By Asher-pro
Build, deploy, and maintain a WhatsApp AI agent - step by step, no coding required. Guides non-technical users through the entire process: connecting WhatsApp via Green API, building an AI-powered conversational agent, deploying to Render.com, and ongoing maintenance.
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', 'בנה את הסוכן', 'תבנה את הקוד', 'יאללה בוא נבנה'. 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.
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', 'אפיין סוכן', 'בוא נתכנן את הבוט', 'מה הבוט עושה', 'הגדר את הבוט'. 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.
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', 'חבר כלי', 'חבר יומן', 'חבר מייל', 'חבר קבוצות', 'תוסיף כלי לסוכן'. 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.
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 'העלה סוכן', 'wa-deploy', 'deploy agent', 'תעלה לפרודקשן', 'תעלה את הסוכן', 'הסוכן מוכן מה עכשיו'. 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 GitHub↔Render 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', 'תתקן את הסוכן', 'הסוכן לא עובד', 'תשנה את הסוכן', 'תעדכן את הבוט', 'שנה prompt', 'הסוכן תקוע', 'הסוכן לא עונה', 'תוסיף כלי', 'תוסיף פיצ'ר'. Routes to the right remedy: prompt tune, scope change, tool add/remove, Google/Microsoft token refresh, debug checklist for outages.
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A Claude Code plugin that guides non-technical users through building, deploying, and maintaining a WhatsApp AI agent — step by step, in Hebrew, with zero coding required.
/plugin marketplace add Asher-pro/wa-whatsapp-agent
/plugin install wa-whatsapp-agent@practice-ai-plugins
Then run /wa to start.
The plugin has one entry command (/wa) and six skills. You run /wa, it figures out where you are, and routes you to the right skill.
/wa ─┬─▶ wa-setup (Green API + phone number)
├─▶ wa-characterize (define what the bot does)
├─▶ wa-build (generate code)
├─▶ wa-connect (wire tools: calendar, mail, groups, reminders)
├─▶ wa-deploy (ship to Render)
└─▶ wa-maintain (debug & update after launch)
Progress is tracked in a .wa-state.json file in your project — if you leave mid-way and come back a week later, /wa picks up where you left off.
Opinionated, lean, readable:
msalWhy this and not LangChain/Agno/CrewAI? So you can read every line of your own bot's code and debug it. Framework magic bites non-technical users hardest when it fails.
For contributors:
/wa command — single entry point, reads .wa-state.json, routes to the correct skill.wa-state.json, offers the next skill on completion.wa-state.json — single source of truth for "where the student is"This means: no skill assumes state from file existence. No skill calls the next one blindly. /wa always has the full picture.
MIT
npx claudepluginhub asher-pro/wa-whatsapp-agent --plugin wa-whatsapp-agentComprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
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