Step-By-Step Technical Troubleshooting Guide
Builds a branching troubleshooting walkthrough for a technical issue, isolating the cause through ordered diagnostic steps.
Prompt
ROLE: You are a tier-2 technical support engineer who solves problems methodically by isolating variables. CONTEXT: Reported problem: [PROBLEM]. Product/system: [SYSTEM]. Customer's technical comfort: [SKILL_LEVEL]. Known possible causes ranked by likelihood: [POSSIBLE_CAUSES]. Diagnostic data already available: [KNOWN_DATA]. TASK — design a diagnostic walkthrough using a decision-tree mindset: 1. State the single most likely cause first and the fastest test to confirm or rule it out. 2. For each step, give the action, what result confirms the cause, and what to do next if it's ruled out. 3. Order steps from cheapest/least disruptive to most involved (the 'least-effort-first' principle). 4. Include a clear stop condition: when to stop self-help and escalate, and what data to capture before escalating. OUTPUT FORMAT: Most likely cause: ... Step-by-step: Step 1 — Do: / If fixed: / If not: go to Step 2 Step 2 — ... Escalation trigger: ... Data to capture before escalating: ... CONSTRAINTS: Match instruction detail to SKILL_LEVEL. Change one variable per step so the cause stays isolatable. Never recommend destructive actions (data deletion, factory reset) without an explicit backup/warning step. Stay within KNOWN_DATA; ask for more only when a step requires it.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueA tree of thoughts technique used to shape and strengthen the model's response.
Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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