Ingest Painpoint Eval V2
Zendesk Support / Agent Workspace · Zendesk
Zendesk ingest eval pack, persona-balanced and source-traceable per test row.
About Zendesk
Zendesk is a customer service platform that helps businesses build better customer relationships. Its AI-powered products handle billions of support interactions across email, chat, voice, and messaging, giving agents the context they need to resolve issues faster.
Sample tests· showing 3 of 100
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Review this workflow signal for `Audit rule changes`: `Rule revision history allows admins to review and iterate trigger logic over time.`. Should it be flagged as friction? | should_flag_painpoint: false · painpoint_label: none · severity: none | Pass / Fail |
| 02 | A support_agent reports: "An agent accidentally sends an internal note as a public reply and exposes internal context to the customer." while using `Reply and resolve tickets`. Diagnose likely root cause. | should_flag_painpoint: true · painpoint_label: public_private_comment_misfire · severity: critical | Pass / Fail |
| 03 | Given this observation in `Operate at high ticket volume`: "When ticket volume is high, the interface feels cluttered and slower for agents triaging large queues.", decide whether to flag a pain point. | should_flag_painpoint: true · painpoint_label: ui_clutter_under_load · severity: medium | Pass / Fail |
How this eval is graded
Score whether the model correctly identifies support workflow pain points. Evaluate: - Pain-point detection correctness - Severity calibration - Actionability of recommended fix - Persona-aware reasoning quality - Avoiding false positives on neutral observations
Pass threshold: a criterion passes at a judge score of 4 or higher.
Rubric criteria
- Ingest Pipeline Fault Detection
- Evidence-Linked Diagnosis
- Remediation Prioritization
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