GitHub Copilot Prompt for Skills Assessment
GitHub Copilot, the AI coding assistant integrated into IDEs, can be repurposed from its usual code completion role into a powerful tool for evaluating technical skills. By leveraging its ability to analyze code, generate exercises, and produce evaluation grids, technical leads, trainers, and recruiters can structure rigorous and reproducible assessment processes. Whether you want to audit an existing team's skills, design a technical test for recruitment, or create a personalized upskilling path, Copilot helps you formalize objective criteria and generate assessment scenarios suited to the target level. The key advantage lies in its deep knowledge of development best practices, design patterns, and industry standards, enabling it to produce evaluations aligned with real market expectations. This prompt guides you to transform Copilot into a structured evaluator capable of covering both pure technical skills and abilities in software architecture, code review, and problem-solving.
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Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
Act as an expert in technical skills assessment. I want to evaluate a developer's skills in the following area: [TECHNOLOGY/LANGUAGE]. The expected level is [JUNIOR/INTERMEDIATE/SENIOR]. Generate a complete evaluation grid including: 1) A list of 8 to 10 key skills to assess, categorized by domain (fundamentals, best practices, architecture, tooling). 2) For each skill, define 4 proficiency levels (not acquired, in acquisition, acquired, expert) with observable and concrete behavioral indicators. 3) Propose 3 practical exercises of increasing difficulty to validate these skills, each with: detailed statement, time allocated, measurable success criteria, and an example commented reference solution. 4) Add a 'red flags' section listing errors or anti-patterns that reveal a critical lack of mastery. Format the output in structured Markdown with tables for the evaluation grid.
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Why this prompt works
This prompt works by assigning an expert role that activates Copilot's specialized knowledge in technical pedagogy. The 4-point structure with precise deliverables (grid, levels, exercises, red flags) eliminates ambiguity and forces a comprehensive and actionable response. The request for observable and measurable criteria anchors the evaluation in concrete rather than subjective terms.
Use Cases
Variants
Expected Output
You will get a complete Markdown document containing a tabular evaluation grid with 8 to 10 skills distributed across categories, each broken down into 4 proficiency levels with precise indicators. The document will also include 3 progressive practical exercises with their commented solutions, as well as a list of warning signs to quickly detect critical gaps.
Frequently Asked Questions
Can GitHub Copilot really assess skills reliably?
Copilot doesn't replace the human judgment of an experienced evaluator, but it excels at structuring the assessment process. It generates consistent rubrics, calibrated exercises, and objective criteria based on industry standards. Its main contribution is eliminating improvisation bias by providing a reproducible framework. It's recommended to always have the generated rubric validated by a domain expert before using it in real-world conditions, and to adjust the exercises to the specific context of your organization.
How do I adapt the generated exercises to my company's specific context?
Give Copilot as much context as possible in your prompt: describe your tech stack, coding conventions, architectural patterns, and the type of projects the developer will work on. You can also provide a snippet of your actual codebase and ask it to create exercises based on similar scenarios. The richer the context, the more relevant and aligned the exercises will be with your operational expectations.
What's the best way to use the generated evaluation rubric during a technical interview?
Use the rubric as a structuring aid, not a rigid script. Start with the practical exercises to observe the candidate in action, then use the rubric to objectively score each skill. The behavioral indicators generated by Copilot serve as benchmarks to distinguish between levels. Share the rubric with all evaluators before the interview to ensure consistent scoring, and keep the completed rubrics to compare candidates against identical criteria.
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- LéaAI
Pour maximiser l'impact, ajoutez une colonne "poids" dans la grille pour pondérer chaque compétence selon le poste (ex : architecture plus importante pour un senior). Cela permet un score global objectif. Vous pouvez aussi remplacer les "red flags" par des "green flags" pour repérer les talents qui dépassent le niveau attendu.
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