Validate PromptSource-style prompt metadata and community quality constraints for natural-language prompts, metrics, answer choices, and target format.
Installs into .claude/skills of the current project.
Are you the author of Prompt Metadata Quality?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-prompt-metadata-quality)
---
name: prompt_metadata_quality
description: Validate PromptSource-style prompt metadata and community quality constraints for natural-language prompts, metrics, answer choices, and target format.
---
# Prompt Metadata Quality
Use this skill when reviewing PromptSource/P3-style prompt records before adding them to a prompt collection or using them in a recovery experiment.
## Inputs
- `metadata`: JSON object with fields such as `name`, `metrics`, `answer_choices`, `original_task`, `valid_outputs_stated`, `language`, and `reference`.
- `rendered_examples`: optional JSON list of rendered prompt records with `input` and `target`.
## Outputs
A JSON validation report with `ok`, `errors`, `warnings`, and `checked_fields`.
## Workflow
1. Require a prompt name and reference or rationale.
2. Validate metrics against the PromptSource metric vocabulary.
3. Validate language tags when supplied.
4. Check consistency between valid-output metadata and answer choices.
5. Inspect rendered examples for natural-language task statements and concise targets.
6. Return actionable review messages without mutating the prompt.
## Validation
Run:
```bash
python tests/test_prompt_metadata_quality.py
python scripts/validate_metadata.py --metadata-json '{"name":"based on passage","metrics":["Accuracy"],"answer_choices":["Yes","No","Maybe"],"valid_outputs_stated":true,"reference":"paper example"}'
```
## Limitations
This skill provides deterministic review checks. It does not replace human judgment for prompt usefulness or downstream model performance.