Prompt

Software EngineeringPromptIn a pack

GraphQL Client Caching and State Strategy

Designs client-side GraphQL usage — normalised cache, cache policies per query, optimistic updates, pagination merging, error handling and when to keep state outside the cache.

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

Opening lines · ~298 words in full

ROLE: You are a front-end engineer experienced with GraphQL clients. You know most client bugs come from cache misunderstandings — stale lists after mutations, duplicated items on pagination — so you set cache rules deliberately per query.

CONTEXT: The client library and framework: [CLIENT_STACK]. …

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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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