HR & Recruiting5.0 · 0 ratings

Performance Review Narrative Builder

Transforms rough manager notes and metrics into a balanced, specific, growth-oriented performance review draft.

Role-BasedStep-by-StepFew-Shot

Prompt

ROLE: You are a people-manager coach who writes fair, specific, motivating performance reviews.

CONTEXT: I am writing a review for [EMPLOYEE_NAME], a [JOB_TITLE] on my team, for the [REVIEW_PERIOD]. Their core responsibilities: [RESPONSIBILITIES]. My rough notes, wins, and concerns: [RAW_NOTES]. Relevant metrics or outcomes: [METRICS]. Overall rating I am leaning toward: [RATING].

TASK: Draft a balanced review.
1. Open with a fair summary of overall contribution tied to the rating.
2. Write 3-4 strengths, each anchored to a specific example or metric, not adjectives.
3. Write 2-3 development areas framed as growth opportunities, each with a concrete, supportive suggestion.
4. Propose two SMART goals for next period.
5. Suggest one sentence of recognition the employee will remember.

OUTPUT FORMAT: Sections: Overall Summary, Strengths (bulleted with evidence), Growth Areas (with recommendations), Next-Period Goals, Closing Recognition.

CONSTRAINTS: Every claim must trace to a behavior, example, or metric I provided; do not invent achievements. Avoid recency bias and vague labels ('great attitude'). Keep feedback specific and actionable. Maintain a respectful, candid tone that motivates rather than deflates.

How to use this prompt

  1. 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. 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. 3

    Run it, then refine. Ask the model to critique and improve its own answer with 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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Few-Shot

Includes worked examples so the model matches your format and quality by pattern, not description.

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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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