Grade every conversation, not just the obvious ones.
Every conversation your agent handles is graded against its own instructions. See exactly which rule was followed and which one slipped, the moment it slips.
The agent pulled the ticket, checked the customer's order history, and matched the refund window before replying.
Always confirm the customer's order details before quoting policy.
It offered a refund without asking the reason for return, which the instructions require.
Before approving a refund, ask the customer for the reason for return.
Ticket 8421 · refund reply
Yes · followed refund policy check
Ticket 8420 · shipping question
Partially · skipped tracking link
Ticket 8419 · return request
Yes · asked reason for return
Ticket 8418 · escalation
No · missed handoff step
Grade every conversation.
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Yes / Partially / No
A clear verdict on every conversation with a written rationale.
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Free with every plan
Continuous evaluation runs on every conversation, at no extra cost to you.
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Graded against the right version
Judged against the instructions that were live when the conversation happened, not what you've since edited.
The judge quotes the exact rule.
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Verbatim citations
When a rule is cited, it's quoted directly from your instructions. No paraphrasing.
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Followed, not-followed, ambiguous
Every rule the judge references is tagged so you can see at a glance what stuck and what slipped.
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Read it like a review, not a rating
Rule + reasoning together, so a reviewer knows exactly why a call was right or wrong.
Why · @wismoAgent · ticket 8421
Read the ticket, then went straight to the Shopify order lookup as instructed.
For every shipping question, look up the order before replying.
Included the tracking link and the delivery window in the same message.
Share the tracking URL and the estimated delivery window in the same reply.
The one slip: left the ticket status open when a pending status would have been more accurate.
If the customer is still awaiting delivery, set the ticket to pending before replying.
Watch adherence over time.
Every graded conversation contributes to a rolling adherence score. When it moves, you know exactly which rule started slipping.
Adherence score
86%
Last 30 days · @refundAgent
371 conversations judgedTop failing rule · 22 conversations
Before approving a refund, ask the customer for the reason for return.
Started slipping on July 2. Reverting the model on the sample set restored it within a day.
Extend it with a coding agent.
Continuous evaluation is a live signal you can wire into whatever comes after. A nightly summary. A Slack ping when adherence drops. A weekly report for your team.
Hand your Macha API key to Claude Code or Codex and it can read the shape of your evaluations and build the workflow you have in mind, without you writing the plumbing.
Build with Claude Code & Codex
#support-quality
Macha evals bot · 9:00 AM
Weekly adherence for @refundAgent
Yes
312
Partially
48
No
11
Top slip: "ask reason for return", 22 conversations.
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