoft token refresh, debug checklist for outages.
Set up Green API for WhatsApp agent connection. Use when a student needs to connect WhatsApp, register for Green API, or says 'ืืืจ WhatsApp', 'ืืงื Green API', 'wa-setup', 'ืื ื ืจืืฆื ืืืชืืื ืืื ืืช ืกืืื WhatsApp', 'ืืื ื ืชืืื ืขื WhatsApp'. Also trigger when someone mentions needing a WhatsApp connection for their bot or agent. This skill handles instance type selection (free for personal assistant, paid for customer service), phone number setup (eSIM recommended), QR scanning, incoming webhook configuration, and end-to-end verification.
Build the WhatsApp agent code from a characterization spec. Use after wa-characterize when the student has an approved spec.json, or says 'wa-build', 'ืื ื ืืช ืืกืืื', 'ืชืื ื ืืช ืืงืื', 'ืืืืื ืืื ื ืื ื'. This skill enforces the opinionated architecture (FastAPI + direct LLM SDK + SQLite + explicit tool registry) and guides Claude Code to generate a clean, deploy-ready codebase. No framework magic - the student can read every line.
Wire a tool (Google Calendar, Gmail, WhatsApp groups, Human handoff, Outlook) into a deployed WhatsApp agent. Use after wa-deploy when the student is ready to give the bot capabilities, or says 'wa-connect', 'ืืืจ ืืื', 'ืืืจ ืืืื', 'ืืืจ ืืืื', 'ืืืจ ืงืืืฆืืช', 'ืชืืกืืฃ ืืื ืืกืืื'. Each invocation wires exactly ONE tool and redeploys. Run multiple times to add multiple tools. Handles auth, credential storage, tool implementation, redeploy, and live verification.
Give the deployed WhatsApp bot durable memory that survives Render restarts. Use when the student says 'ืืืื ืฉืืื ืฉืืืืช', 'ืืืื ืื ืืืืจ ืืืชื', 'wa-persistence', 'ืชืืกืืฃ ืืืืจืื ืืืื', 'reminders ื ืืืงืื', or any variant of 'memory doesn't persist'. Also called automatically at end of wa-deploy if the student is on Render Free without a disk. Four sub-flows: (A) Render Disk, (B) Supabase Pooler โ most common, (C) Render Postgres, (D) Skip with warning.