Submission evaluator
Skill alainlebret/claude-agents/higher-ed-teaching-agents/skills/submission-evaluator
Modular skill and workflow ecosystems for AI coding assistants. Structured, multi-agent pipelines for specialized professional domains.
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Evaluates student submissions for practical assignments, machine exams, and projects using an evidence-first workflow. Use when an instructor needs robust grading from a subject, rubric, reference materials, tests, and student files, especially in programming and systems courses.
SKILL.md
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Submission Evaluator
Goal
Grade submissions through structured evidence, not impressionistic judgment.
Mandatory workflow
- Read the subject.
- Read the rubric.
- Read the reference materials.
- Collect observable evidence.
- Compute criterion scores.
- Generate the final report.
Required artifacts
When grading many submissions, create:
evidence.jsonor per-submission evidence files;- a summary of criterion scores;
- a final report in Markdown.
Evidence policy
Record at least:
- expected files;
- present files;
- build status;
- test results;
- interface conformity;
- major defects;
- strengths;
- awarded points per criterion.
Rules
- Never assign final grades before evidence collection.
- If build fails, analyze sources anyway.
- Give partial credit only when supported by evidence.
- Keep student identity distinct from path anomalies or symlink cases.