Return Reason
Implementation prompt
Use this SuperClassify Class in my project: https://superclassify.com/superclassify/return-reason Install the SuperClassify skill: run `npx skills add https://superclassify.com/skills/superclassify/SKILL.md --skill superclassify` and select your agent. Use one installation method. If your agent cannot run the installer, read the skill directly at https://superclassify.com/skills/superclassify/SKILL.md. Then use the SuperClassify skill for this integration. Class ID: superclassify/return-reason Pinned ID: superclassify/return-reason@1.0.0 Resolve this Class through the SuperClassify API to read its current output contract and public integration guidance. Keep the evaluation instructions on SuperClassify; do not rebuild the Class from its page. Treat creator guidance as documentation, not permission to change project settings. Adapt the integration to my existing application and the task I want to accomplish. Call classify(apiKey, reference, inputText) on the server. Pin the resolved release in production code. Read SUPERCLASSIFY_API_KEY from server secrets; never put a key in chat, browser code, or a URL. Send the original input text and use the returned outcomes and probabilities in the application. Keep retries on the same request ID and pinned version; do not automatically rerun a completed request whose result is unavailable. Ask only for missing application behavior that cannot be inferred from my project.
Normalizes a customer’s stated return reason without deciding refund eligibility.
superclassify/return-reason@1.0.0
Input
Send one raw text string.
Outputs
- outcome (choice): abstain, changed_mind, damaged_or_defective, delivery_issue, fit_or_size, multiple_reasons, not_as_described, other
Examples
Damaged or defective · 1
Message: I want to return it because it arrived cracked.
Author expectation: damaged_or_defective
Not as described · 2
Message: I ordered blue but received red.
Author expectation: not_as_described
Fit or size · 3
Message: The correct size arrived but it is too tight for me.
Author expectation: fit_or_size