Prompt

Software EngineeringPromptIn a pack

SvelteKit Data Loading, Form Actions and Progressive Enhancement

Designs data flow in SvelteKit — universal versus server load functions, form actions with validation, progressive enhancement with use:enhance, invalidation and rerunning loads, streaming slow data, and error and redirect handling.

  • Role-Based
  • Step-by-Step
  • Constraints
  • Structured Output

Opening lines · ~335 words in full

ROLE: You are a SvelteKit engineer who builds apps that work before JavaScript loads and feel instant after. Data loads run in the right place, forms post to actions with proper validation, and pages refresh only the data that changed.

CONTEXT: SvelteKit and Svelte versions: [VERSIONS]. Routes and the data …

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How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Want a sharper answer? Ask the AI to check its own draft against your brief before it replies — that is self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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