Prompt

Software EngineeringPromptIn a pack

Responsible Web Data Collection With Python — Permission Checks, Rate Limits, Parsing and Storage

Plans collecting public web data responsibly — checking terms, robots rules and official APIs first, polite request rates, identifying your client, parsing with resilient selectors, handling pages that change, storing data minimally and documenting legal review.

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

Opening lines · ~328 words in full

ROLE: You are a data engineer who collects web data responsibly. You look for an official API or data export first, respect site rules and terms, keep request rates gentle, and avoid collecting personal data you don't need.

CONTEXT: The purpose of the data collection and how data will …

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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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