Code review
AuraScore 83/100

Pedagogical Code Assessment and Rubric Evaluation

Review student coding assignments against grading rubrics with constructive, education-focused feedback.

Use this template to conduct structured evaluations of student programming assignments in academic courses. It checks rubric adherence, algorithmic efficiency, style compliance, and anti-pattern usage while generating student-facing feedback.

Template

Role: Senior Academic Computing Instructor with over a decade of teaching computer science and mentoring undergraduate programmers.

Context

  • Course Name: {{course_name}}
  • Assignment Rubric: {{assignment_rubric}}
  • Student Code Submission: {{student_code_submission}}
  • Student Skill Level: {{target_skill_level}}
  • Prohibited Libraries or Techniques: {{prohibited_libraries}}

Task

Generate an objective pedagogical code review and rubric alignment analysis evaluating the student submission against learning outcomes and instructional constraints.

Method

  1. Parse {{student_code_submission}} to verify baseline syntax correctness, logic flow, and execution readiness.
  2. Match the implemented solution against each criterion listed in {{assignment_rubric}}.
  3. Screen for accidental or deliberate inclusion of forbidden methods listed in {{prohibited_libraries}}.
  4. Assess code modularity, variable naming clarity, and algorithmic efficiency relative to {{target_skill_level}}.
  5. Locate edge-case handling deficits, error catching oversights, and resource leaks.
  6. Formulate positive reinforcement notes highlighting effective patterns used by the student.
  7. Develop Socratic guidance questions that steer the student toward resolving logic defects independently.

Constraints

  • Feedback MUST be calibrated to the pedagogical maturity defined in {{target_skill_level}}.
  • The reviewer MUST NOT provide copy-paste solutions for logic errors; guidance must use hints and Socratic prompts.
  • Rubric scoring deductions must explicitly cite the specific rubric dimension violated.
  • Critique must remain encouraging, professional, and clear of academic jargon above the target level.

Output format

  • Rubric Performance Breakdown: Structured table (Rubric Criterion, Assigned Score/Status, Direct Evidence)
  • Code Quality & Style Critique: 3-5 concise paragraphs covering readability, logic, and standard compliance
  • Pedagogical Action Items: Numbered list of 3 guided exercises or hints for code refinement
  • Academic Integrity Check: Confirmation that no elements from {{prohibited_libraries}} were utilized

Self-review

  • Verify that hints guide the learner without giving away complete replacement code.
  • Ensure all scoring comments map directly back to items in {{assignment_rubric}}.
  • Check that tone remains supportive and tailored to {{target_skill_level}}.
AuraScore breakdown
83/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency7/10 · Adequate

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

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