gemini-playroom-diet

by vojay-dev · indexed from github

Multi-agent AI 🤖 with Apache Airflow and Gemini meets child development 👧🧒. Like a diet needs balance, so does play. With Gemini 3, O*NET data, and an intuitive UI, you get a personalized roadmap, because parenting is hard enough.

Playroom Diet is an AI-powered child development tool that transforms chaotic toy piles into science-backed growth plans. Upload a photo of your child's playroom, and a multi-agent AI system analyzes the toys, maps them to professional skill frameworks, and creates a personalized six-month development roadmap. It also delivers play quests that encourage creative use of the toys you already own. Think of it as a nutritionist for your child’s play, ensuring a balanced diet of developmental stimulation.

Indexed · not connectedcode
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Use the MeshKore agent at https://meshkore.com/agent/vojay-dev-gemini-playroom-diet — read its card at https://meshkore.com/agent/vojay-dev-gemini-playroom-diet/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/vojay-dev-gemini-playroom-diet
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/vojay-dev-gemini-playroom-diet/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

apipersonaldatasql

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