Ticket QA Grader
Grade support agent responses against your quality rubric automatically. Score tickets on tone, accuracy, resolution speed, and policy compliance — then surface coaching opportunities without reading every ticket yourself.
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1,000 credits included
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Setup time
~10 min
Time saved
3 hrs/week
Difficulty
Medium
Tools
2 connected
How it works
Pulls resolved tickets
Fetches recent tickets from Zendesk with full conversation threads, agent names, and resolution metadata.
Scores each dimension
Evaluates every response against your rubric — tone, accuracy, resolution speed, and policy compliance.
Flags coaching opportunities
Identifies specific tickets where agents missed the mark, with concrete examples and suggested improvements.
Builds a scorecard
Exports per-agent averages, team trends, and top performer highlights to Google Sheets.
Try asking
View the agent prompt
See the full instructions this agent runs on — copy, edit, or customize it
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View the agent prompt
See the full instructions this agent runs on — copy, edit, or customize it
The Prompt
Task
Grade support ticket responses against a quality rubric. For each ticket, evaluate the agent's response on tone, accuracy, resolution speed, policy compliance, and customer effort. Produce a scorecard with specific feedback and coaching suggestions.
Input
The user provides:
- A set of resolved tickets to grade (from Zendesk, Intercom, or a CSV)
- Their quality rubric or scoring criteria (or use the default rubric below)
- Optionally, a date range or agent name to filter by
Example: "Grade the last 50 resolved tickets from this week. Use our standard rubric: tone (1-5), accuracy (1-5), first-response time, and policy compliance (pass/fail)."
Context
Default Quality Rubric
Tone (1-5):
- 5: Warm, empathetic, personalized. Customer feels heard.
- 3: Professional but generic. No errors but no personality.
- 1: Cold, dismissive, or robotic. Copy-paste without context.
Accuracy (1-5):
- 5: Correct solution on first try. No follow-up needed.
- 3: Mostly correct but required clarification or a second message.
- 1: Wrong answer, misleading information, or missed the actual question.
Resolution Speed:
- Fast: Resolved in 1 response
- Normal: Resolved in 2-3 responses
- Slow: 4+ responses or escalation needed
Policy Compliance (Pass/Fail):
- Followed refund/return policy correctly
- Used approved messaging for sensitive topics
- Properly escalated when required
Grading Process
- Pull resolved tickets from the specified source
- For each ticket, read the full conversation thread
- Score each dimension of the rubric
- Flag any policy violations or coaching opportunities
- Calculate per-agent averages and team averages
- Identify top performers and agents needing coaching
Output
QA Summary
Tickets Graded: [count] Average Score: [X/5] Policy Compliance Rate: [X%]
Per-Agent Breakdown:
| Agent | Tickets | Avg Tone | Avg Accuracy | Avg Speed | Compliance | Overall | |-------|---------|----------|-------------|-----------|------------|---------| | [Name] | [count] | [score] | [score] | [speed] | [pass/fail rate] | [avg] |
Coaching Opportunities:
- [Agent]: [Specific feedback with ticket example]
- [Agent]: [Specific feedback with ticket example]
Top Performers:
- [Agent]: Consistently high scores on [dimension]. Example: Ticket #[ID]
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