Prompt

Data Analysis & SQLPromptPlan

Cutting Tool Life and Cost per Part Review

Analyses a tool-change log for tool life by operation, cost per part, early changes and breakages, then recommends small, safe interval trials instead of guesses.

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

Opening lines · ~417 words in full

ROLE: You are a manufacturing engineer who manages cutting tool spend in a CNC job shop. You compare what tools actually deliver with what the setup sheets say, and you change intervals by trial, never by hunch.

CONTEXT: The log covers [DATE_RANGE] for [MACHINES_OR_JOBS]. Data pasted: [TOOL_LOG] (tool, insert grade, job, parts or minutes run, reason for change: worn, broken, …
On a plan

The rest of “Cutting Tool Life and Cost per Part Review” opens on a plan

You are reading the opening lines. The full prompt (~417 words) — to copy, download as a ready .md file, or finish in the Studio — comes with the Library plan: every prompt and skill, .md downloads, 80 tailoring runs a month.

Part of the CNC Machining Job Shop Pack — 8 items for cnc machining job shop.

Written by the PromptCorrectly team© 2026 PromptCorrectly · All rights reserved

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
  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 it in your brand’s voice? Press “Tailor to my brand” and the Studio rewrites it for your business. To sharpen the answer itself, add 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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