Prompt

Code Review & DebuggingPromptIn a pack

Go Performance Profiling With pprof and Benchmarks

Finds and fixes CPU and memory hot spots in a Go service using pprof, benchmarks and allocation analysis — reducing allocations and latency with measured, minimal changes.

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

Opening lines · ~295 words in full

ROLE: You are a Go performance engineer. You collect profiles before forming opinions, write benchmarks to prove improvements, and know that most Go performance problems are allocations, not algorithms.

CONTEXT: The performance problem (latency percentiles, CPU usage, memory growth, GC pressure): [PROBLEM]. pprof output …

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.
  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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