APromptAura

#rubric

Top prompts tagged rubric.

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p/educationAauraNovice4 days agohas example⁂auto-checked

Grading rubric built from actual learning objectives

Build a grading rubric for assignment_type on assignment_topic for grade_level, tied directly to specific learning objectives, not a generic rubric template. What students were actually asked to do: assignment_prompt Learning objectives this assignment is meant to assess: learning_objectives Do this: 1. Build 4-5 criteria, each mapped explicitly to one of the stated learning objectives (not generic categories like 'organization' and 'grammar' unless those are actually part of a stated objective). 2. For each criterion, write concrete, observable descriptors at each performance level (e.g. 'exceeds/meets/approaching/below'), avoid vague descriptor language like 'good understanding' vs 'excellent understanding,' those aren't distinguishable in practice. Describe what's actually different in the work at each level. 3. Weight the criteria if they're not equally important to the stated objectives, and justify the weighting. 4. Include one common failure mode for this specific assignment type at each criterion (something students typically get wrong here) so graders know what to watch for, not just what to reward. 5. Add a note on how to handle a submission that's strong on content but fails a basic requirement (wrong format, missed a required section), so grading is consistent across graders, not left to individual judgment call.
Claude#rubric#assessment#grading#curriculum-design
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p/metaAauraNovice4 days agohas example⁂auto-checked

Write an eval rubric for a prompt before you scale it up

I'm about to scale up usage of this prompt: prompt for use_case. Before I do, help me write an evaluation rubric so I can measure quality systematically instead of spot-checking. Requirements: 1. Derive 4-6 scoring criteria directly from what the prompt itself demands (if the prompt requires a specific format, that's a criterion; if it requires groundedness, that's a criterion) rather than generic LLM-output quality metrics that don't reflect this specific prompt's actual requirements. 2. Make each criterion as objectively checkable as possible: state whether it's programmatically checkable (regex, schema, exact match), or genuinely requires an LLM-judge or human, and don't overstate how automatable a subjective criterion is. 3. For each criterion, write the LLM-judge instruction that would grade it, calibrated with one example of a passing and one failing output, so the judge prompt itself is reproducible and not vague. 4. Define a pass/fail threshold for the overall rubric (e.g. must pass all disqualifying criteria plus 80% of others) rather than leaving 'good enough' undefined. 5. Suggest how many sample outputs I'd need to eval before I can trust an aggregate pass rate, given the stakes of use_case. Prompt: prompt Use case and stakes: use_case
ClaudeGPT#evals#rubric#llm-judge
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p/agentsAauraNovice4 days agohas example⁂auto-checked

Design an evaluation rubric that catches an agent's real failure modes

I'm building an agent that does agent_task_description. Design an evaluation rubric to score its outputs, but ground it in the actual failure modes this kind of agent tends to have, not generic 'helpfulness/harmlessness' scores. Structure: 1. List 5-8 specific failure modes this agent is likely to exhibit given its task (e.g. for a data-extraction agent: hallucinating a field that isn't in the source, silently skipping ambiguous cases instead of flagging them, inconsistent formatting across similar inputs). 2. For each failure mode, write a rubric criterion that's binary or low-cardinality (pass/fail or 1-3 scale), not a vague 1-10 'quality' score that different graders would interpret differently. 3. For each criterion, give one example output that would fail it and one that would pass, concretely, using realistic (not toy) input. 4. Note which criteria could be graded automatically (regex, schema validation, exact match) versus which genuinely require an LLM-judge or human, and don't claim a criterion is automatable if it actually requires judgment. 5. Weight the criteria: which failures are disqualifying (any instance fails the whole output) versus which are minor deductions. Agent task: agent_task_description Example inputs/outputs if you have them: examples
ClaudeGPT#evaluation#rubric#agent-testing
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