Self Care Plan Gap Checker

How Self Care Plan Gap Checker works

Press Load model once: your browser downloads Gemma 3 1B instruction-tuned (web build) (728 MB) from this site and keeps it in its cache. Then add your text and press Check locally. The model runs on this device using your graphics card, so nothing you enter is sent to a server. Until the model is loaded, or if your device cannot run it, the tool falls back to a simple keyword check and labels the result as the fallback.

Gemma 3 1B instruction-tuned (web build) is a small open language model from Google. The tool sends it the instruction below plus your two texts, asks for a JSON answer with fixed fields, and shows each field as a card. It runs at temperature 0, so the same input gives the same answer on the same device, though different graphics cards can word it slightly differently.

Inputs longer than 6,000 characters are cut to that length before they reach the model, and the result says so. The model only sees what you paste: it does not look anything up.

The instruction also carries one worked example: the built-in sample with the answer the larger Gemma 4 E2B model gave for it. That example is what lets this smaller model follow the answer format reliably.

If what you enter mentions suicide or self-harm, the tool does not run the model. It shows crisis lines instead (in the US, call or text 988), because a trained person can help in a way a small model cannot.

The instruction the model gets

You compare someone's current self-care plan (first text) with a checklist of needs (second text). For each checklist item, say whether the plan clearly covers it. Count an item as covered only when the plan has a concrete step for that same need. You do not diagnose, do not give medical or therapeutic advice, and do not add new needs; only organise what the user wrote, kindly.

What it returns

• Covered by the plan: Checklist items with a matching step, written as 'item: the step that covers it'.
• Not yet covered: Checklist items the plan has no step for.
• One small next step: A small, concrete step for one gap, using only what the user wrote.

Worked example

The model's output for the built-in sample, recorded on a desktop browser. Your run may word things slightly differently.

Walk after work three days a week. Journal twice a week. Text one friend when overwhelmed. Phone out of the bedroom by 11pm. A regular sleep routine. Emergency contacts. Realistic coping options. A follow-up date. What to do during travel weeks.

Covered by the plan

A regular sleep routine: Add a step for a regular sleep routine

Not yet covered

Emergency contacts Realistic coping options A follow-up date What to do during travel weeks

One small next step

Add a step for a regular sleep routine.

The model

The files are served from this site, versioned so a cached copy is never stale. Nothing is fetched from a third party while you use the tool.

You can switch models in the tool. Also available: Gemma 4 E2B instruction-tuned (web build) (2.0 GB). The larger language model gives more thorough answers but is a bigger download and needs a stronger device.

Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms.

Limitations

• Small language models make mistakes: they can miss an item, merge two, or state something more confidently than the text supports. Check the result against your input before you rely on it.
• It needs WebGPU and about 4 GB of memory, so it is offered on desktops and laptops, not on phones and tablets. Devices that cannot run it get the keyword fallback, clearly labelled.
• Results describe the input you gave, not the real-world situation behind it. Review them yourself before acting.
• This is not a medical device and does not give medical advice, a diagnosis or a treatment plan. Ask a qualified health professional about any symptom, medication or change to your routine.

Good uses

• Triage mental health and wellbeing notes before deeper review
• Prepare consistent labels for repeat workflows
• Reduce manual sorting on small batches
• Keep sensitive drafts in the browser preview