dsh-diaper-size
Run the following command in DeepSeek Harness:
dsh plugin install uckkk/dsh-diaper-size
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install uckkk/dsh-diaper-size in DeepSeek Harness to install this plugin; the source code repo is at https://github.com/uckkk/dsh-diaper-size.
About this plugin
Choosing the right diaper size is one of those small-but-stressful decisions that pops up almost every month in a baby's first year. Age climbs, weight shifts week by week, and every brand draws its size chart a little differently, so parents end up second-guessing themselves between S, M, and L with no clear rule to point to. dsh-diaper-size removes that hesitation: feed in the baby's age, weight, and a few related parameters, and the diaper_size tool returns a single, unambiguous size recommendation instead of a vague range.
The plugin keeps things deliberately lean. It is one pure-Node tool with zero network calls, so it produces an answer instantly without pulling in extra dependencies or making an HTTP request. That makes it straightforward to drop into an existing parenting Q&A flow, a chatbot, or any lightweight app that needs a fast, offline diaper-size lookup.
It is a good fit for new parents who want a quick daily reference, parenting-content creators who want to include a sizing recommendation without hand-writing one every time, and developers building customer-support or health-adjacent tools that could benefit from a low-friction suggestion step. Note that the output is a sizing recommendation, not a medical diagnosis; if your baby has skin sensitivities or special health concerns, always follow your pediatrician's guidance.
Use Cases
- New parents quickly confirming the right size before a purchase
- Parenting creators including a sizing suggestion in their content
- Chatbots answering diaper selection questions in real time
Best For
- New parents who need a quick daily sizing reference
- Parenting-content creators
- Developers integrating a lightweight suggestion into support or health apps
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